Phase Change Memory An Architecture and Systems Perspective

Phase Change Memory An Architecture and Systems Perspective Benjamin C. Lee Stanford University bcclee@stanford.edu Fall 2010, Assistant Professor @ Duke University Benjamin C. Lee 1

Memory Scaling density, capacity; cost-capability ratio Emerging challenges for prevalent technologies Process integration, devices, and structures, ITRS 2009. Benjamin C. Lee 2

Memory in Transition Charge Memory Write data by capturing charge Q Read data by detecting voltage V Examples: Flash, DRAM Resistive Memory Write data by pulsing current dq/dt Read data by detecting resistance R Examples: PCM, STT-MRAM, memristor Benjamin C. Lee 3

Limits of Charge Memory Difficult charge placement and control Flash: floating gate charge DRAM: capacitor charge, transistor leakage Benjamin C. Lee 4

Towards Resistive Memory PCM Inject current to change material phase Resistance determined by phase STT-MRAM Inject current to change magnet polarity Resistance determined by polarity Memristors Inject current to change atomic structure Resistance determined by atom dist n Benjamin C. Lee 5

Benefits of Resistive Memory Scalable Program cell with scalable current Map resistance to logical state Non-Volatile Alter structure of storage element Incur activation cost to alter properties Competitive Achieve viable latency, power, endurance Scale to improve performance metrics Benjamin C. Lee 6

Technology Benjamin Lee, Engin Ipek, Onur Mutlu, Doug Burger. Architecting phase change memory as a scalable DRAM alternative. ISCA 2009. Benjamin C. Lee 7

Phase Change Memory Store data within phase change material Set phase via current pulse Detect phase via resistance (amorphous/crystalline) Benjamin C. Lee 8

PCM Scalability Program with current pulses, which scale linearly PCM demonstration at 30nm, DRAM roadmap to 40nm [1] Raoux et al., IBM J Res & Dev 2008; [2] Lai, IEDM 2003; [3] Pirovano et al., IEDM 2003. Benjamin C. Lee 9

PCM Non-Volatility Joule Effect Program with current pulses Melt material by heating material (e.g., 650 C) Cool material to desired phase Activation Cost Isolate thermal effects to target cell Retain data for >10 years at 85 C Benjamin C. Lee 10

Technology Parameters Survey prototypes from 2003-2008 (ITRS, IEDM, VLSI, ISSCC) Derive PCM parameters for F=90nm Cell Size 9-12F 2 using BJT 1.5 DRAM, 2-3 NAND Endurance 10 8 writes per cell 10 8 DRAM, 10 3 NAND [1] Lee et al., ISCA 2009; [2] Russo, Workshop Emerging Memory Technologies 2010 Benjamin C. Lee 11

Technology Parameters Survey prototypes from 2003-2008 (ITRS, IEDM, VLSI, ISSCC) Derive PCM parameters for F=90nm Read Latency 50 ns Rd 4 DRAM, 10 3 NAND Write Bandwidth 5-10 MB/s 0.1 DRAM, 1.0 NAND Dynamic Energy 40µA Rd, 150µA Wr 2-43 DRAM, 1.0 NAND [1] Lee et al. ISCA 2009; [2] Russo, Workshop Emerging Memory Technologies 2010 Benjamin C. Lee 12

PCM Comparison vs. Flash Advantage in endurance, performance Comparable in energy Scalable Flash alternative vs. DRAM Disadvantage in endurance, performance, energy Within competitive range of DRAM Scalable DRAM alternative Benjamin C. Lee 13

PCM as DRAM Alternative Deploy PCM on memory bus Begin by co-locating PCM, DRAM Benjamin C. Lee 14

Price of Scalability Replace DRAM with PCM in present architectures 1.6 delay, 2.2 energy, 500-hour lifetime Benjamin C. Lee 15

Architecture and Scalability Benjamin Lee, Engin Ipek, Onur Mutlu, Doug Burger. Architecting phase change memory as a scalable DRAM alternative. ISCA 2009. Benjamin C. Lee 16

Architecture Objectives DRAM-Competitive Reorganize row buffer to mitigate delay, energy Implement partial writes to mitigate wear mechanism Area-Efficient Minimize disruption to density trends Impacts row buffer organization Complexity-Effective Encourage adoption with modest mechanisms Impacts partial writes Benjamin C. Lee 17

Buffer Organization On-Chip Buffers Use DRAM-like buffer and interface Evict modified rows into array Narrow Rows Reduce write energy buffer width Reduce peripheral circuitry, associated area Multiple Rows Reduce eviction frequency Improve locality, write coalescing Benjamin C. Lee 18

Buffer Area Strategy Narrow rows :: fewer expensive S/A s (44T) Multiple rows :: additional inexpensive latches (8T) Benjamin C. Lee 19

Buffering and Locality Read locality: number of array reads Write coalescing: number of array writes per buffer write Benjamin C. Lee 20

Buffer Design Space Derive DRAM, PCM area model Explore space of area-neutral buffer designs Benjamin C. Lee 21

Wear Reduction Wear Mechanism Writes induce phase change at 650 C Contacts degrade from thermal expansion/contraction Current injection is less reliable after 1E+08 writes Partial Writes Reduce writes to PCM array Write only stored lines (64B), words (4B) Add cache line state with 0.2%, 3.1% overhead Benjamin C. Lee 22

Partial Writes Derive PCM lifetime model Quantify eliminated writes during buffer eviction Benjamin C. Lee 23

Scalable Performance 1.2 delay, 1.0 energy, 5.6-year lifetime Scaling improves energy, endurance Benjamin C. Lee 24

Systems and Non-Volatility Jeremy Condit, Edmund Nightingale, Christopher Frost, Engin Ipek, Benjamin Lee, Doug Burger, Derrick Coetzee. Better I/O through byte-addressable, persistent memory. SOSP 2009. Benjamin C. Lee 25

Storage Systems Persistent data in slow, non-volatile memory Buffered data in fast, volatile memory Benjamin C. Lee 26

Storage System Trade-offs Design Objectives Safety :: security against crashes Consistency :: accurate description of file state Performance :: buffering in volatile memory Byte-addressable Persistence (BPRAM) Narrows gap between volatile/non-volatile memory Byte-addressable like DRAM Persistent like disk, Flash Benjamin C. Lee 27

Byte-addressable Persistent File System (BPFS) Safety Use PCM as DRAM alternative Reflect writes to PCM in O(ms), not O(s) Consistency Enforce atomicity, ordering in hardware Support shadow paging, copy-on-write Performance Exploit byte-addressability for small, in-place writes Propose short-circuit shadow paging Benjamin C. Lee 28

Tree-Based File System Benjamin C. Lee 29

File System (FS) Consistency Computer Crash Update to FS may require multiple writes Crash between writes leaves FS invalid State of files not as described by FS Consistency Checker Traverse FS Compares directory structure, data blocks Depends on allocator, free-space manager Benjamin C. Lee 30

Disks & Journaling Writes to journal before to file system Requires twice the writes Benjamin C. Lee 31

Disks & Shadow Paging Copy-on-writes up to file system root Incurs copying overhead Benjamin C. Lee 32

PCM & Short-Circuit Shadow Paging (1) Exploit PCM byte-addressability Write in-place when possible (e.g., 64b updates) Ex: In-place write Benjamin C. Lee 33

PCM & Short-Circuit Shadow Paging (2) Exploit PCM byte-addressability Write in-place when possible (e.g., 64b updates) Ex: In-place append Benjamin C. Lee 34

PCM & Short-Circuit Shadow Paging (3) Exploit PCM byte-addressability Write in-place when possible (e.g., 64b updates) Ex: Partial copy-on-write Benjamin C. Lee 35

Hardware Support for Atomicity Volatile Buffers PCM row buffers are volatile 8T latches BPFS updates 64b pointer to buffer BPFS requires atomic 64b eviction to array Atomicity PCM writes atomically into memory array PCM writes complete in O(100ns) Capacitors guard against power failures Benjamin C. Lee 36

Hardware Support for Ordering Modern Performance Optimizations Controller for write-back caches re-order stores Controller for memory bus re-orders transactions Ordering Epochs define barrier-delimited BPFS writes Copy-on-write updates may be re-ordered Pointer update must follow barrier Benjamin C. Lee 37

BPFS Evaluation NTFS-Disk: baseline NTFS-RAM: current FS on DRAM, proxy for PCM BPFS-RAM: proposed FS on DRAM, proxy for PCM Benjamin C. Lee 38

BPFS Evaluation Safety: no DRAM buffer Consistency: shadow paging Performance: short-circuit shadow paging Benjamin C. Lee 39

For more information... Workshop on Emerging Memory Technologies 2010 Survey of emerging memories www.stanford.edu/ bcclee/emt.html Phase Change Memory Lee et al., Architecting phase change memory as a scalable DRAM alternative. ISCA 2009. Condit et al., Better I/O through byte-addressable, persistent memory. SOSP 2009. Benjamin C. Lee 40

Conclusions Scaling Challenges Fundamental limits in charge memory Transition towards resistive memory Architecture and Scalability PCM position as Flash replacement PCM viable as DRAM alternative Architect buffers, partial writes Systems and Non-Volatility Apply non-volatility for new capabilities Change storage system trade-offs Improve durability, performance Benjamin C. Lee 41

Phase Change Memory An Architecture and Systems Perspective Benjamin C. Lee Stanford University bcclee@stanford.edu Fall 2010, Assistant Professor @ Duke University Benjamin C. Lee 42