How Persistent Memory Will Bring an Entirely New Structure to Large Data Computing

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Memory and Storage-Side ProcessingHow persistent memory will bring an entirely new structure to large data computingSteve Pawlowski, VP of Advanced Memory Systems

Persistent Memory Today

© 2016 Micron Technology, Inc. |

Closing the Memory / Storage Latency Gap

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Nanoseconds Microseconds Milliseconds

Storage I/O Memory Persistent Memory

Memory Control(Load/Store)

I/O Control(Read/Write)

Hard Disk Drive(Spinning Media)

SATA/SAS SSD(NAND)

NVME SSD(NAND)

QuantX™ Technology

SSD(3D XPoint™

memory)

DIMM(3D XPoint™

memory)ASP/Bit

Latency(not to scale)

NVDIMM-N(DRAM/NAND)

RDIMM/LRDIMM(DRAM)

Cost Optimized PM

Performance OptimizedPM

May 1, 2023

© 2016 Micron Technology, Inc. |4 | Micron Confidential

Impact of NVDIMM-N on Application Performance

| May 1, 2023

• Data committed to persistent media written to NAND through the I/O stack

• Data committed to persistent media written to DRAM on NVDIMM-N through the I/O stack

• Latency improvement due to writing to DRAM (35ns) versus NAND (85,000ns)

• Data committed to persistent media written to DRAM on NVDIMM-N through Load/Store Bus

• Latency improvement due to circumventing overhead associated with I/O stack

35ns

35ns

85us

85us

35ns

DRAM + NAND-Based NVMe SSD

DRAM + NVDIMM-N Block Mode

DRAM + NVDIMM-N Direct Mode

35ns

35ns

25us

25us

35ns

35ns

35ns

35ns

35ns

35ns NV Direct

NV Block

NVMe

LATENCY


HPE and Microsoft Enterprise Performance

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Hardware Broadwell 2-way Platform DB data on 6x 400GB SSD

8GB NVDIMM Cache + SSDsMirrored Pool of

SSDs

SQL Server Transaction Log

970k Tx/min372us write latency

1.08M Tx/min181us write latency

+11% Performance

Benefit(Block Mode, Read Centric)

Exchange Server

+63% Performance

Benefit(Block Mode, Write Centric)

780k Tx/min 1.3M Tx/min

Future Vision


Fast Persistent Writes Metadata StorageWrite Back Cache

Scale-out Storage

Big Data Analytics

In-Memory Databases

Relational Databases

Persistent Memory will … Persist

Higher capacities and storage-class memories will open even broader applications

BECOMING THE MAINSTAY OF MEMORY SUBSYSTEMS

© 2016 Micron Technology, Inc. |May 1, 2023 | Micron Confidential

The Critical Element of Future Memory Systems

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NVDIMM-NHybrid Memory Cube

This opens interesting new possibilities for managing data

Integrated on-board controller


Moving Data to the Processor is Costly

What if we could avoid this 1000x chasm?

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One floating-point calculation

17 picojoules

Moving data from DRAM to CPU

17,000 picojoules


Why Hasn’t it Been Done Before?

DRAM transistors are not ideal for logic processing– In-memory processing must be very simple– Processing must be intrinsically data-centric– Complementary to CPU / Custom Processors

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Memory Technology

Low leakage transistorsLow power

Processor Technology

High speedHigh power


What Can Be Done with STM?

Data-centric problems• Data sort• Databases• Machine learning (90% of the problem is feeding the MACs)

Computationally lightweight problems Solutions that can be smoothly transitioned:• Replace a library call (qsort ->msort)• Replace a subsystem (MySQL)

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An Illustration

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Challenges to Overcome

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Driving Easier Market Adoption

– Simplify the power source

– Minimize SW and programming ecosystem impact

– Appropriate energy/performance tradeoffs

– Latency optimization

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HPE Smart Storage NVDIMM Integrated Backup Power


Implications of NVDIMM-P

High capacities enable truly large in-memory computing Latencies introduce opportunity for tiered memory systems Industry ecosystem should begin preparing

today

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