HP TECHNOLOGY@WORK 2011THE INSTANT-ON ENTERPRISE IS HERE

MASSIVE SCALE FOR X86 - PROLIANT DL980 G7 - HP’S 8 SOCKET X86 SERVER

Grant Johnstone

ESSN Presales Sydney

AGENDA

1. The Problem

2. Scale Characteristics

3. Customer Scenarios

4. HP Solution

5. Summary

3

4

30%Business Innovation throttled to

70% Captive in operations and maintenance

IT SPRAWL IS TAKING BUSINESS PERFORMANCE TO THE BREAKING POINT

• Rigid & aging infrastructure

• Application complexity

• Inflexible business processes

• Time to revenue

• Cost of lost time, effort, opportunity

• Unpredictable business cycles

Flex Fabric

Wire-once, dynamic assembly, always predictable

Virtual Resource Pool

Virtualized compute, memory, storage & network

Data Center Smart Grid

Intelligent energy management across systems & facilities

MatrixOperating Environment

Enables shared-service management

THE ARCHITECTURE OF THE CONVERGED INFRASTRUCTURE

DEFINITIONS

SCALABILITY

– System and performance expandability

– Ability to handle increased user and workload requirements without significant disruption

SCALE UP

– Increasing the compute power of an SMP server by adding CPUs and memory to the same server

– Also called vertical scaling

SCALE OUT

– Obtaining additional compute power by adding more servers so that the workload is spread across multiple systems

– Also called horizontal scaling

Some broad guidelines

SCALE UP VS. SCALE OUT HIGH LEVEL

– Easier to manage

– Lower facilities costs

– More efficient scaling

– Greater security and control

– Greater redundancy/availability

– Lower cost of server acquisition (HW)

– “Pay as you grow”

– Modular addition/removal of systems means greater flexibility

– Higher initial capital outlay

– Limits of processor scalability

– Requires redundancy/failover for highest levels of availability

– Management complexity increases as you scale

– Requires multiple high-speed network interconnects

– Applications need to architected for distribution across multiple systems

Scale Up Scale Out

ADVANTAGES

CHALLENGES

– “Pay as you grow”

– Modular addition/removal

CUSTOMER USAGE SCENARIOS

8

Where & When

SQL SERVER CONSOLIDATION

– Large number of similar DBs

– Too many OS & DB versions

– Reduced• Time to deploy OS instances• Time to complete Patch Deployment Cycle

– OS Virtualisation not an option

– Greater utilisation of resources• Just like OS consolidation

9

Where & When

– Decrease licensing (On the Whole)

– Reduce OS footprint

– Decrease patching time

– Single DB version; multiple Instances

– Greater resource availability required

– Greater resource capacity required• Consolidation of $$ to provide

larger pools of HW• Use Oracle to manage

resource allocation

ORACLE CONSOLIDATION

Where & When

– Reduce the OS footprint

– Low latency required between components

– One Large server rather than tiered HW

– A Single DB instance• Reduced need to split the DB

SAP WAREHOUSING

Where & When

TECHNICAL APPLICATIONS

– Real time operations analysis

– Rapid creation of analytic models without impacting established BI environment

– Mash up of data from multiple sources

– Enabled for SAP BusinessObjects BI Tools

– Next generation of BWA for BW (HANA 1.5)

SAP HANA “IN MEMORY PROCESSING”

BUSINESS APPLICATIONS

– Point of sale

– Demand signal repository

– Market measurements analysis

– Traffic analysis

– Liquidity risk management

Where & When

– Oracle are using x86

– Solaris account looking for processing power

– Alternate HW Roadmap for Solaris OS ?

– More cost efficient HW Platform

SOLARIS REPLACEMENT/MIGRATION

CUSTOMERS EMBRACE HP’S SCALE-UP PROLIANT SERVERS

SQL Server DB to support twice as many users (8,000 vs. 4000)

Cancer research - high compute & memory needs (512GB/server)

Fluent-based CAE required higher compute & memory Enables complex simulation

Large Database

High Performance Computing

ERP migration from IBM System z to support 4x order volume (50 to 200 orders/min)

Business Processing

VMware as DB platform cutting downtime by 75% & reducing automatic failover to minutes instead of hours

Enterprise Consolidation

DL980

HP PREMA Architecture to scale up with confidence

INTRODUCING THE HP PROLIANT DL980 G7

Self-healing Resiliency– 200% boost in server availability

– Redundant system fabric to maximize uptime

Balanced Scaling

– World record performance enabled by HP Smart CPU caching

– Up to 8 Intel® Xeon® 7500 series processors

– Up to 8 cores and 24MB L3 cache per processor

– Up to 128 DDR3 DIMM slots; 2.0TB max memory!

– Up to 16 slots, PCI-E 2.0 or PCI-X

– Quad-Port 1GbE embedded NIC upgradable to Dual Port 10GbE

PREM

A A

rchite

cture

Breakthrough Efficiency

– Consolidate up to 197 legacy servers on to a

single system

– HP-only innovations like Thermal Logic, Sea of

Sensors, and Dynamic Power Capping for ROI

that competitors can’t touch

– iLO3 & Insight Control for tomorrow’s

datacenter capabilities today

OPTIMAL SCALING FOR VIRTUALISATION, ERP AND DATABASE DEPLOYMENTS

Bringing HP scale up expertise to 8-socket x86 systems

FASTER RESPONSE TIME

DL 980

Exclusive

HP PREMA ArchitectureSmart CPU Caching

Up to 50%reduction in

inter-processor communication

Eliminates system bottleneck

Minimiseinter-processor communication

Accelerate local memory

access

Dynamic trafficrouting

30% improvement in memory latency

Processor

Processor

Processor

ProcessorPr

oce

ssor

Proce

ssor

Proce

ssor

Proce

ssor

SELF-HEALING RESILIENCY THROUGH INNOVATIONS ON INDUSTRY STANDARDS

CPU Resiliency

System Resiliency

HP PREMA ArchitectureDynamic routing on System Fabric

Enhanced MCA logging

Machine Check Architecture

Advanced memory protection

Corruption PreventionHot Plug RAID

Link Level RetryOS enhanced availability

Advanced reliability with

resilient system fabric

200%boost in server availability

Resi

liency

Leverages

mission critical designs of Superdome 2

DL980 G7 BLOCK DIAGRAM

Boxboro

5 slots + mgmt

Upper

Interface Board

Lower

Interface Board

Link Board

Boxboro

6 PCI-e slots

Boxboro

5 PCI-e LP slots

XNC Board

XNC XNC

XNC Board

XNCXNC

Lower CPU Board

Nehalem-EX

16 DIMMs4 Mill-Brooks

2xRisers

16 DIMMs4 Mill-Brooks

2xRisers

16 DIMMs4 Mill-Brooks

2xRisers

16 DIMMs4 Mill-Brooks

2xRisers

Nehalem-EX

Nehalem-EX

Nehalem-EX

Upper CPU Board

DL580 G7

HP PROLIANT DL980 G7 AWARD-WINNING PERFORMANCE

• #1 non-clustered Windows x86 benchmark result on TPC-H@3000GB : BI leadership

• #1 8-Processor x86 SPECjbb2005 benchmark result : Java business application performance leadership

• #1 single-node SPECjAppServer2004Result: Java application server performance leadership

• #1 8-Processor x86 single-node SPEC CPU2006 benchmark results

• #1 8-processor Windows/SQL Server two-tier SAP® Sales and Distribution (SD) Standard Application Benchmark result with SAP enhancement package 4 for SAP ERP 6.0

SUMMARYImpacts and Benefits

Database Workloads

• Lots of simultaneous users (100s – 1000s)

• Large databases for OLTP and decision support

• IO intensive

• Write intensive

• Compute intensive

• Non partition-able data and application

• Batch workloads

• Consolidation of OLTP, batch and ad hoc reporting

• 47% lower

• 3 Year TCOfor similar performance

• 50% lower initial application configuration cost

• 50% lower database administration costs

Cost Benefitsof Scaling Up

Most data intensive workloads are better suited to a scale-up approach

ADVANTAGES OF SCALING UP

Why ?

WHO’S BUYING 8 PROCESSOR SCALE-UP SERVERS?

– Two and four socket x86 customers who• Need greater capacity and scaling as their applications hit

headroom constraints• Want scalability WITH performance • Value the operational cost savings of a consolidated

environment• Want to consolidate a larger number of virtual machines

– RISC/EPIC users who made a strategic decision to migrate to x86 and want • Comparable performance and scaling• Lower costs and flexibility of industry standard servers• Lower operational costs of a larger, 8 socket server over time

versus 2 and 4 socket solutions

Large query-intensive

workloads

I/O or memory-constrained environments

Consolidation for improved

resource utilization

EXECUTIVE SUMMARY

SCALE UP AND SCALE OUT solutions can both be viable architectural choices, depending on the specific deployment

Influenced by• Application design

• DB, DW, ERP, possibilities..• Management/availability• Cost vs. TCO

Application deployments are frequently a combination of scale up and out: • eg DB tier up,

and app/front end/web pages tier out

NEXT STEPS

Visit: The Cloud System Feature

Engage: See the HP Rep at rear of clinic

Seek more: Request follow up via Eval Form

Re-Live: www.hp.com.au/taw11post