Z13 update

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Large Systems Update (LSU) 2015z Systems z13 update

Status, Trends and DirectionsKMD/JN Data Århus, December 8

The Modern Mainframe Redefining Digital Business, …at the brink of the Cognitive Era.

Version 5.9 December 2015

January 14, 2015 AnnouncementHenrik Thorsen, IBM Technical DirectorNordic z Systems Platform LeaderWith credit for certain charts to fellow IBMers

Trademarks

Notes: Performance is in Internal Throughput Rate (ITR) ratio based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput that any user will experience will vary depending upon considerations such as the amount of multiprogramming in the user's job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve throughput improvements equivalent to the performance ratios stated here.

IBM hardware products are manufactured from new parts, or new and serviceable used parts. Regardless, our warranty terms apply.

All customer examples cited or described in this presentation are presented as illustrations of the manner in which some customers have used IBM products and the results they may have achieved. Actual environmental costs and performance characteristics will vary depending on individual customer configurations and conditions.

This publication was produced in the United States. IBM may not offer the products, services or features discussed in this document in other countries, and the information may be subject to change without notice. Consult your local IBM business contact for information on the product or services available in your area.

All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.

Information about non-IBM products is obtained from the manufacturers of those products or their published announcements. IBM has not tested those products and cannot confirm the performance, compatibility, or any other claims related to non-IBM products. Questions on the capabilities of non-IBM products should be addressed to the suppliers of those products.

Prices subject to change without notice. Contact your IBM representative or Business Partner for the most current pricing in your geography.

This information provides only general descriptions of the types and portions of workloads that are eligible for execution on Specialty Engines (e.g, zIIPs, zAAPs, and IFLs) ("SEs"). IBM authorizes customers to use IBM SE only to execute the processing of Eligible Workloads of specific Programs expressly authorized by IBM as specified in the “Authorized Use Table for IBM Machines” provided at www.ibm.com/systems/support/machine_warranties/machine_code/aut.html (“AUT”). No other workload processing is authorized for execution on an SE. IBM offers SE at a lower price than General Processors/Central Processors because customers are authorized to use SEs only to process certain types and/or amounts of workloads as specified by IBM in the AUT.

* Registered trademarks of IBM Corporation

* Other product and service names might be trademarks of IBM or other companies.

Adobe, the Adobe logo, PostScript, and the PostScript logo are either registered trademarks or trademarks of Adobe Systems Incorporated in the United States, and/or other countries. IT Infrastructure Library is a registered trademark of the Central Computer and Telecommunications Agency which is now part of the Office of Government Commerce. Intel, Intel logo, Intel Inside, Intel Inside logo, Intel Centrino, Intel Centrino logo, Celeron, Intel Xeon, Intel SpeedStep, Itanium, and Pentium are trademarks or registered trademarks of Intel Corporation or its subsidiaries in the United States and other countries. Linux is a registered trademark of Linus Torvalds in the United States, other countries, or both. Microsoft, Windows, Windows NT, and the Windows logo are trademarks of Microsoft Corporation in the United States, other countries, or both. Windows Server and the Windows logo are trademarks of the Microsoft group of countries.ITIL is a registered trademark, and a registered community trademark of the Office of Government Commerce, and is registered in the U.S. Patent and Trademark Office. UNIX is a registered trademark of The Open Group in the United States and other countries. Java and all Java based trademarks and logos are trademarks or registered trademarks of Oracle and/or its affiliates.Cell Broadband Engine is a trademark of Sony Computer Entertainment, Inc. in the United States, other countries, or both and is used under license therefrom. Linear Tape-Open, LTO, the LTO Logo, Ultrium, and the Ultrium logo are trademarks of HP, IBM Corp. and Quantum in the U.S. and other countries.

The following are trademarks of the International Business Machines Corporation in the United States and/or other countries.

The following are trademarks or registered trademarks of other companies.

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• The following people “contributed” to this presentation:

• Riaz Ahmad, Matthias Bangert, Uno Bengtson, Mario Bezzi, Maria K Boisen, Nick Clayton,

• Donna Dillenberg, Martin Dvorsky, Michael Eggloff, Harv Emery, Cindy Grossman, Ray Jones,

• Frank Kyne (Watson & Walker), Parwez Hamid, Gerard Laumay, Helene Lyon, Silvia Melitta,

• Marianne Menå Heltborg, Frank Packheiser, Ewerson Palacio, Alain Poquillon,

• Per Rosenquist, Jørgen Riis Andersen, Jeff Seidell, Harri Stranden, Peter Sommer

• Christopher Spaight, Svenn-Aage Sønderskov (BEC), Henrik Thorsen, Robert Vaupel,

• Dan Wardman, Charles Webb

• ... and many many more

...Irv Gordon (”5 million km Volvo man”),

....Per Groth (”2 Volvo book writer”)

Acknowledgements Thanks!

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Agenda

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IT world transforming fast, creating extra MF requirements

• Consumer, Economic and IT MF perspective in ww, European, Nordic context

• Digital disruption, CAMSS, IoT, Cognitive Era

IBM servers holistic view – survival of the fittest

• IBM divesting 86-based servers, emphasizing z Systems and POWER brands

• What about Moore’s law? Silicon Semiconductor update

• Innovation much more than semiconductors and HW

IBM z Systems z13 enabling lower cost:

• Simultaneous Multithreading (SMT)

• Single Instruction Multiple Data (SIMD)

• Large Memory and Memory Affinity

• Significant I/O, Security and other enhancements

IBM z13 and Real Time Transaction/Predictive Analytics

IBM client value of HW/SW currency

IBM z13 Status:

• Obervations, tips and tricks, tools, videos

• workshops – ITSO, LinuxOne, GSE,...

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5

2014 Key IBM Systems Server Milestones

6

2015 Key IBM Systems Server Milestones

Systems HW Ongoing Transformation – 2015 Milestones

January

z13 launch

July

IBM launch 7 nm chip, world’s smallest:

GlobalFoundries and Samsung

March

3$B R&D investment in

IoT technology

LinuxONE Emperor,

world’s most advanced Linux

system

Welcome to the cognitive era

IBM CEO Rometty describes new era in

technology

August -YE

October

IBM POWER8

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7

The 3rd generation of computing platform, the 3rd phase of the Internet, and the explosion of information are colliding to form a perfect storm of disruption and transformation

2020-2

Amount of Data Collected and Stored

Adapted from HorizonWatch: Top Technology Trends To Watch In 2013 Source: Bill Chamberlin

1964 1981 1994 2003 2008 2012

Continuum of Computing Platforms

Mainframe

Client Server / PC

Mobile Devices

Internet Web 2.0Phases of

the Internet Web 3.0 (Cloud, Analytics, Mobile, Social)

IoT

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The 3rd generation of computing platform, the 3rd phase of the Internet, and the explosion of information are colliding to form a perfect storm of disruption and transformation

The Internet of Things – infographic The Connectivist based on Cisco data -2014

Source: Slide Share: Ammar Sabzwari

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Eras of Computing

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By 2018, 1/3rd of leaders in each industry will be disrupted by 3rd platform competitors.

The 3rd Platform allows businesses to:• Create greater operational

efficiencies• Build deeper relationships with their

customers• Create new revenue streams

based on technology-enabled products and services

The 3rd Platform is a Business Platform

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Digital Disruption is Real

1175% of S&P 500 companies may be replaced by 2027!

> 60 years

< 20 years

1st Platform 2nd Platform 3rd Platform

Digital Disruption is Real

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Everything in This 1991 Radio ShackAd Has BeenReplaced w/Apps Running on a Smartphone

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What drives Mainframe and z13 Growth?Share 2015 Perspective

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Systems of Insight drives Future Growth

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Eagle studies validate that adding workload to Mainframes reduces labor cost per unit of work

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Mobile, Mobile, Mobile!Transactions generate business, MF load,

and they are growing

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Mainframes in an Worldwide context:

• Recent past - 10 years ago• Less than 1 transaction a day

• Today – right now• Up to 37 transactions a day

• Future – 3 years and in 10 years• 2017 50 trans/day • 2025 1.6 Trillion+ trans/day from 10

Billion devices=1.600.000.000.000 transactions

30.000.000.000 MF business transaction today

50% Compound annual growth rate

Sources: Juniper, Gartner, Wall Street Journal Japan, IBM PoV

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The Platform for the FutureIDC says 60% critical apps run on IBM MF today

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Mainframes in an European context:

• 10.000 mobile transactions happened when you read the heading!

• Drive 12% of Europe's economy

• Generate more than 110,000 jobs

• Creates an ecosystem of 1000 partner organizations

• €5.6 billion ecosystem revenue

• Open architectures and Linux are sizzling

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20M+ 100B 6x and 3xapps in the world today

apps was downloaded in 2014

Google and Apple respectively have released more major Android and iOS versions than Microsoft has released

major Windows PC versions

Build and Connect

System z mobile web, hybrid, and native app development

System z data, service and application integration

Lifecycle management

Building and connecting System z data to mobile devices

to provide a better, more-secure customer experience

Building and connecting apps to z Systems

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Mainframes in a Nordic context:• ~ 90 Mainframes

• Surrounded by ~ 900.000+ other servers

• ~ 600.000 MIPs

• ~ 50% on latest z13 technology (~ 50% YE)

• ~ 2% of Worldwide MF server capacity

• Growth rate MIPs (5 YR CAGR) ~ 15%

• More for specialty engines

• Linux on z MIPs (5 YR) ~ 45%!

• ~ 1.000.000.000 MF business transactions/day

• ~ 50.000 MF business transactions/sec in peak

• MFs are vital to Nordic cooperations, our society, you,

IBM and myself

• Latest version MF z13 announced January 14, 2015

...continues to carry the torch


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• ~ 600.000 MIPs






• ~ 1-2.000.000.000 MF business transactions/day



IBM and myself


Mainframes in a Worldwide context:

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• ~ 600.000 MIPs






• ~ 1-2.000.000.000 MF business transactions/day



IBM and myself


Market Forces 2014-2018

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2018 Devices:• 2x growth

• 40 billion

• 5.0/person

2018 Mobile Users:• 50% growth

• 3.8 billion

• 50% penetration

… yesterday’s infrastructure won’t cut it…

2018 Datacenter Cores:• 2x growth

• 77 billion

• 10/person

2018 Data:• 3x growth

• 24 zettabytes

• 1.5 TBs/person/day

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IBM z Systems z13 Platform Positioning

• The world’s premier data and

transaction engine enabled for

the mobile generation

• The integrated transaction and

analytics system for right-time

insights at the point of impact

• The world’s most efficient and

trusted cloud system that

transforms the economics of IT

Transaction Processing

Data Serving

Mixed Workloads

Operational Efficiency

Trusted and Secure Computing

Reliable, Available, Resilient

Virtually Limitless Scale

2323

Enable superior Cloud services at up to 32% lower cost than x86 Cloud and up to 60% less than Public Cloud over three years

Deliver up to 36% better response time, up to 61% better throughput, and 17 to 37% lower cost per mobile transaction

Deliver insights up to 17x faster and with 13x better price performance than closest competitor

Accelerate speed of encryption up to 2X over the zEC12 to help protect the privacy of data throughout its life cycle

Cloud

Analytics

Mobile

Security

The all new IBM z13: Excel in Digital Business Against Competition

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Innovation Drives Performance

0%

20%

40%

60%

80%

100%

180 nm 130 nm 90 nm 65 nm 45 nm 32 nm 22 nm

Gain by Technology Scaling Gain by InnovationRelative %

of Improvement

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• Future growth also comes from dimensions other than hardware thread speed alone:

• Software efficiency – extract full performance value from System z hardware

– Compiler technology, dynamic optimization, exploit new architectural facilities

• Core density – multi-core processor chips

– More efficient use of space, less complex packaging

• Cache density – leveraging leadership eDRAM technology

– Larger caches closer to more cores

�Combined result: continued growth in system capacity each generation

• Sysplex scale – more systems sharing data and workloads

• Workload optimization via specialized capabilities

Compute Capability Trends

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Java

Semiconductor Technology

Microprocessor Design

Systems Design

Virtualization & Operating Systems

Compilers & Java Virtual Machine

Optimized Middleware

IBM z Systems z13

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IBM $3B R&D investmentin chip technologies over next 5 years

IBM is tackling chip challenges by launching two broad research and development programs:

1. 7nm and beyond silicon technology will address serious physical challenges that are threatening current semiconductor scaling techniques

2. Alternative technologies for post-silicon era chips under development:

• Silicon Photonics/Nanowire

• Silicium Germanium...

• (2012 9nm transistor)

• (2015 7nm experimental chip capableof holding up to 20 Billion transistors)

• Carbon Nanotubes

• Graphene

• Neurosynaptic Computing

• Quantum Computing28

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1. 7NM and beyond silicon technology will address serious physical challenges that are threatening current semiconductor scaling techniques





• (2012 9NM transistor)

• (2015 7NM chip))

• Graphene


• Quantum Computing - Qubits

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1. 7NM and beyond silicon technology will address serious physical challenges that are threatening current semiconductor scaling techniques





• (2012 9NM transistor)

• (2015 7NM chip))

• Graphene


• Quantum Computing


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5 year development effort, 1B$ and 500 patents/year involved in launch of z13

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z13 - Refined z Systems Architecture

• Performance: How fast a given piece of work can be done?

• Throughput: How much work can be done in a given amount of time?

• Performance and throughput are the combination of architecture, design innovation and

processor frequency (cycle time)

• z13 improvements delivered through:

– Design innovations such as increased cache sizes, Out of Order instruction processing,

restructured pipelines, increased n-way design, etc.

– Increasing Uni-processor performance with a reduction in cycle time when compared to zEC12

– Increasing the scale in the system N-way

– Introducing Simultaneous Multi Threading (SMT)

– Reintroducing SIMD vector processing

– Extending memory from 3TB to 10TB

Frequency Scalingx86, POWER, z Systems

� x86 and POWER already transitioned to a throughput-centric model

� Frequency peaked for x86 in 2005, POWER in 2008

� In System z we have held this off with unique cooling, packaging, technology, and design solutions

Fre

quency

(MH

z)

0

1000

2000

3000

4000

5000

6000

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

x86

Power

System z

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CPU core speed vs Computer Performance

� Why the overall CPU frequency approach is changing ?̶ Consistent frequency growth in the past decade

• from hundreds of MHz to GHz ̶ CPU frequency has reduced in the past couple of years

� Designing chips for better performance̶ Limits are imposed by physics, technology or economics ̶ Controls the rate of improvements in different dimensions̶ Different processor architectures have different issues with overclocking

� Physical limitations ̶ Speed of light limits how fast signals travel form one end to the other on a chip̶ Power and heat dissipation̶ Cooling̶ How many memory elements (caches) can be within a given latency from the CPU

� Physical limitations force the designers to make trade-offs̶ “Shrinking” a processor chip

• pro: Faster due to the shorter distances• con: Reduced area for dissipation

� Power dissipation increases as the chip speeds up̶ Raising the processor voltages would make transistors to switch quicker

• pro: Frequency could then be increased• con: current also increases creating more heat

� Sounds easy.. but… it causes serious problems with heat� Emerging technologies allow frequency variation according to processing needs

CPU Clock speed versus Computer Performance…

� GHz is not the only dimension that matters̶ System z focus is on balanced system design across many factors:

• Frequency, pipeline, efficiency, energy efficiency, cache/memory design and I/O design • Greater logic density, power density, wire-ability. All permits more cores per chip, larger

cache, additional execution units/circuits, addition of SMT and SIMD on each core.

� System performance is not linear with frequency ̶ Need to use LSPR and System z capacity planning tools for real client / workload sizing

� System z leverages technologies to get the most out of chips design ̶ Low latency pipelines ̶ Dense packaging with proper cooling which yields more power-efficient operation̶ Consistent performance at high utilization

� The IBM z13 Server is a significant change from zEC12̶ Processor speed measured in instructions per second (for a given workload) has increased as

compared to the zEC12.• Wider pipeline (up to six per cycle)• Enhanced branch prediction• Optimized resolution of dependencies between instructions.

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z Systems - Processor Roadmap

z1969/2010

zEC128/2012

z102/2008

z131/2015

Leadership Single Thread, Enhanced Throughput

Improved out-of-order

Transactional Memory

Dynamic Optimization

2 GB page support

Step Function in System Capacity

Top Tier Single Thread Performance System Capacity

Accelerator Integration

Out of Order Execution

Water Cooling

PCIe I/O Fabric

RAIM

Enhanced Energy Management

Leadership System Capacity and Performance

Modularity & Scalability

Dynamic SMT

Supports two instruction threads

SIMD

PCIe attached accelerators (XML)

Business Analytics Optimized

Workload Consolidation and Integration Engine for CPU

Intensive Workloads

Decimal FP

Infiniband

64-CP Image

Large Pages

Shared Memory

� 8 double-wide cores per CP chip

� 2X Instruction pipe width

– Improves IPC for all modes

– Symmetry simplifies dispatch/issue rules

– Required for effective SMT

� Added FXU and BFU execution units– 4 FXUs (Fixed point units)– 2 BFUs (Binary floating-point units)– DFUs (Decimal floating-point units) – 2 new SIMD units

� SIMD unit plus additional registers

� Pipe depth re-optimized for power/performance

– Product frequency reduced (5.0 GHz)

– Processor performance increased

� SMT2 support

– Wide, symmetric pipeline

– Full architected state per thread

– SMT-adjusted CPU usage metering

z13 Processor Overview Enhancements at a glance

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IFB

ICM

LSU

L2D (eDRAM)

RU

IDU

ISU

XU TU

VFU

FXU

IFB

ICMLSU

ISU

IDU

FXU

RU

L2DL2I

XUPC

VFU

COP

Where is the SIMD Unit?

Fixed Point Unit• Counters (Loops)• Adresses

Vector & Float Unit• Fixed Point Decimal (BCD)• Floating Point HEX• Floating Point BINARY• Floating Point DECIMAL• Vector string processing• Binary vector integer

z13 VFU (Vector and Floating-Point Units)• Enhancements

– Two execution pipelines & 4x FPU / VFU registers

– SIMD & string (new engine)

• String processing & vector execution of binary integer

– DFX (decimal FXU)

• new engine optimized for BCD add/sub/compare

• zEC12: these ops executed on DFU

– BFU: Binary & Hex floating-point unit

• new: Vector support for Binary 64b float

– Leading edge Divide/sqrt engine for binary & hex FP

• zEC12: divide & square-root executed in the BFU

• Shorter latency and higher throughput than zEC12

– DFU: decimal floating-point unit

• 3rd generation, allowing for higher throughput

• Executes BCD mul, div, convert, shift

– All Units are implemented twice – so in the best case this doubles

througput compared to zEC12

BFU

BFU

Divide

Divide

DFU

DFU

DFX

SIMD&String

DFX

SIMD&

String

RegFiles

RegFiles

zEC12 FPUs

Silvia M Mueller, Jan/2015

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� New Memory Controller

� Crypto Express5S

� FICON Express16S

� 1U Support Element

� Standalone zBX Node Hybrid Computing

� 2.7M lines of firmware changed

� Radiator Design improvements

� Expanded operating environment (Rear Doors)

� 22nm Processor with SIMD, SMT

� Integrated I/O with PCIe Direct Attach

� Single Chip Modules

� Drawer-Based CPC Design

� Cable-Based SMP Fabric

� Oscillator Backplane

� Flexible Service Processor (FSP2)

� Integrated Sparing

� On-chip power/thermal monitor / control

z13 System Design Changes

� New Memory Controller

� Crypto Express5S

� FICON Express16S

� 1U Support Element

� Standalone zBX Node Hybrid Computing

� 2.7M lines of firmware changed

� Radiator Design improvements

� Expanded operating environment (Rear Doors)

� 22nm Processor with SIMD, SMT

� Integrated I/O with PCIe Direct Attach

� Single Chip Modules

� Drawer-Based CPC Design

� Cable-Based SMP Fabric

� Oscillator Backplane

� Flexible Service Processor (FSP2)

� Integrated Sparing

� On-chip power/thermal monitor / control

z13 System Design Changes

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Physical node: (Two per drawer)� Chips

– Three PU chips (with up to 8 active cores each)– One SC chip (480 MB L4 cache)

� RAIM Memory– Three Memory Controllers: One per CP Chip– Five DDR3 DIMM slots per Controller: 15 total per logical node– Populated DIMM slots: 20 or 25 per drawer

� SC and CP Chip Interconnects– X-bus: SC and CPs to each other (intra node)– S-bus: SC to SC chip in the (intra drawer) – A-bus: SC to SC chips in the remote drawers (intra box)

Mem

PSI

Mem

GX Bus

2x PCIe

GX Bus

2x PCIePUPU

SCSC

MemMem DIMMs

GX Bus

2x PCIe

Node 1

GX Bus

2x PCIe

GX Bus

2x PCIe

GX Bus

2x PCIe

Fully Populated Drawer

MemMem

A-Bus

S-Bus

X-Bus

Node 0

X-Bus

SCSC

A-Bus

To otherdrawers

To otherdrawers

z13 Drawer Structure and InterconnectDrawer Based SMP Topology

Node 1 Node 0

Node 1 Node 0

Node 1 Node 0

Node 1 Node 0

Drawer

Drawer

Drawer

Drawer

PU

PU

PU PU

PU

z13 versus zEC12 HW Comparison… and z196

� zEC12 (z196)

– CPU

• 5.5 GHz (1514 PCI)

• Enhanced Out-Of-Order

– Caches

• L1 private 64k i, 96k d (Same)

• L2 private 1 MB i + 1 MB d (1.5 MB)

• L3 shared 48 MB / chip (24 MB)

• L4 shared 384 MB / book (192 MB)

� z13– CPU

• 5.0 GHz (1695 PCI)

• Major pipeline enhancements

– Caches

• L1 private 96k i, 128k d

• L2 private 2 MB i + 2 MB d

• L3 shared 64 MB / chip

• L4 shared 480 MB / node

- plus 224 MB NIC

...

Memory

L4 Cache

L2

CPU1

L1

L3 Cache

L2

CPU6

L1... L2

CPU1

L1

L3 Cache

L2

CPU6

L1...

...

Memory

L4 Cache

L2

PU1

L1

L3 Cache

... L2

PU8

L1

L2

PU1

L1

L3 Cache

...L2

PU8

L1

...

Memory

L4 Cache

L2

PU1

L1

L3 Cache

... L2

PU8

L1

L2

PU1

L1

L3 Cache

...L2

PU8

L1

Single Book View

Single Drawer View

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z13 Architecture ExtensionsCore, SIMD, SMT-2

• Core micro-architecture radically altered to increase parallelism– New branch prediction and instruction fetch front end

• Supports SMT-2 and improves branch prediction throughput for all modes

– Wider instruction decode, dispatch and completion bandwidth:

• Up to six instructions per cycle compared to three on zEC12

– Up to ten instructions issued for execution per cycle compared to seven on zEC12

• 2 branch, 4 FXU, 2 LSU, 2 BFU/DFU/SIMD

• Single Instruction Multiple Data (SIMD) instruction set and execution: Business Analytics Vector Processing

– 139 new instructions operate on 32 new 128-bit registers

– String, vector integer and vector floating point operations

• Two 64-bit, four 32-bit, eight 16-bit, or 8-bit operands per register

• Two-way simultaneous multithreaded (SMT-2) operation– Up to two active execution threads per core

• Dynamically share caches, TLBs, and execution resources.

• Significant boost in core and chip throughput on top of core performance increase

– SMT-2 operation supported for IFLs and zIIPs

– Hardware monitoring support for chargeback and capacity planning

43

Simultaneous Multi-threading (SMT)

• Simultaneous Multi-threading (SMT) technology • Multiple programs (software threads) run on same processor core• More efficient use of core hardware

• Active threads share core resources• In space: data and instruction caches, TLBs, branch history tables, etc.• In time: pipeline slots, execution units, address translator, etc.

• Increases overall throughput per core when SMT active• Amount of increase varies widely with workload – typically 1.2-1.6X• Each thread runs more slowly than on a single-thread core

A/B

A

B

B

Load/Store (L1 Cache)

A A B

Execution Units (FXU/FPU)

instructions

A B A A

B AA

B

Shared Cache

A B A A

B A

BA

Cache

Thread-A

Thread-B

Use of Pipeline Stages in SMT-2

Both threads

Stage idle

44

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Simultaneous Multi Threading (SMT2)

• Simultaneous multithreading allows instructions from more than one thread to execute in any given pipeline stage at a time

• SMT helps address memory latency, resulting in overall throughput gains

• It can increase processing efficiency, and throughput

• Currently available on IFLs (Linux and z/VM) and zIIPs (z/OS)

• The number of concurrent threads is limited to two and can be turned on or off by an operator command and also set up through parmlib for z/OS

45

Which approach is designed for the highest volume of

traffic? Which road is faster?

Illustrative numbers only

Note: SMT is designed to deliver better overall throughput for many workloads. Performance in some cases may be superior using single threading

Why only 45?

SMT dependency on Job runtime

• SMT increases the efficiency of a core. Instead of lets say running 100 instructions per

TIME in a single thread, SMT allows running more than 100 instructions in 2 threads in the

same TIME.

• However, sharing one ressource amoung 2 threads is „not for free“. There is a „cost“

associated.

• SMT Effectivness = (SMT Throughput / Single Thread Throughput).

– Lets assume we can run 125 instructions in the same timeintervall with SMT switched on we

would end up with SMT Eff. = 125 / 100

• The „cost“ is, that both threads run slower than a single thread.

• The elongation is calculated as: Elongation % = (2 / SMT Eff.) - 1

– In our example the single threads would run 60% slower than before.

• Lets assume your client has a system zEC12 with 10 ZIIPs.

– Because of z13‘s single thread performance improvement you only need 9 ZIIPs now

– With SMT switched on and 25% efficiency improvement you end up with 7 ZIIPs.

– In that case all workload on your ZIIPs will run 60% slower than without SMT and 46% slower

than before on zEC12.

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Remarks on SMT

• For z/OS

– You enable SMT in LOAD xx at IPL

– Once done, enable/disable SMT per LPAR by dynamically activating different

OPT files.

• For native Linux

– There is no support (yet) in Redhat or Suse Linux for SMT.

– This is expected to be available in Q3 2015.

• For z/VM

– No dynamic switching of SMT modes

– Linux running under z/VM can exploit SMT

• Throughput improvements dependent on the workload with SMT:

– SAP runs very nicely with SMT switched on (large SMT throughput benefit)

– Imagine you are running OLTP transactions and time critical Batch Jobs on a

single core with SMT switched on – may be less beneficial (Bad Cache lines)

Enterprise Level Multithreading Expands capacity without compromising predictability

• z13 delivers significant boost in IFL and zIIP performance (throughput and capacity) via simultaneous multithreading (SMT)

• Extends per-processor capacity growth beyond single-thread performance

• z13 will support 2 threads per core

• Design will preserve unique System z values and attributes• Predictable core capacity with precise utilization measurement

– Supports chargeback, billing, and capacity planning

• SMT enablement independently controlled by LPAR• Operating systems must be explicitly enabled for SMT

• Operating system may opt to run in single-thread mode

• SMT control coordinated across hardware, hypervisors, software• Operating system running in LPAR controls use of threads in each core

– Transparent to the application

• Hypervisors can leverage SMT for image consolidation

• Functionally transparent to middleware and applications• Each hardware thread has full z/Architecture processor function

• No changes required to run in SMT partition

48

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49

z13 and Simultaneous Multi Threading• Simultaneous Multi Threading (SMT2) is available on IFLs and zIIPs only (currently)

– 10% to 35%+ throughput improvement on top of Uni-processor performance gains

• IFLs: 10% to 32%

• zIIPs:10% to 40%

– Will affect throughput (amount of work that can be done) versus performance (speeding up the IFL / zIIP)

• Be sensitive to workloads that need fastest possible single thread performance– Individual work units may run slower due to each thread running slower on an SMT enabled core

• Example: If a core can do 1000 MIPS without SMT (one thread) and with SMT turned on runs 2 threads giving 40%

more throughput, then the core will deliver 1400 MIPS with SMT. Since the 1400 MIPS is the sum of the two threads,

each thread will be running at 1400/2 = 700 MIPS

– Workloads, jobs, transactions that are CPU bound and very response time or

elapsed time sensitive many not want to exploit the throughput benefits of SMT

• Capacity planning tools for SMT – For IFLs: Assume 20% increase in throughput due to SMT

– For zIIPs: Assume 25% increase in throughput due to SMT

– Capacity planning tools will initially default to 20% throughput improvement for IFLs and 25% throughput

improvement for zIIPs

– Tools will be updated with the latest information

– Remember that SMT throughput is in addition to benefits seen from the faster uni processor

• Overall guidance: Processor speed + SMT benefit

– IFL: 32% = 10%+ + 20%+

– zIIP: 40% = 10%+ + 25%+

Note: SMT is designed to deliver better overall throughput for many workloads. Performance in some cases may be superior using single threading

A3 B3 C3

A2 B2 C2

ScalarSINGLE INSTRUCTION, SINGLE DATA

SIMDSINGLE INSTRUCTION, MULTIPLE DATA

Instruction is performed for every data element

Perform instructions on every element at once

Sum and Store

C1

C2

C3

A1 B1

A2 B2

A3 B3

INSTRUCTION

A1 B1 C1

Sum and Store

SIMD (Single Instruction Multiple Data) Increased parallelism to enable analytics processing

• Smaller amount of code helps improve execution efficiency

• Process elements in parallel enabling more iterations

• Supports analytics, compression, cryptography, video/imaging processing

• Exploitation by (partial list):

– Java8 and C/C++ for z/OS and Linux on System z; GCC for Linux on System z

– Enterprise COBOL for z/OS, PL/1

– MASS and ATLAS math libraries from Rational for z/OS and Linux on System z

– ILOG-CPLEX, z/OS XML System Services

50

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26

Single Instruction Multiple Data (SIMD)Introduction and background

51

� Motivation / Background– The amount of data is increasing exponentially - IT shops need to respond to the diversity of data– Enterprises use traditional integer, floating point data; also string, XML character-based data– It’s becoming more important for customers to do computations, analytics closer to the data

� Customer Perception of Analytics and System z– System z handles OLTP and Batch; lots of math and changing data is too compute intensive for z

� Reality of Analytics and System z– For last 2-3 generations, z has changed its capabilities in compute processing space (analytics)

• Superscalar, Out of Order (OoO), compiler improvements, floating point

• Legacy Capabilities: quad precision floating point, fuse/multiply/add– SIMD provides next phase of enhancements for analytics competitiveness on z

� SIMD Objective– Leverage data intensity and be competitive with large data volumes; compete by doing more operations on a given

byte of data, extract more interesting insight, and turn that insight into customer inspiration

� Workloads that may benefit from Data Parallelism (SIMD) – High Data Intensity (i.e. data volume)– High Compute Intensity (i.e. operations on a given byte of data)– Predictive IT analytics, Advanced Security/Crypto, BI reporting, Prescriptive Analytics, Next-Gen Data Warehousing

� Use Cases– Reporting functions: Querying and populating reports, often in batch fashion to process lots of data quickly– Numerically intensive processing

• i.e. time forecasting, simulation; ex: Tivoli based analysis with capacity management– Modelers, matrix intensive computations– ILOG CPLEX: optimizations; i.e. delta cruise scheduling, linear programming

Instruction pool Data pool

Results

Instruction pool Data pool

Results

Single Instruction Multiple Data (SIMD) Vector Processing

• When used with provided libraries and compilers: – creates a platform for numeric and data intensive computing, – minimizing effort on the part of middleware/application developers for exploitation.

This capability enhances analytics and big data capability of z13

Key enablers:� Libraries: MASS, ATLAS� Compliers: XLC, Java.Next

� String processing: � Java / Cobol / PL1 string, XMLSS, Cognos� Binary Floating Point

� ILOG, SPSS, analytics, mobile codes

OS/Hypervisor Support:� z/OS: 2.1 SPE� Linux: SLES12 SP1 and RHEL7.2

WorkloadsJava.Next C/C++Compiler built-ins

for SIMD operations (zOS and zLinux)

MASS & ATLASMath Libraries

(zOS and zLinux)

SIMD Registers and Instruction Set

52

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27

SIMD - Exploitation

� New z13 assembler instructions which directly use the vector facility (this is not the full list):• VL Vector Load • VLL Vector Load with Length• VSTL Vector Store with Length• VCEQ Vector Compare • VFAE Vector Find Any Element Equal• VFEE Vector Find Element Equal• Using these instructions promises maximum improvements from SIMD• ILOG CPLEX, COBOL Inspect .. Tallying, JAVA8, self written ASM programs

� All floating point operations will benefit – without change – from the new VFU design (all units are doubled now compared to zEC12).

tor Element Rotate and Insert under Mask

53

Java 8SIMD Vector Engine Exploitation

54

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28

Java Performance on z13By Java version, HW generation, and w/w/o SMT

30 % increasein Throughput

55

1999

2009

199

8

2001

2003

2005

2007

SDK1.4 1. 31-bit z/OS and 31-bit and 64-bit Linux on z2. GA 4Q20023. z/OS End of Marketing September, 20084. z/OS End of Service September, 2011

31-bit and 64-bit SDK 51. IBM J9 2.3 VM and JIT Technology2. z9 Exploitation3. GA 4Q20054. z/OS and Linux on z

31-bit SDK1.1.81. OS/390 GA 19992. Out of service

31-bit and 64-bit SDK 6 , V6.0.01. Supplies Java SE 6 APIs2. z10 Exploitation3. IBM J9 2.4 VM and JIT Technology4. GA 4Q20075. z/OS and Linux on z

31-bit SDK1.3.11. z/OS and Linux on z2. GA 3Q20003. End of Service: September, 2007

z/OS 64-bit SDK 1.4.21. IBM J9 2.2 VM and JIT Technology (1st product use)2. GA 4Q20043. End of Service September, 2008

31-bit SDK1.1.1, then 1.1.4 and 1.1.61. First OS/390 Java product – GA 19972. Out of service

2014

31-bit and 64-bit z/OS Java SDK 6 V6.0.1

1. Supplies Java SE 6 APIs2. z196 Exploitation3. New IBM J9 2.6 VM and JIT Technology4. Enhanced JZOS and z/OS Security5. z/OS Java products, GA March 2011:

System z Java Product Timeline

31-bit and 64-bit Java SDK 7.x1. z/OS and Linux on z2. Supplies Java SE 7 APIs3. OpenJDK4. z196/zEC12 Exploitation5. New IBM J9 2.6/2.7 VM and JIT

Technology6. GA Oct 2011

Testimonials: http://www.ibm.com/software/os/systemz/testimonials/

IBM continues to invest aggressively in Java for System z, demonstrating a rich history of innovation and performance improvements.

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STIz990/z890

STIz9

InfiniBandz10/z196/z114/zEC12/zBC12

STI: Self-Timed Interconnect

6 GBps

2 GBps

PCIe Gen2zEC12/zBC12/

z196/z114

16 GBps

System z I/O Subsystem Internal Bus Interconnect Speeds

PCIe Gen3z13

8 GBps

2.7 GBps

57

New FICON Function on z13• 16 Gbps Link Speeds

– Designed to reduce I/O latency to improve response time for performance-critical middleware and to shrink the batch window required to accommodate I/O bound batch work

• FICON Dynamic Routing – September 2015 – Designed to allow ISL sharing by FC and FCP traffic to optimize use of ISL bandwidth in the SAN

fabric for both types of traffic

• SAN Fabric Priority – September 2015 – Extends z/OS WLM policy into the SAN fabric

– Gives important work priority to get through SAN traffic congestion (e.g. after SAN hardware failures)

• zHPF Extended Distance II – June 2015– Up to 50% I/O service time improvement for remote write

– Designed to help GDPS HyperSwap configurations with secondary DASD in remote site

• 32K devices per FICON channel – Up to 85 Logical Partitions: More flexibility for server consolidation

• Preserve Virtual WWPNs for NPIV configured FCP channels– Designed to simplify migration to a new-build z13

• Forward Error Correction Codes – September 2015 – Designed to addresses high bit-error rate on high frequency (>= 8Gb/s) links

– Estimated equivalence to doubling optical signal power

• 6th Logical Channel Subsystem – Up to 85 Logical Partitions: More flexibility for server consolidation

• 4th Subchannel Set– Simplifies I/O configurations for a 2nd synchronous copy of data

– With multi-target PPRC, can do HyperSwap and still maintain synchronous copy for 2nd HyperSwap58

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30

DS8870 and z13 Improve performance and resiliency for mainframe environments

59

• January 2015 Preview announcement DS8870

• FICON Dynamic Routing

– Reduce costs with improved and persistent performance for

supporting I/O devices

• 16Gb host adapters

– Improve network performance with 2x faster FC and FICON

adapters; minimize latency for DB2 log writes with zHyperWrite

• Forward Error Correction

– Preserve data integrity with more redundancy on the information

transmitted via 16Gb adapters

• zHPF Extended Distance II

– Increase remote data speed with 50% better IO performance for

remote mirror

• Fabric Priority

– Improved resiliency capabilities while enhancing the value of FICON

Dynamic Routing

120014000

31000

20000

52000

23000 23000

92000

110000

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

I/O driver benchmark I/Os per second4k block sizeChannel 100% utilized

FICONExpress4

andFICON

Express2

zHPF

FICON Express8

zHPF

FICON Express8

FICONExpress4

andFICON

Express2

ESCON

zHPF

FICON Express8S

FICON Express8S

z10 z10z196z10

z196z10

zEC12zBC12

z196,z114

zEC12zBC12

z196,z114

350520

620770

620 620

1600

2600

0

200

400

600

800

1000

1200

1400

1600

1800

2000

2200

2400

2600

2800

3000

FICON Express44 Gbps

I/O driver benchmarkMB/secondFull-duplexLarge sequentialread/write mix

FICONExpress44 Gbps



FICON Express8S

8 Gbps

FICON Express8S

8 Gbps

z10 z10z196z10

z196z10

zEC12zBC12

z196,z114

zHPF

zHPF

zHPF

zEC12zBC12

z196,z114

z13GA1

zHPF

FICON Express

16S

z13GA1

FICON Express

16S

z13GA1z13

GA1

FICON Express

16S16 Gbps

FICON Express

16S16 Gbps

zHPF

zHPF and FICON Performance z13 GA1DS8000 enhanced to support FICON16S

63% increase

60

20% increase

(Controlled measurement environment, results may vary)

12/10/2015

31

60000

84000

92000

110000

0

20000

40000

60000

80000

100000

120000 I/Os per secondRead/writes/mix 4k block size, channel 100% utilized

z10 z196, z10

z13 GA1zEC12zBC12

z196, z114

520

770

1600

2500

0

500

1000

1500

2000

2500 MegaBytes per second (full-duplex)Large sequential Read/write mix

z10 z196, z10

56% increase

20% increase

FE44 Gbps

FE8S8 Gbps

zEC12zBC12

z196, z114

FE88 Gbps

FE8S8 Gbps

FE16S16 Gbps

FE16S16 Gbps

z13 GA1

FE88 GbpsFE4

4 Gbps

FCP Performance for z13 GA1

61

FICON Express 16S

• 16 GB/sec link speed–QLogic HBA supports 4G / 8G / 16G

–New standard 64b / 66b encoding

• Improves link data efficiency

–HBA code in IBM memory

• Simplifies Qlogic code updates

• Reduced latency for large block transfers–z/OS DB2 Log writes

� 12-14% latency reduction in 128K log writes

� Up to 5-6% improvement in Transaction Latency

–z/OS Managed file transfer

� DS8000 zDDB feature - exchange data through the SAN

–Reduced batch window

• Forward Error Correction–Addresses higher error rates at 16GB

• Sensitivity to damaged / faulty optical cables

–Improved fault isolation for optical links

–IBM leading standards to enable FEC

• Fabric Priority–Cooperative design across adapter / switch / control unit

–Each operation given priority by z/OS / WLM

• Priority propagated across SAN fabric

–Ensures consistent performance for most important work

Z13 GA1 (1Q2015)

FL

SFP+

SFP+

DRAM

PG2

PG2

CNA

CNA

FL

CFAM-S

SW

Storage Card (LX, SX)PG2 ASIC4/8/16GFC CNA ASIC

Universal FC/FICON spare

FICON Express16S Card

62

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32

More Memory Makes a Huge Difference

Adding more memory can enable you to…– Cut response time – up to 70% reduction for SAP transactions

– Achieve faster decision making by leveraging in memory data

– Shrink batch windows with no change to applications

– Deploy and support more Linux workloads in the same system footprint

– Improve system performance (reduced MLC), minimize constraints, and simplify management of

applications with database exploitation of additional memory

– Get more work done

z13 offers up to a Maximum of 10TB (10,000 GB)� Up to 2.5 TB per model increment � Leadership reliability and availability with RAIM� LPAR support of the full memory configured

� Elimination of the 1TB limit� z/OS 2.1 (with SPEs) to support up to 4TB per image� z/VM 6.4 to support up to 1TB per VM guest

63

64

Memory Delivers Additional BenefitsGo for mega memory…

� Enable totally new types of applications

− Perform faster table scans with in memory data for faster response time; reduce CPU by avoiding IO

� Simplify Memory capacity planning

− Reduce need to fine tune memory

� Accommodate growing batch workloads

− Run sorts using large memory, improving CPU consumption and elapsed times

� Now easily support new modern computing languages and architectures

− Java and other memory intensive languages

� Customers can see CPU savings

− See up to 5% CPU savings with DB2 tuning enabled by Large Memory

− See 5% CPU savings for typical workloads, in some cases up to 20% in certain environments, e.g.; when using SAP with DB2

− Your mileage may vary, and is highly depending on buffer pool hit ratios

70GB buffer pools 1MB frames with Page Fixed is the best performer

Candidates benefiting from large memory include:

� Analytics

� Java

� DB2

� Cognos

� Indexing

� Batch

� LE

� CF

� PR/SM

1.5

1.55

1.6

1.65

4K Pagable 4K Fixed 1M Pagable 1M Fixed

milli

-se

co

nd

s

Total DB2 CPU time per Transaction

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33

z13 PR/SM Role and Capabilities expandedDynamic Memory Management!

• zEC12 and earlier PR/SM controlled

relationship between logical and physical

CPs. it pseudo-dedicate physical CPs to

vertical high logical CPs, and try to keep

logical CPs for an LPAR together in 1 book

and one chip, to maximize the value of the

L3 and L4 cache. PR/SM can change

relationship and transparently move logical

CPs between physical CPs.

• z13 capabilities of PR/SM expands. Not only

assigning logical CPs to physical CPs, now

also responsible for controlling where the

memory for each LPAR will be allocated.

And it is now able to not only dynamically

move logical CPs between drawers, it can

also (transparently) move memory between

drawers.

• The complex algorithms PR/SM uses to

determine best location for each LPAR

include considerations, including:

– The number and type of logical CPs

in LPAR.

– The LPAR's weight as % of total

weight of all active LPARs (fair

share' of overall capacity).

– The number of vertical high, vertical

medium, and vertical low (“parked”

and “un-parked”) CPs in the LPAR.

– The amount of LPAR memory and

drawer memory.

– The number of assigned and

unassigned PUs in each chip, node,

and drawer.

– Many others.

65

IBM z13 Large MemoryClient Value from Large Memory

• Response Time: Consistent, fast transactional response time drives a series of

bottom line benefits for Clients including higher productivity and sales.

• Availability Gains: The culture to hoard memory and tune tightly exists. 3X and

mega memory help break this. Availability gains show up in (1) how well the system

survives I/O disruptions (2) workload tuning to handle spikes and (3) all of the Flash

use cases get better (workload startup and failure scenarios).

• Application Productivity and Memory Hungry Workloads: Analytics and other

large memory users can be placed closer to data. Changes to charge back

allocation reflecting the lower cost of memory enable Application Designers' use of

caching software layers and other industry performance and productivity technology.

• Long Term Architectural Vision: The 3X memory purchase acts as a shock to the

system to move the balance point of workloads towards gaining the advantages of

large memory usage. This change in vision in an organization is a very significant

Client advantage of the 3X and Mega memory pricing approaches.

(Controlled measurement environment, results may vary)

http://www.redbooks.ibm.com/abstracts/redp5146.html?Open

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34

IBM z13 Large Memory Enabling optimal middleware efficiency

• DB2 Buffer pools

– By configuring more memory for DB2 buffer pools

• up to 3% CPU time savings

• up to 10% transaction response time savings in the DB2 portion of their workload

– DB2 synchronous I/O simulation tool now available on DB2 11

• Predict expected reduction in sync I/O resulting from a specific increase in the size of a

DB2 buffer pool

• Estimate CPU savings based on reduction in sync IOs /sec

• IMS

– Page fix IMS Full Function database buffers

• Improve response time for IMS DB accesses from application

• Save up to 3% CPU time of the IMS portion of your workload

• MQ

– Large memory for IBM MQ V8 can help to cost effectively manage the

increasing message volumes generated from today's mobile and cloud

applications

(Controlled measurement environment, results may vary)http://www.redbooks.ibm.com/abstracts/redp5146.html?Open

IBM z13 Large Memory Unleashing the Next Wave of Innovation

• MDM (InfoSphere)

– Right-sizing your group buffer pools

• Configure large enough group buffer pools to cache all MDM Tables and indexes

– Internal measurements

• Increasing group buffer pool size from 120 GB to 565 GB and retaining all MDM

tables and indexes in the group buffer pool

• Reduced CPU time by 6.8%

• Reduced application elapsed time by 18%

• Java / WAS

– Allow larger Java heaps and more Java instances

• Reduce latency and CPU cost

• Cognos Dynamic Cubes on z/OS

– Data in memory for faster report generation

– Scale up from 1 to 3 Cognos instances with

– Increasing one COGNOS Instance to 3 instances using 480GB, we

measured 95% scale efficiency

(Controlled measurement environment, results may vary)http://www.redbooks.ibm.com/abstracts/redp5146.html?Open

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35

IBM z13 Large Memory Demonstrating Customer Value

• Ensure that middleware is optimally tuned

– Are DB2 buffer pools optimized?

• Are the DB2 buffer pools sized correctly?

– Customers with DB2 V11 to use DB2 synchronous I/O simulation tool.

• Is the customer using fixed large pages for buffer pools?

– Is other middleware taking full use of memory (IMS, MQ, MDM)?

• There are other opportunities to exploit mega-memory

– Benefits from more JVMs, or larger JVM heaps?

• WAS applications, Java applications, Java transactions

– Other opportunities?

http://www.redbooks.ibm.com/abstracts/redp5146.html?Open

Large Memory remarksRethink memory usage on z Systems

• With z13 option to include up to 10 TB in the machine, 2.5 TB per drawer.

– “Mega memory“ affordable option 1H 2015

• Large memory expolitation?

– Assiging the memory to Linux images, as Linux applications often like that.

– Assigning memory to DB2 Bufferpools. Good idea, also consider:

• Adding more memory to local buffer pools means you need to add memory in the

global bufferpools (CF)

• If your customer already has high local bufferpol hit ratios, larger bufferpools offer

less value. Consider revamping BP layout.

– Other middleware smaller benefits from large memory than DB2 (like IMS, CICS, ...)

– Java may use large memory

– For MQ Series, Version 8 provides 64 bit support

• Application programmers should be involved in planning for large memory

exploitaion.

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36

Large Memory Measurement ResultsDB2 and SAP

http://www-03.ibm.com/support/techdocs/atsmastr.nsf/WebIndex/WP102461

z13 Extends Scale, Relieves ConstraintsAdvanced system design optimized for digital business

* Servers exploit a subset of its designed I/O capability

PCI – Processor Capacity Index

CustomerProcessors

PCI for1-way1695

Memory

80-way

64-way

54-way

1.5 TB

512 GB

1202920600

288 GB/sec*

172.8 GB/sec*

15033TB

384 GB/Sec*

101-way

z10 EC

z9 EC

z196

zEC12

z13

10TB

141-way

System I/O Bandwidth832 GB/Sec*

72

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37

Acceleration & OptimizationIntegration versus time-to-market,

• Embedded accelerators• Computation engines for analytics

• Assists for dynamic software optimization

• Enablement for integrated function

• Close collaboration with compiler and other software teams

• PCIe-attached accelerators• FPGAs, Field Programmable Gate Arrays

• Leverage flexibility for special functions

• In-line processing of data entering or leaving system

• Off-load specialized data processing

• Crypto, FICON, Compression, ROCE, Flash,...

• More may come...

• Heterogeneous system optimization• Integrate special-purpose appliances into System z workloads

• Enhanced system scale and price/performance

73

IBM z13 Designed for Analytics - SummaryAccelerate insight and simplify implementation

• IBM DB2 Analytics Accelerator accelerates

queries for faster insight

– New innovative use cases, such as in-

database transformation and advanced

predictive analytics

• Large memory allows new opportunities for

in-memory computing

– per system & per LPAR

• SMT2 for increased zIIP & IFL cores

capacity

• SIMD delivers accelerated analytics

processing for complex queries

– Enable vector processing capabilities to z

Systems

• More

– Optimized math libraries and compilers that

will speed up and simplify application

development

– Faster thread speeds

– z Enterprise Data Compression (zEDC) to

improve the economics of keeping data on

z Systems

74

Which approach is designed for the highest volume of

traffic? Which road is faster?Illustrative numbers only

A3 B3C3

A2 B2C2

Scalar

SINGLE INSTRUCTION, SINGLE DATA

SIMD

SINGLE INSTRUCTION, MULTIPLE DATA

Instruction is performed for every data element

Perform instructions on every element at once

Sum and Store

C1

C2

C3

A1 B1

A2 B2

A3 B3

INSTRUCTION

A1 B1C1

Sum and Store

12/10/2015

38

Analytics as part of the flow of business; Insights on every transaction

• Purchase made

• Resources consumed

• Bill paid

• Claim submitted

• Information updated

• Call center contacted

• What happened?

• How many, how often, where?

• What actions are needed?

• What will happen if?

• What will produce the best outcome?

Transactions & Analytics processed togetherMade possible by using LARGE memory - in addition to SIMD and SMT

75

What’s changing? Data is the new basis of competitive advantage

Data is the world’snewest

resource

Decision-making extends from few to many

As data value grows, current systems won’t

keep pace

76

12/10/2015

39

77

What is Big data?

� Google can give you nearly 2 Billion options� Vendors have even more definitions

Here is how Gartner defines Big DataBig data is high-volume, high-velocity and high-variety information

assets that demand cost-effective, innovative information processing for enhanced insight and decision making.

Big Data Growth is Astounding…The four V’s of Big Data

1 in 2business leaders don’

’’

’t have access to data they

need

83%of CIO’

’’

’s cited BI and analytics as part of their

visionary plan

54%of companies use analytics for competitive advantage

80%of the world’s data

today is unstructured

90% of the world’s data was created in the last two

years

20%is the amount of

available data traditional systems leverages

Source: GigaOM, Software Group, IBM Institute for Business Value“, “Volume, Velocity, Variety, Veracity”

78

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40

Extracting insight from an immense volume, variety and velocity of data, in context, beyond what was previously possible

Big Data includes any of the following Characteristics

Manage the complexity of data in many different structures, ranging from relational, to logs, to raw text

Streaming data and large volume data movement

Scale from Terabytes to Petabytes (1K TBs) to Zettabytes (1B TBs)

Establish trust as the number of data sources grows

Variety:

Velocity:

Volume:

Veracity:

Create IT AgilityManage RiskOutperform

Why Act Now?

Only 1 in 5 organizations allocate more than 50% of IT budget to new projects

Of leaders cite growth as the key source of value

from analytics

Source:1 - IBM IBV Study: Analytics: A blueprint for value, October 2013 2 - IBM Global Study on the Economic Impact of IT Risk, 20133 - IBM Global Data Center Study, 2012

Of respondents were impacted by a cyber security breach

over the past 24 months

46%75% 1in5

12/10/2015

41

Analytics is becoming the Keystone of every organization …

• Analytics derive insight from data

– To help optimize business performance

– To build new innovative services

– To fight against fraud

– To make all customer interaction personal! …

• Analytics become Business Critical!

– Analytics services are tightly integrated with business critical applications and data

• Often hosted in z/OS transaction and batch systems

• Often relying on copies or aggregation of transaction and application data

– Analytics is part of the flow of the business.

– Decision processes have to be improved with new business insight derived from real

time or near real time data.

– Failure of these applications for any length of time can result in lost business or

reputation.

– Analytics solutions need to support a large concurrent user population with high volumes

of requests.

• Analytics are only as good as the underlying data foundation

– Data governance & Security & Performance

81

… but IT remains aligned to the old wayof doing business analytics.

• Some reluctances from the past

– Core business is primary, analytics is secondary!

• On core business side: High volume transactions and batch processing running concurrently,

shared everything DB

• On analytics side: Low volume complex queries and batch reporting, shared nothing DB

– Cost of running analytics on z … without looking at all hidden costs concerning data

movement – latency, data governance, IT complexity

– Impact on operational performance & security

• Key drivers to change IT perception

– Awareness of z position as primary Systems of Records

– Technology availability to build a fully-integrated, end-to-end system that executes

intelligent business processes

– Recognized business value of advanced real time analytics

– Business leaders brainstorm to identify to rethink business process with HTAP influence

• Gartner Research Note G00259033 28 January 2014: Hybrid Transaction/Analytical Processing

Will Foster Opportunities for Dramatic Business Innovation

Insights on every transaction

Analytics as part of the flow

of business

Analytics close to the data

z Systems

Transactions

Analytics

8282

12/10/2015

42

Data Moved

Analytics Approaches for Mainframe Data

DATA

�Transaction Data

�Customer Data

�Account Data

�Payment Data

�Claims Data

System z HostSystem z/OS

Systems of Record

Orchestrate Processing Predictive

Scoring

Business Rules

Move the data to the analytics

Performance of critical transactions may not meet SLAs due to data movement

Customer needs to create security infrastructures across multiple servers

Customer needs to create audit infrastructure across multiple servers to ensure governance

Customer needs to create availability and DR function for multi-server transaction flows and in-transit data

Move the analytics to the data, and within the transaction

Unparalleled, proven performance execution for models and rules, with NO or seamless data movement

Leverage existing best of class security with System z infrastructure

Leverage existing transaction level auditing and logging for governance

Leverage existing, tested HA / DR capabilities already configured with System z

Network

Network

Data Moved

Data Moved

Network

DATA

�Transaction Data

�Customer Data

�Account Data

�Payment Data

�Claims Data

� Orchestrate Processing

� PredictiveScoring

� Business Rules

System z/OS Systems of Record

System z Host

83

System z Mainframe

CP(s)

z/OS

IFL…

z/VM

SMF

Linux for System z

IBM InfoSphere BigInsights

HDFS

MapReduce, Hbase, Hive

IFL IFL

DB2

VSAM

IMS

Logs

System zConnector

For Hadoop

System zConnector

For Hadoop

Simplified data transfer from z/OS to Hadoop

IBM InfoSphere System z Connector for Hadoop

� Easily extract data from mainframe sources

� Purpose built for Hadoop

� Complementary to other IBM tools: IBM MQ FTE, DataStage

� Fast, secure data transfer

� Interactive or batch

� Supports popular Hadoop distributions

� IBM BigInsights

� Cloudera CDH

� Hortonworks HDP

12/10/2015

43

Operational Data Store

Enterprise Data Warehouse

AnalyticsAccelerator

What ishappening?

Whathappened?

What is likelyto happen and what do I do about it?

OLTP Transactions

Operational analytics

Real time data ingestion

High concurrency

Advanced analytics

Standard reports

Complex queries

Historical queries

OLAP

Integrated Transformation/Warehousing

Single DB2 z/OS Data Sharing Group

Big DataAccelerator

Accelerated Reporting

Real-Time Predictive and Prescriptive Analytics

Customer Interaction

Data In

Business Insight Out

z Systems Hybrid Transaction and Analytic ProcessingEverything is online – Analytics in the Right Place

85

Why did it happen?

Hybrid transaction/Analytical processing

The hybrid computing platform on z Systems

Supports transaction processing and analytics workloads

concurrently, efficiently and cost-effectively

Delivers industry leading performance for mixed workloads

The unique heterogeneous scale-out platform in the industry

Superior availability, reliability and security

TransactionProcessing

AnalyticsWorkload

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44

• Business agility through simplified architecture with in-database transformation and multi-step processing

• Real-time, actionable business processes through in-database analytics

• Insight into now to maximize business opportunities through enterprise Incremental Update enhancements

Announcing DB2 Analytics Accelerator Version 5.1

Enabling real-time analytic solutions on a single, integrated system combining transactional data, historical data and predictive analytics

• Extended security through encryption of data at rest and in motion while taking advantage of the renowned built-in security of z Systems

• Enriched systems management capabilities and improved serviceability through IBM Call Home

Strategy

Enable DB2 transition into a truly universal DBMS that provides best characteristics for both OLTP and analytical workloads.

�Complement DB2's industry leading transactional processing capabilities

�Provide specialized access path for data intensive queries

�Enable real and near-real time analytics processing

�Execute transparency to the applications�Operate as an integral part of DB2 and z

Systems�Reusing industry leading PDA's query and

analytics capabilities and take advantage of future enhancements

�Extend query acceleration to new, innovative usage cases, such as:

– in-database transformations– advanced analytical capabilities– multi-temperature and storage saving

solutions

Ultimately allow consolidation and unification of transactional and analytical data stores

DB2 for z/OS

In-databaseTransformation

QueryAccelerator

StorageSaver

OLTP

AdvancedAnalytics

12/10/2015

45

IBM DB2 Analytics Accelerator Do things you could never do before!

• What is it?

– The IBM DB2 Analytics Accelerator is a workload optimized, appliance add-

on to DB2 for z/OS, that enables the integration of analytic insights into

operational processes to drive business critical analytics and exceptional

business value

• What does it do?

– Accelerates complex queries, up to 2000x faster

– Lowers the cost of storing, managing and

processing historical data

– Minimizes latency

– Reduces z Systems capacity requirements

– Improves security and governance

– Reduces operational costs and risk

– Complements existing investments89

IBM DB2 Analytics Accelerator Product Components

OSA-Express4

10 GbE

CLIENT

Data Studio Foundation

DB2 Analytics Accelerator Admin

Plug-in

z Systems

Data Warehouse applicationDB2 for z/OS enabled for IBM

DB2 Analytics Accelerator

IBM DB2 Analytics

Accelerator

NetezzaTechnology (PDA)

Users/Applications

Note: There are several connection options using switches to increase redundancy

Dedicated highly availablenetwork connection

90

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46

Customer Table~ 5 Billion Rows

300 Mixed Workload Queries

Times Faster

Query

Total Rows

Reviewed

Total Rows

Returned Hours Sec(s) Hours Sec(s)Query 1 2,813,571 853,320 2:39 9,540 0.0 5 1,908

Query 2 2,813,571 585,780 2:16 8,220 0.0 5 1,644

Query 3 8,260,214 274 1:16 4,560 0.0 6 760

Query 4 2,813,571 601,197 1:08 4,080 0.0 5 816

Query 5 3,422,765 508 0:57 4,080 0.0 70 58

Query 6 4,290,648 165 0:53 3,180 0.0 6 530

Query 7 361,521 58,236 0:51 3,120 0.0 4 780

Query 8 3,425.29 724 0:44 2,640 0.0 2 1,320Query 9 4,130,107 137 0:42 2,520 0.1 193 13

DB2 Only DB2 with

IDAA

270 of the Mixed Workload Queries

Executes in DB2 returning results in seconds or sub-

seconds

30 of the Mixed Workload Queries took minutes to hours

Successfully accelerated the problem queries without affecting the rest

Customer “A” Example

91

Without

accelerator

With

accelerator

Customer Example –LPAR CPU utilization comparison with and without IDAA

92

12/10/2015

47

Analytic needs are expanding from enterprise data to big data5 Facts to consider to ensure success

1 Organizations are using analytics to outperform their competition

2More users across the organization want access to analytics,

woven into the fabric of the business

3 Analytics is business critical and demands low latency, high qualities of service and performance

4Spreading analytic components across multiple departments can

increase data latency, cost, complexity and governance risk

5Bringing analytic components to where data originates improves

data governance while minimizing data latency, cost and complexity

93

Five Business Critical Analytics Use Cases

Big Data Exploration

Find, visualize, understand all big data to improve business knowledge

Enhanced 360o Viewof the Customer

Achieve a true unified view, incorporating internal and

external sources

Operations Insight

Analyze a variety of machinedata for improved business results.

Data Warehouse Augmentation

Integrate big data and data warehouse capabilities to increase operational efficiency

Security/Intelligence Extension

Risk, compliance and counter fraud

detection. z13 can deliver real time

analytics and scale up to meet future

demand

94

12/10/2015

48

More Users across the Organization want access to Business Critical Analytics

95

The “Big Data” Starting PointWhere are organizations getting the most return on Big Data projects?

0 10 20 30 40 50 60 70 80

Audio

Video

Others

Images

Geospatial data

Free-form text

Social media data

E-mails or documents

Machine or sensor data

Log data

Transactions

Percentage ofrespondents

Gartner research note “Survey Analysis - Big Data Adoption in 2013 Shows Substance Behind the Hype“ Sept 12 2013 Analyst(s): Lisa Kart, Nick Heudecker, Frank Buytendijk

N=465, multiple responses allowed

Most big data initiatives involve transactional or log-file

data

96

12/10/2015

49

Unfortunately for most of our clients, their data lifecycle is too fragmented to gain advantage from that data

• Significant complexity

– Data is move from operational databases

to separated data warehouses/data marts

to support analytics

• Analytics latency

– Transactional data is not readily or easily

available for analytics when created

• Lack of synchronization

– Data is not easily aggregated and users

are not assured they have access to

“fresh” data

• Data duplication

– Multiple copies of the same data is

proliferated throughout the organization

• Excessive costs

– An IT infrastructure that was not designed

nor can support real-time analytics

HistoricalData

PredictiveData

TransactionData

97

Business Critical Analytics Systems with IBM z SystemsAn Hybrid Vision

Bring analytics to the data

� Reduced latency� Reduced complexity � Reduced cost

Deliver business critical analytics� Timely, accurate, secure data� Availability, scalability,

performance� Rapid deployment & expansion

Evolve with the business

� Start with your top analytic requirement(s)

� Grow without changing customer existing IT environment

Business System

OLTP & Batch

Business Critical Analytics

Improved business performance out

Transactions in

Data Transformation

Data Warehousing

Minimize latency. Improve performance. Drive innovation.

• Purchase made

• Resources consumed

• Bill paid

• Claim submitted

• Information updated

• Call center contacted

• What happened?

• How many, how often, where?

• What actions are needed?

• What will happen if?

• What will produce the best outcome?

98

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On average, 70% of the data that feeds data warehousing and

business analytics solutions originates on the System z platform

(financial information, customer lists, personal records,

manufacturing…)

DB2 Analytics Accelerator – Four Usage Scenarios

Understand your workload and data:

Where transaction source data is being analyzed today

Use Case Benefits

If the data is analyzed on the mainframe

Rapid Acceleration of Business Critical Queries

Performance improvements and cost

reduction while retaining System z security and reliability

If the data is offloaded to a distributed data warehouse or data mart

Reduce IT Sprawl for analytics

Simplify and consolidate complex infrastructures, low latency, reliability, security and TCO

If the data is not being analyzed yetDerive business insight from z/OS transaction systems

One integrated, hybrid platform, optimized to run mixed workload.

Simplicity and time to value

If the analysis is based on a lot of historical data

Improve access to historical data and lower storage costs

Performance improvements and cost

reduction

1

2

3

4

99

System z Point of ViewBuilding a foundation to grow with business needs

100

Why z13?� 3X larger memory enables in-memory analytics for faster insight� MASS libraries can see a 2X to 10X improvement making it

advantageous to port x86 analytic workloads� CPLEX on z/OS exploitation of SIMD instructions provides up to 80%

improvement complex modeling� Add real-time scoring to your OLTP workload with minimal impact on

CPU consumption � zIIP exploitation of SMT2� Linux exploitation of SMT2

Why System z� Currency of data� Reduce complexity� Bring analytic function to the data� Improve synchronization� Eliminate data duplication

12/10/2015

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101

Systems of Record

Systems of Record are well integrated and mostly complete

Order Fulfillment

CorporateData

Ware-house

Accounting

Finance

z/OS

Systems of Engagement

Systems of Engagement are disconnected, piece parts

Internet of Things (e.g., RFID)

Mobile Apps

Social Channels

Siloed Dept. Apps

SaaS/Cloud Apps

Linux on System z

Campaign Mgmt App

Other Dept. Apps

System z Bridging Systems of Record with Systems of Engagement

102

z13 Potential Cost ReductionUse Cases: HW/SW “currency” Summary

Workload OptionsPerformance Improvement(estimation)

Potential Cost Reduction

(estimation)

SAP with DB2 on z/OSzHW+zSW currency+ more memory

10%-18%+20%

10%30%

CICS/DB2 banking zHW+zSW currency+ more memory

10%-15%+5%

10%15%

WAS on z/OSe.g. internet banking

zHW+zSW currency+ SMT+ more memory

10%-12%+25%+5%

5%5%

15%

SPSS predictive analytics

zHW+zSW currency+ more memory+ SIMD

10%-18%+5%tbd

10%15%tbd

Traditional Batch processing

zHW+zSW currency+ more memory+ SIMD

10%+5% tbd

10%15%tbd

Linux consolidation on IFLe.g. Private Cloud

zHW+zSW currency+ SMT+ more memory+ GDPS

15%+20%

tbdD/R improvement

15%35%tbdtbd

MobilezHW+zSW currency+ more memory

10%+5%

5%15%

All performance information was determined in a controlled environment. Results may vary.

Sample output from new version ofz13 Benefits Estimator tool

12/10/2015

52

L1 miss

Instrs

1

2

3

4

5

6

7

Time

In-order core execution

L1 miss

Time

z196 Out-of-order core execution

L1 miss

zEC12 Out-of-order core execution

Time

Improvedoverlappingopportunities

Execution

Storage access

Dependency

Out of Order Execution z10, z196 vs zEC12/zBC12

12/10/2015

zBC12/zEC12 Cache Topology

L1 64KI + 96KD8w (D) / 4w (I) Set Associative

L2 Private 1+1MB Inclusive of L1s;new split 2nd level cache design

L3 Shared 48MB Inclusive of L2s12w Set Associative

L4 384/192MB Inclusive24w Set Associative

zBC12/zEC12

4 L4 Caches

384/192MB

Shared eDRAM L4

L1 64KI + 128KD8w (D) / 4w (I) Set Associative

L2 Private 1.5MB Inclusive of L1s12w Set Associative

L3 Shared 24MB Inclusive of L2s12w Set Associative

L4 192MB Inclusive24w Set Associativez114/z196

4 L4 Caches

192MB

Shared eDRAM L4

6 L3s,24 L1 / L2s

L2L1

24MB SharedeDRAM L3

L2L1

L2L1

L2L1

L2L1

24MB SharedeDRAM L3

L2L1

L2L1

L2L1

L2L1

48MB SharedeDRAM L3

L2L1

L2L1

L2L1

L2L1

L2L1

L2L1

48MB SharedeDRAM L3

L2L1

L2L1

L2L1

L2L1

L2L1

6 L3s,36 L1 / L2s

12/10/2015

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Data Compression Acceleration

High Speed Communication Fabric

Proactive Systems Health Analytics

SSD Flash Exploitation

Hybrid Computing Enhancements

Reduce CP consumption, free up storage & speed cross platform data exchange

Optimize server to server networking with reduced latency and lower CPU overhead

Increase availability by detecting unusual system behavior for faster problem determination and resolution

Improve availability at critical times like market open or during abnormal situations; New coupling & Linux exploitation

x86 blade resource optimization; New alert & notification for blade virtual servers; Expanding future roadmap

zEDC Express

10GbE RoCE Express

IBM zAware

IBM Flash Express

zBX Mod 003; zManager Automate; EAM

zEnterprise compilers (COBOL, PL/I, C/C++), Run time monitoring and Transactional Memory provide an optimized application infrastructure for increased software performance

Innovations available on zBC12 and zEC12

w zEC12/zBC12

w zEC12zBC12

w zEC12zBC12

w zEC12zBC12

General Performance Disclaimers

MSURatings

MIPSTables

IBM System z Capacity Planning in a nutshell

Please do not use “single-number tables” for capacity comparisons

12/10/2015

54

General Performance Disclaimers

IBM System z Capacity Planning in a nutshell

Please do not use “single-number tables” for capacity comparisons

Preparing for z13: Why CPU MF Important?Collect SMF 113, Calculate RNI, use zPCR

• z13 provides lower single thread improvements than previous processor

changes, e.g. zEC12 versus z196

• z13 provides more variability in capacity improvement

– Capacity projections and expectations should be reasonably accurate

– Relative Nest Intensity (RNI) is a metric describing access to various cache

levels of the processor architecture

12/10/2015

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Although System z servers are famous for their scalability, CPU consumed/Trans is a function of total load on system as this real life Nordic client case illustrates

Approx. 3-4% growth in CPU/transaction for each 10% growth in CPU busy

Increasing Data and Compute Requirements

110

Mathematical Optimization

Next Best Action

What will happen next?

Business Intelligence-Reporting

Big Sort

Small Sort

Small String Ops

Large String Ops

Big Scan

Traditional IT Analytics

Predictive IT Analytics

Data Intensity

Small Matrix Math

LargeMatrix Math

Co

mp

ute

In

ten

sity

IntegerOps

Floating-Point Ops

String Ops

FP, String, Int

String, Int

Traditional

Algorithms

CompetitiveAlgorithms

Data Warehousing (DW)

Next-GenerationDW

Small Compress

Large Compress

Security/Crypto

Adv Security/Crypto

12/10/2015

56

111

Per

form

an

ce G

ain

HW upgrade

SIMD and other instructions

Large Memory

SW currency

z13 Performance and relevance in marketplace

Transparent Transformational

Cobol 5

HLASMNew SIMD Instructions

2 GB Pages

Java 8

DB2 V11 + Large Memory

Reduce Paging with larger Memory

MQ Series V8 + Large Memory

z13 vs. zEC12 Performance

XMLSS exploiting SIMD

SMT Throughput gain (zIIPs and IFLs)

New Floating Point Unit exploitation

Processor PerformanceSingle engine performance function Drawer layout

zEC12 z/OS 2.1

z13 z/OS 2.1

MIPS MSU MIPS MSU Mips Delta Percent

2827-701 1514 188 2964-701 1695 210 181 12

2827-702 2853 352 2964-702 3196 394 343 12

2827-703 4151 511 2964-703 4644 571 493 12

2827-704 5409 664 2964-704 6041 740 632 12

2827-705 6628 813 2964-705 7392 905 764 12

2827-706 7809 957 2964-706 8700 1062 891 11

2827-707 8954 1092 2964-707 9964 1212 1010 11

2827-708 10063 1224 2964-708 11188 1356 1125 11

2827-709 11137 1350 2964-709 12371 1496 1234 11

2827-710 12179 1473 2964-710 13515 1632 1336 11

2827-711 13188 1593 2964-711 14622 1764 1434 11

2827-712 14166 1709 2964-712 15693 1891 1527 11

2827-713 15126 1822 2964-713 16729 2011 1603 11

2827-714 16069 1934 2964-714 17731 2129 1662 10

2827-715 16994 2043 2964-715 18700 2244 1706 10

2827-716 17904 2149 2964-716 19665 2358 1761 10

2827-717 18797 2254 2964-717 20624 2472 1827 10

2827-718 19673 2359 2964-718 21579 2584 1906 10

2827-719 20534 2462 2964-719 22529 2695 1995 10

2827-720 21380 2564 2964-720 23475 2801 2095 10

2827-721 22222 2661 2964-721 24415 2905 2193 10

2827-722 23061 2755 2964-722 25351 3009 2290 10

2827-723 23896 2848 2964-723 26282 3111 2386 10

2827-724 24728 2940 2964-724 27209 3212 2481 10

2827-725 25557 3032 2964-725 28130 3313 2573 10

2827-726 26382 3122 2964-726 29048 3414 2666 10

2827-727 27205 3212 2964-727 29960 3516 2755 10

2827-728 28023 3301 2964-728 30868 3619 2845 10

2827-729 28839 3389 2964-729 31772 3725 2933 10

2827-730 29651 3480 2964-730 32671 3830 3020 10

Same CHIP

Same NODE, different Chip

Different NODE or different Drawer

12/10/2015

57

To MIPS or not to MIPSthat is z question

• You can not/should not just convert MIPS from zEC12 (or older machines) to z13. Hollistic“

view performance needed to make a prediction on what machine you need.

• Collecting data from existing CEC is „strongly recommended“

– HW Instrumentation Services (HIS) is support built into the z/OS operating system to allow

customers to capture CPU MF information, both counter data and sample data.

– Please use the tool from Patrice Megard to analyse the data.

– Use the HIS data also as „feed“ for zPCR.

– This is also important to have a detailed documentation about the status quo before migrating to a

new machine.

• Native Linux does neither support SMT2 nor SIMD until 3Q 2015. Please keep that in mind

when sizing machines for Linux for system z workloads.

• You need to involve Software People in the performance discussions. Their job is to do an

assessment for (list is incomplete):

– Java 8 improvements due to SIMD.

– Cobol 5.2 Compiler improvements and project evaluation with the client.

– Large memory analysis and exploitation activity definition with the client.

– Check that SMT can be exploited as planned.

z13 Sizing Methodology

1. Collect HIS data from the peak hours of the last month (Software AND Hardware)� Please use the IBM supplied tool to analyse the data. � Use the HIS data also as „feed“ for zPCR.� Collect the SMF70 records from the same time intervall

2. Collect CP3000 data from one full week (incl. WE).� It must be the week where the 4HRA is also included (you get this from the SCRT

report) -> Ask your SW rep to provide it to you.� Once you have the data you need, analyse what workload is running in the 4HRA and

what effect a migration to z13 would have to this particular workload.

3. Use zPCR to get a first proposal of the new HW size. This is dependent on the HW PEAK you have – not the SW peak (the SW peak is a 4hour rolling AVERAGE).� For a first iteration on sizing, leave out SMT benefits.

4. After you analyzed the HIS and zCP3000 data do a workshop with IBM about z13 and its capabilities and dependencies. � Make sure you involve Software IBMers as they need to explain Java, Cobol, PL1 etc.

Improvements of z13.

12/10/2015

58

2001 20052000 2008 2010 20152003

Capacity comparison based on LSPR & IBM zPCR tool* Average SMT benefit on z13

Linux Performance EvolutionTCO improvement through server generations, and SODs

+58%

+10-12%

+33%+61%

+36%

20152012

+20-32%*

+26%

1 IFL on all Systems = 120 PVUs

KVM support for Linux on System z SODGDPS support for Linux on System z SOD (1H 2015)

Source: 2014 IBM Market Intelligence, Percentage of survey respondents

Recommended Linux Workloads for Linux on z Systems

• Data services: Cognos®, SPSS®, DB2®, InfoSphere™, Informix®, Oracle Database, IBI WebFOCUS, …

• Business applications: WebSphere Application Server, WebSphere Process Server, Oracle Application Server, …

• Development and test: WebSphere®/Java applications –Rational® Asset Manager, Build Forge®, ClearCase®, Quality Manager

• Email and collaboration: IBM Domino®, IBM Connections, IBM SameTime, WebSphere Portal, …

• Enterprise Content Management: FileNet® Content Manager, Content Manager, Content Manager On Demand

• Business Process Management: Business Process Manager, WebSphere Business Monitor, FileNet Business Process Manager, WebSphere Operational Decision Management, …

• Infrastructure services: WebSphere MQ, WebSphere Message Broker, WebSphere Enterprise Service Bus, DB2 Connect™, FTP, NFS, DNS, Firewall, Proxy, …

• Cloud management: Infrastructure (IaaS), Platform (PaaS), Software (SaaS), Business Process as a Service – Tivoli®System Automation Manager, Tivoli Provisioning Manager, Integrated Service Management for System z, Maximo® Asset Management, …

• Print (Ubiquitech)

12/10/2015

59

Before

Enterprise

Linux

Servers

2*15 IFL = 30 Oracle RAC EE Licenses

380 cores = 285 Oracle RAC EE Licensesfrom

to

Nordic customer - Oracle consolidation

SOD: zKVM – An Open Hypervisor for zEnterprise

Open

• Open Source based Virtualization

• Open Source with Enterprise scale capabilities

• Accelerate adoption Linux on System z

Cloud

• Standards-based Cloud enablement

• OpenStack

Efficient

• KVM already used by existing users by FIEs and MSPs

Use the tools you know and use today

• Puppet, Chef, Heat, Knife, Moab

• Home Grown Scripts in Perl , Ruby , Java….

KVM –Optimized for System z

System z Host

z CPU, Memory and IO

Support Element

PR/SM™

. . .

z/T

FP

z/O

Sz/

OS Lin

ux

on

Sys

z

z/O

Sz/

OS Lin

ux

on

Sys

z

Lin

ux

on

Sys

z

Lin

ux

on

Sys

z

KVMz/VM

Modern

Open Standard

SimpleLin

ux

on

Sys

z

A new non disruptive hypervisor choicefor the mainframe

z13, zEC12, zBC12 supported

KVM as an additional choiceto run existing and new Linux

centric workload on

zEnterprise in parallel to your

existing z/VM virtualization

environment and z/OS

118

12/10/2015

60

Introducing the z13 Removing constraints on growth through innovation

Greater Workload Performance, Capacity and Scale in the same

energy footprint

40% more total capacity

40% more configurable cores (up to 141 vs 101)

New vector facility (SIMD) for faster mathematical computation

Up to 6 instructions per cycle (double that of zEC12)

3+ x more memory to reduce latency (10 TB vs 3 TB)

New multithreading (SMT2) to expand IFL (Linux) and zIIP

capacity

40% more LPARs to securely host more cloud tenants (85 vs 60)

z13: An innovative, intelligent and integrated system that provides a trusted foundation for sustainable growth today and in the future

Better Economics, Flexibility and Efficiency

Almost 50% increase in granularity to fine tune system

usage and cost

4x data access with zEDC

Standalone zBX support for more flexibility

New resilient IO Infrastructure addresses Skills, Complexity,

Cost and Availability

Price Performance gains for Linux, zIIP, mobile and new SW

workloads

Investment protection with full upgradeability from z196 and

zEC12

Resilient and Secure Growth

Highest level of Security (PR/SM EAL5+)

Next Generation Hardware Cryptography

Best System z RAS with integrated sparing

Much enhanced hypervisor

119

Focused on Enterprise Linux

Extending Linux to wider audiencewith LinuxONE, Linux/KVM (SOD)*

Continuous data availability for z/OSand Linux guests under z/VM with

new GDPS Appliance (SOD)*

Faster diagnosis with IBM zAware –now extended to Linux on z Systems

IBM zAware Support for Linux on System z

120

• Linux on System z system logs can now be analyzed by IBM zAware

• Upgraded analytics engine for better results on z/OS analysis

• Upgraded internal database for improved RAS

• Completely rewritten UI, including heat map views

HiperSockets ™

OSA (for data from other servers)

LPAR

z13 Host 1

IBM zAware Partition

Web Server

Analytics

z/OS

operlog

LOGGER Data

Transport

Linux on System z

HiperSockets ™

OSA (for data from other servers)

LPAR

zServer Host 2

z/OS

operlog

LOGGER Data

Transport

z/OS

operlog

LOGGER Data

Transport

syslog

Results

Models

Data Retrieval

Manage zAware Firmware partition (similar to CF)

File System

IBM zAware GUI

PersistentStorage

Control IBM zAware-specific

knobs

View IBM zAware results

SE

zAware Partition

Shipped as firmware with z13

zVM

12/10/2015

61

z Aware Heat Map – All systems in a groupenhanced zAware interface

z Systems z13 Model Overview

Processors� CP, IFL, zIIP, ICF, optional SAP Specialty engines:‒ IFL and zIIP exploitation of SMT-2‒ 2:1 zIIP to CP ratio on a core basis‒ zAAP eliminated as per SOD

� 3 Sub capacity levels for up to a 30 way� Full support of Capacity on Demand Features� 85 LPARs, increased from 60

Memory� Maximum 10 TB / 2.5 TB per drawer RAIM� LPAR support of the full memory enabled

I/O

� Up to 5 PCIe I/O drawers

‒ FICON Exp8S, OSA-Exp4S, OSA Exp5S, 10Gb RoCE, ‒ FICON 16S

� Up to 2 Legacy I/O Drawers‒ Up to16 FICON 8 features‒ Carry forward only

� Crypto Exp4S, Crypto Exp5S,� zEDC,� zFlash Express

Environmental � Enhanced integrated sparing� Directional setting of rear exhaust airflow

� 1 U rack mountable HMC option

zEC12

z196

Model # PUsMax

Memory

NE1 141 10 TB

NC9 129 10 TB

N96 96 7.5 TB

N63 63 5 TB

N30 30 2.5 TB

Investment protection strategy supported by:� Announced upgrade paths from z196 and zEC12� N-2 Sysplex co-existence (backwards and forwards) � Ensemble co-existence� Node based zBX mod 004 eliminates tight coupling to CEC

122

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62

Prior Servers

z9 EC Z10 EC z196 zEC12 z13

Unscheduled Outages

Scheduled Outages

Planned Outages

Preplanning requirements

Power/Thermal Management

Application Availability

zAware

Flash

IT Analytics

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System z overall RAS Strategy: Never RestDesign objective: Continuous end-to-end availability

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© 2015 IBM Corporation 124

Operating Systems focused on exploiting Hardware innovation

z/OS V2.1 and 2.2 • Improved price performance for zIIP workloads with SMT

• Support new analytics workloads with SIMD and large memory• Digitally sign audit records to reduce risk

• Improved operations agility with entitled z/OSMF

z/VM®

V6.3 • Improved price performance with SMT– support for twice as many processors

• Improved systems management and economics

• Embracing Open Standards and Open Source Interoperability

• Supports more virtual servers than any other platform in a single footprint (up to 8000)

Linux on z Systems

• Multithreading allows for per core software savings

• Starting with z/VM support today

• Linux distributions expected shortly

• Ability to host and manage more workloads efficiently and cost-effectively

• Automatic identification of unusual messages (zAware)

• Integrated continuous availability & disaster recovery solution (GDPS SOD)

• KVM Support - SOD

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Supported Operating Systems

Operation System Supported Levels

z/OS • z/OS V2.1 with PTFs (exploitation)• z/OS V1R13 with PTFs (coexistance)• z/OS V1R12 with PTFs (Toleration. Life cycle extension required)

z/VM • z/VM 6.3 (exploitation)• z/VM 6.2 (toleration)

z/VSE • z/VSE 5.1 and 5.2 will support z13 GA1 in compatibility mode with PTFs• z/VSE 5.2 (with PTFs) will exploit Crypto Express5s

zTPF • z/TPF 1.1

Linux1 • SLES 11 and SLES 12• RHEL 6 and RHEL 7

1The intention is to support n and n-1 Linux distribution releases depending on how their product cycle rolls out. The majority of z13 exploitation will be made available with the major distribution releases following System zNext general availability. IBM intends to make selected exploitation items available on selected distributions and work with its Linux distribution partners to make these available

A Complete Workload-Optimized System Integration of operations and business-critical analytics into one streamlined, end-to-

end data lifecycle

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Transact

Transform

Analyze

Report

Better business responseReduced data movement, reduced complexity, reduced configuration resources

More accurate, more secure, more available

CUSTOMER INTERACTION

DATA IN

BUSINESSINSIGHTS

OUT

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Sources of Information

� IBM DB2 Analytics Accelerator

– Primary Product Page

– Prerequisites and Maintenance

– Guides and manuals

– Knowledge Center

� Customer Testimonials

– https://engage.vevent.com/index.jsp?eid=556&seid=68284&code=brand

� Redbooks and Redpapers

– Reliability and Performance with IBM DB2 Analytics Accelerator Version 4.1

– Optimizing DB2 Queries with IBM DB2 Analytics Accelerator for z/OS

– Hybrid Analytics Solutions using IBM DB2 Analytics Accelerator for z/OS V3.1

– IBM DB2 Analytics Accelerator: High Availability and Disaster Recovery

– SAP Integration with IBM DB2 Analytics Accelerator for z/OS

� All TechDocs available at the following link.

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Eight major trends that will affect the industry in coming years

Business Services

Hardware

Software

Technology Services

SecurityThrough 2016, the financial impact of cybercrime will grow 10% per year, due to the continuing discovery of new vulnerabilities

Growth MarketsBy 2015, IDC expects emerging markets to generate over 33% of all IT spending

Big DataThrough 2015, more than 85% of Fortune 500 organizations will fail to effectively exploit big data for competitive advantage

AnalyticsThrough 2015, more than 90% of business leaders contend information is a strategic asset, yet fewer than 10% will quantify its economic value

Social BusinessBy 2014, 20% of business users will replace email as the primary interpersonal communications with social networking

Smarter PlanetOver $100 billion: Global investment in technology to support smart city development by 2020

Mobile Enterprise66% of CIOs ranked mobility as a top investment priority in 2012

CloudEconomic benefits of cloud will continue to be the #1 driver of adoption through 2016 for most companies.*

Strategic Market Trends

Spring 2012

CustomerSets

*Source: IDC, IDC's CloudTrack 2012 Summer Survey, Part 1: Cost Savings in the Cloud, November 14, 2012

Business Initiatives

% 10% 20% 30% 40% 50% 60%

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Q. In 2015, which of the following business initiatives will be significant in driving IT investments at your organization?

N=242

Increase Productivity

Reduce Costs

Improve Business Processes

Increase Revenue

Introduce new Products & Services

Increase Agility

Improve Customer Retention

Source: IDC IT Experience Survey, January 2015

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Power & Cooling

Mgmt & Administration

New Server Spending

Why OPEX MattersIT Efficiency? IT Effectiveness?

1311995 20002005

2010

2015

OPEX/CAPEX Ratio

0.48 0.771.51

2.83

3.91

$94B$123B

$138B

$206B

$272B

WW Server, P&C and Administration Spending

3x

8x

2009800,000 petabytes

202035 zettabytes

as much Data and ContentOver Coming Decade

44x Business leaders frequently make decisions based on information they don’t trust, or don’t have

1 in3

83%of CIOs cited “Business intelligence and analytics” as part of their visionary plansto enhance competitiveness

Business leaders say they don’’’

’t have access to the information they need to do their jobs

1 in2

of CEOs need to do a better job capturing and understanding information rapidly in order to make swift business decisions

60%Of world’s datais unstructured

80%

Big Data �� Big Valueto enterprise and society

The resulting explosion of information (plus intermediate data) creates a need for a new kind of intelligence

Kilobyte (kB) 1,000 Bytes

Megabyte (MB) 1,000 Kilobytes

Gigabyte (GB) 1,000 Megabytes

Terabyte (TB) 1,000 Gigabytes

Petabyte (PB) 1,000 Terabytes

Exabyte (EB) 1,000 Petabytes

Zettabyte (ZB) 1,000 Exabytes

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Conclusion• There is no shortage of Big Problems that require Big Data

• The Nature of Data in IT is changing.

• Volume – Data doubling every two years

• Variety – Heading to a trillion devices; Unstructured data;

• Velocity – Sometimes all you have is milliseconds to respond

• Veracity – My business, finances, safety, health, life depend on

• Not all Big Data systems are created equal even if the datasheet says they are!

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BigData

BigData

Big Data allows to bring together all kinds of data on one single platform

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135

Unstructured DataDocuments

(Word, Excel, PDF, TXT, etc.)

Social Media DataFacebook, Twitter,

YouTube, Internet, etc.

Multimedia DataFilms, Music, Pictures, etc.

Events / StreamsLive-Cam, Exchange-Trigger,

Microphone, etc.

Operational DataPolicy, Claim, Underwriting,General Ledger, CRM, etc.

BigDataon z

Big Data allows to bring together all kinds of data on one single z13 platformMost of the structured data used today resides there already, and extracting golden nuggets from unstructructured data has never been easier

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Big Data Analytics allows various kindsof Analytics on one single z13 platformReal time, predictive and in-transaction. Bring analytics to the data.

Analytics on DatabasesBigSheets, reports, dashboards, etc.

on unstructured data

Operational AnalyticsReports, dashbords, etc.

on operational data (i.e. legacy systems)

Business AnalyticsReports, dashbords, etc.

on dispositive Data (i.e. Data Warehouse)

Predictive AnalysisWhat-if-Analysis,

Cluster-Analysis, etc.

Visualization/DiscoverySearch, connection and

visualization of data of different datasources and –types with one

application

Realtime AnalyticsDashboards, reports of events and

streamed data

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Top 5 Use Cases for z13

� Risk, compliance and counter fraud detection

� z13 can deliver real time analytics and scale up to meet future demand

� Operational Insight

� z13 can deliver customer insight and next-best-action with a competitive TCO

� Payment

� z13 is the industry-proven platform for realtime payment and transaction

management

� Cloud, API management and Linux

� z13 can deliver the required scaleability for private clouds, API management

platforms and critical Linux-based workload

� Mobile

� z13 can scale up to meet the high-volume transactions demand from mobile

YouTube z13 Nordic Videos

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https://www.youtube.com/watch?v=YuytuCEYIUg

https://www.youtube.com/watch?v=sl8VKXiatjM

https://www.youtube.com/watch?v=Bi4-0guBbOI

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How many times have you used a Mainframe today?

IBM Mainframe: Make the Extraordinary Possible

http://www.youtube.com/watch?v=0tgt4VSrPso

Mainframe 50

IBM Mainframe: Make the Extraordinary Possible

http://www.youtube.com/watch?v=x6MpJL9XBlU

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Server Consolidation on System z

http://www.youtube.com/watch?v=mMsvTR0x334

z13: InstallationsStatus per October 2015

500+ thus far worldwide (15+ Nordic)

– Most installations, migrations and upgrades

went smooth w/o problems

– What we see:

• Most installation are within -1% to +8% of the

zPCR modelled expectation

• Expectation is ~10% better ITR than zEC12

– Plan upgrade carefully

• So far few installations experience some

problems with the migration:

– Less compared to previous significant

processor design changes (for example

z10)

– But enough to warrant planning

considerations

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Matthias R. Bangert, Executive IT-

Specialist

IBM Europe, z Systems

November 14, 2015

Exploiting IBM z13 to the utmost(these results were NOT measured in an “IBM controlled environment” – it is CUSTOMER PRODUCTION data)

• Java 7 to Java 8 migration: - 25% CPU consumption

• DB2 V10 to V11 migration: - 15% CPU consumption

• SIMD usage in Assembler programs: - 30% CPU consumption

• Cobol 4 to 5.2 migration (project started): - 20% CPU consumption (expected)

• MQ Series V7 to V8 migration: up to 50% less batch elapsed time

• SMT exploitation for ZIIPs: + 20% capacity

• Large memory exploitation: VSAM/RLS, DB2 Buffer Pools,

MQ Series V8

The benefits this particular client got out of their z13 clearly shows, that a holistic approach to gain the most out of z13 is not optional – it is mandatory. It also confirms the results the z13 Benefit Estimator

tool is calculating.

IBM LinuxONE In Action…

IBM LinuxOne In Action: Scalable Financial Trading

https://www.youtube.com/watch?v=VWBNoIwGEjo

“I demonstrate the new IBM LinuxONE system for scalable financial trading at the LinuxCon 2015 conference. The demo shows multiple data loads (live data from the S&P 500 and Tweets) streaming via Maria DB, MongoDB, Spark Analytics, Chef, Docker and PostgreSQL.

In this LinuxONE demo, even with drastic upticks in CPU Utilization during the Greek financial crisis, response times are still lightning fast”.

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z13 Planning: What else can be done?• Plan your z13 LPARs carefully

– Why is this important?

• We will see that the LPAR layout matters

– That means LPAR weight, # of logical processors and the resulting numbers of vertical high, medium and low processors (VH, VM, VL)

• A good starting point here is the LPAR Design tool available from the WLM homepage:http://www-03.ibm.com/systems/z/os/zos/features/wlm/WLM_Further_Info_Tools.html#Design

• What does it do?

– It allows you to layout your LPARs

– Examine the VH, VM, VL processors

– Provides guidelines on how to set up the LPARs efficiently

Preparation for z13: CPU MF

• Use the CPU Measurement Facility (Hardware Instrumentation Sampling) to obtain insight into the processor and cache architecture

• Value of CPU Measurement Facility (CPU MF)

– Recommended methodology for successful z Systems processor capacity planning

• Need on “Before” processor to determine LSPR workload

– Validate achieved z Systems processor performance

• Needed on “Before” and “After” processors

– Provide insights for workload pattern, behavior, new features and functions

• Continuously running on all LPARs

�Capturing CPU MF data is an industry “Best Practice”

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Preparation for z13: CPU MF …

• Introduced in z10 and later processors

• Facility that provides hardware instrumentation data for production systems

• Two major components

– Counters – for capacity planning

• Cache and memory hierarchy information

• SCPs supported include z/OS and zVM

– Sampling – for detailed, module level analysis

• z/OS HIS started task

– Gathered on an LPAR basis

– Writes SMF 113 records

• z/VM Monitor Records

– Gathered on an LPAR basis – all guests are aggregated

– Writes new Domain 5 (Processor) Records 13 (CPU MF Counters) records

• Minimal Overhead

A plug for Cheryl Watson’s Tuning Letter:

User experiences...

Frank’s Viewpoint...

zIIP Capacity Planning...

Prep for VSAM/RLS...

z13 Performance...

Software pricing workshops

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Cheryl Watson Tuning Letterarticle on z13 performance and related items – 2015 no. 2

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Large Systems Update (LSU) 2015

• Stockholm 9-10 Nov

• Oslo 11-12 Nov

• Helsinki 16-17 Nov

• Copenhagen 18-19 Nov

• http://www-03.ibm.com/systems/no/lsu2015/index.html

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Other Nordic z Systems events 4Q 2015Free of charge – enroll now

• Stormaskin Forum 2015

– Capgemini - Oslo Tuesday 29. october at 15.00 - 20.30

• 2015 ITSO 3 full day Workshops in Stockholm and CopenhagenIBM z/OS Technical Update, WRZ22G

IBM z/OS Performance and Availability Topics, WRZ23G

IBM z/OS Networking Technologies Update, WRZ28G

– Denmark: Copenhagen 30.11-2.12

– Sweden: Stockholm 2-4.12

http://www.redbooks.ibm.com/redbooks.nsf/home?ReadForm&page=workshops

• LinuxONE ½ day Workshop in Stockholm December 15

– In cooperation with MariaDB

LinuxONE Announcement Overview - Stefan Ekman IBM

IBM’s Commitment to Opensource - Utz Bacher IBM

MariaDB – Anders Karlsson MariaDB

KVM Using KVM to as hypervisor to host 1000’s of servers - Tony Gargya IBM

Docker – Utz Bacher IBM

-- Sweden: Stockholm 15.12153

This year’s ITSO PresentersStraight from the horse’s own mouth

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© 2015 IBM Corporation 155

Nordic Mainframe Entry Education ActivitiesDetailed skills surveys, communities, universities/clients/IBM joint programmes

• 1H 2015• DTU Netbank case (Denmark)

– Guest Education BEC, JN Data, IBM - 14 students enrolled (growing)

• DTU High Availability (Denmark)

• Client trainee programmes at many clients (with IBM sparrring)

• 2H 2015• HIG (Norway). An introduction to the modern Mainframe

– Guest Education DNB, NAV, IBM - 25 students enrolled (growing)

• IBM conduct ”entry MF training also for managers & senior people

• 2H 2015• IBM looking at restoring ”MVS Hissen”

for Nordic and Swedish clients.Previous activity with KTH, Stockholm University and Olsen Education (Cobol).

• 2H 2015 • Student track on Nordic GSE (Gothenburg this year)

• IBM Hursley Lab: zGen community mtg (hosted by Danske Bank)

• ...

GSE Nordic Region Conference 2016

GUIDE SHARE EUROPE

Hotel Reykjavik Nature – Reykjavik, Iceland June 1-5, 2016

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GUIDE SHARE EUROPE

GSE Nordic Region Conference 2016

Hotel Reykjavik Nature – Reykjavik, Iceland from June 1st - 5th 2016

• 6 Tracks with 70 highly technical and educational sessions on

– DB2,CICS,IMS,Mainframe Infrastructure, Application Development and Architecture

• All of the presentations are brought to you by Users and professional speakers

• You will be networking with people with professional background

• We take care of you from flight take off at home until you are safely returned home

• The Conference is organized by Professionals from Bankdata (DK), DNB(NO), EVRY (NO),

Volvo (SE), Tieto (FI), CSC(DK), JN Data (DK) and IBM (UK/DK).

• The Program is available now. Visit WWW.GSE-NORDIC.ORG to view and register.

• Remember that GSE members get’s a 20% discount on IBM Conferences/training. Visit

www.gse.org and register through there to receive the discount.

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