BIBIM: A Prototype Multi-Partition Aware Heterogeneous New Memory

Size: px
Start display at page:

Download "BIBIM: A Prototype Multi-Partition Aware Heterogeneous New Memory"

Transcription

1 HotStorage 18 BIBIM: A Prototype Multi-Partition Aware Heterogeneous New Memory Gyuyoung Park 1, Miryeong Kwon 1, Pratyush Mahapatra 2, Michael Swift 2, and Myoungsoo Jung 1 Yonsei University Computer Architecture and MEmory Systems Lab

2 1. Demands for Hybrid Memory 2. Preview of BIBIM 3. Design Considerations of BIBIM 4. Example of BIBIM Operation 5. Evaluation

3 Relative capacity Increasing Demands for Bigger Memory More cores require more memory capacity However, there is memory capacity gap Core count doubling ~ every 2 years Memory capacity doubling ~ every 3 years Core Need a bigger and larger memory!! 1 Memory (DRAM) Source: Lim et al, ISCA Moreover, there are many data-intensive applications Ex) Memory caching (MEMCACHED, Redis), In-memory database (DynamoDB, HANA) Year

4 Comparison of Technology Scaling Cost Reduction Rate DRAM NAND New Memory (PRAM, STT-MRAM, ReRAM) Suitable for next memory device DRAM NAND Source: SK Hynix New Memory Scaling limitation Managed DRAM 3D NAND Time & Technology node

5 Write time (s) Comparison of Programming Latency Unfortunately, takes a long time to program FeRAM MRAM SRAM Courtesy: Motoyuki Ooishi DRAM NOR Flash memory PRAM Can achieve high capacity NAND Flash memory NV-RAM w/o erase-beforewrite NV-RAM w/ erase-beforewrite Volatile RAM Memory capacity (bit)

6 Why does PRAM Show Long Write Latency? How Significant? Top electrode Ge 2 Sb 2 Te 5 (GST) PRAM exploits the unique behavior of chalcogenide glass (GST). By switching status of GST, it can store data Heater Bottom electrode PRAM cell

7 GST Temperature Programming Method of PRAM GST status is changed by heating the material Amorphous (Data 0 ) T melt (~600 ) Crystallin (Data 1 ) T crys (~300 ) T reset T read T set Long write latency T room Time Moreover, compared with DRAM, PRAM has asymmetric latency

8 General Assumptions of PRAM Latency HPCA 18 ISCA 09 HPCA 13 Many previous works assume PRAM s write latency as similar to or slightly worse than DRAM (1.5x) WRITE latency (ns) DRAM x Assumed PRAM

9 PRAM Latency Measurement 3x nm PRAM WRITE latency (ns) DRAM x Real PRAM Our performance measurement on real 3x nm PRAM exhibits expensive write latency than DRAM (190x)

10 Then, How Can PRAM s Long Write Latency Be Mitigated? Let s borrow the concept of Bibim Bibim means Mix in Korean Mix various ingredients for better taste

11 Hybrid Memory Can Help Us Put fast DRAM and slow PRAM together DRAM PRAM NOTE) I m just used as a write-only inclusive cache of slow PRAM

12 BTW, How Can Hybrid Memory Be Used in Real System? We design new memory controller, BIBIM, for non-volatile hybrid memory BIBIM

13 1. Demands for Hybrid Memory 2. Preview of BIBIM 3. Design Considerations of BIBIM 4. Example of BIBIM Operation 5. Evaluation

14 Demo (Track and Field) DRAM PRAM Performance comparison (memory access with synthetic, readwrite inter-mixed trace) BIBIM

15 Demo Slow Version DRAM PRAM Host sent 1M memory requests 1 Memory Still services PRAM servicing incoming memory requests requests BIBIM 2

16 1. Demands for Hybrid Memory 2. Preview of BIBIM 3. Design Considerations of BIBIM 4. Example of BIBIM Operation 5. Evaluation

17 PHY What Are The Considerations To Design Hybrid Memory (DRAM+PRAM) Controller? Memory controller DRAM PRAM To get insights of controller design, let s understand the details of DRAM and PRAM

18 Row decoder Bank 0 Bank 1 Bank N DRAM s Multi-bank Architecture Multiple banks to serve multiple memory requests in parallel Single row buffer within a bank Row buffer Column decoder

19 Does PRAM have the Same Internal Architecture with DRAM? Challenge1: PRAM s write latency is long PRAM employs multiple row buffers Challenge2: PRAM s asymmetric latency incurs lots of bank conflicts PRAM uses multi-partition architecture

20 Decoder Bank PRAM s Multi-partition Architecture Multiple partitions within the bank for partition-level parallelism Multiple row buffers to mitigate long write latency RAB RDB Cell Array Partition 0 Partition 1 Partition 15 Sense Amp.

21 Can A Conventional DRAM Controller Be Aware of Multi- Partition? (Inside of A Bank) (Revisited) Conventional DRAM scheduler just utilizes bank-level parallelism. Cannot see inside of bank! Partition-level parallelism should be supported

22 Sense amp. Blocked! How Memory Requests Can Be Scheduled By Exploiting Multi-Partition Architecture? Limitation of PRAM: In PRAM design, WRITE request blocks whole PRAM bank. Decoder Request (Write) Partition 0 Partition 1 Partition 15

23 How Memory Requests Can Be Scheduled By Exploiting Multi-Partition Architecture? Key insight: Although WRITE cannot be serviced, READs can be serviced if partition number is different

24 Sense amp. Non-Blocking Read Service (NBRS) Solution: Add a register to store partition number of WRITE and compare it with partition number of incoming READ request BIBIM controller WRITE partition number Decoder Partition 0 Partition 1 Partition 2 Partition 15 Same partition READ can t be serviced!

25 PHY BIBIM Design1: Scheduling Support Module for PRAMaware New Scheduling Scheme Request Scheduling? Module? DRAM?? PRAM

26 Now Requests Are Scheduled. Then, How Then Can It Serve to Hybrid Memory? Firstly, as is generally known, LPDDR2 is JEDEC standard low-power memory interface (used for DRAM)

27 Row decoder Bank 0 Bank 1 Bank N DRAM s Timing (LPDDR2 by JEDEC) 1) Activation: activate target row & write that data to row buffer 2) Read/Write: accessing row buffer with column address 3) Precharge: charge half-voltage of bit-line Column decoder

28 Does PRAM have the Same Memory Interface (LPDDR2) with DRAM? (Revisited) PRAM has a different architecture with DRAM such as Multiple row buffers and More larger capacity Different interface is required

29 Upper row address PRAM s Timing PRAM requires different timing model from DRAM NVM memory space is much larger than a DRAM 3-Phase addressing (LPDDR2-NVM by JEDEC) ❶ Pre-active ❷ Activate ❸ READ RAB Lower row address Upper Lower RDB Column address PRAM array Row Address Buffer (RAB) is selected by the memory controller Row Data Buffer (RDB) is also selected by the memory controller Data out

30 PHY BIBIM Design2: Heterogeneity Support Module for both LPDDR2 & LPDDR2-NVM Request Scheduling? Module Heterogeneity Support? Module Our own new physical layer (400MHz) is implemented?? DRAM PRAM

31 Don t Forget DRAM is For Cache. Then, How Caching Can Be Supported? Solution: Keep which data exist in DRAM (caching info) in lookup table. Moreover, like conventional cache, controller should have algorithms such as DRAM dataline update, eviction, and find empty dataline.

32 0000 tag index offset Hardware Support for Lookup Table Lookup table do not include data value, includes address information count valid tag DRAM hit/miss way2 way3 way4 = = = = # way Mux Only 512KB BRAM is used for lookup table With multiple comparators, 4 ways can be parallelized

33 PHY BIBIM Design3: Caching Support Module for Use DRAM As Inclusive Cache of PRAM Request Scheduling? Module Heterogeneity Support? Module DRAM Caching Support Module?? PRAM

34 BTW, How Non-Volatility of PRAM Can Be Maintained Although DRAM Is Integrated? (Hybrid) Challenge of hybrid memory: Data in DRAM will disappear when there is a power failure Power failure Data CPU Memory controller Data DRAM PRAM

35 FLUSH Operation Solution: Provide Flush operation which moves DRAM data to PRAM. Memory controller generates PRAM write request corresponding to the target DRAM row. NOTE) PRAM write will be stored in command queue which exists in memory controller. And DRAM dataline is invalidated. CPU Flush Generate PRAM write request Memory controller WRITE Data DRAM PRAM

36 Okay, Data Delivery Is Guaranteed. Is It Good Enough? Challenge of flush: User believes data has the latest value. But, the memory controller can reorder the order of memory request Process1 Process2 1) Data=1 CPU 2) Data=2 reorder Memory controller DRAM PRAM

37 FENCE Operation Solution: Provide Fence operation to enforce data delivery order of memory requests. The memory controller can simply add fence flag to check fenced or not 1) Data=1 CPU 2) Data=2 Fence Fence flag Memory controller DRAM PRAM

38 PHY BIBIM Design4: Persistent Support Module to Guarantee Data Delivery & Delivery Order Request Scheduling? Module Heterogeneity Support? Module DRAM Caching Support Module Persistent Support Module?? PRAM

39 1. Demands for Hybrid Memory 2. Preview of BIBIM 3. Design Considerations of BIBIM 4. Example of BIBIM Operation 5. Evaluation

40 PHY We Designed Four Modules in BIBIM. BTW, How They Work Together? Request Scheduling Module Caching Support Module Heterogeneity Support Module Persistent Support Module DRAM PRAM

41 PHY Specific Example: Evict DRAM Dataline Host WRITE Request Scheduling? Module Caching Support Module Heterogeneity Support? Module Persistent Support Module?? DRAM Addr DRAM PRAM [Host] Sends WRITE request to the hybrid memory [CACHING] Check DRAM dataline hit or not [CACHING] (If it is a miss) Find victim DRAM dataline based on LRU policy, and return victim DRAM address to the SCHEDULING module

42 PHY Specific Example: Evict DRAM Dataline Request Heterogeneity DRAM Scheduling? Addr DRAM Support? Cmd DRAM DRAMData Module Module Caching Support Module Persistent Support Module?? PRAM [SCHEUDLING] Sends DRAM address to the HETEROGENEITY module [HETEROGENITY] Generate DRAM commands [DRAM] Return DRAM dataline to the SCHEDULING module

43 PHY Specific Example: Evict DRAM Dataline Request Scheduling? Module DRAM Data Heterogeneity Support? Module DRAM Caching Support Module Persistent Support Module?? PRAM [SCHEUDLING] Ask fence flag is set or not to the PERSISTENT module [PERSISTENT] Return as fence flag is set [SCHEUDLING] Do not serve PRAM WRITE (Eviction of victim DRAM dataline)

44 1. Demands for Hybrid Memory 2. Preview of BIBIM 3. Design Considerations of BIBIM 4. Example of BIBIM Operation 5. Evaluation

45 Persistent Memory Workloads WHISPER: Wisconsin-HP Labs Suite for Persistence

46 Wisconsin-HP Labs Suite for Persistence (WHISPER) Benchmark echo ycsb tpcc ctree hashmap vacation Brief description Scalable, multi-version key-value store H-store like DB. Undo logs for consistency H-store like DB. Undo logs for consistency Micro-benchmarks for simulations Micro-benchmarks for simulations Online travel reservation system Write-intensive (82% of total requests)

47 Latency Comparisons (DRAM-only vs. PRAM-only vs. Hybrid memory w/bibim)

48 Average Request Latency CPU CPU CPU Avg. request latency(us) echo DRAM PRAM BIBIM (15%) us 9.8 us 0.87 us tpcc ycsb ctreehashmap Lower is better! DRAM > BIBIM > PRAM vacation

49 Average Request Latency Avg. request latency(us) echo DRAM PRAM BIBIM (15%) tpcc ycsb ctree hashmapvacation BIBIM reduces the long latency than PRAM by 87% BIBIM only degrades the perf. than DRAM by 44% Best performance benefits: vacation; many cache hits (high write fraction) Small performance benefits: tpcc, ycsb; persistent operation (flush) generates many PRAM writes

50 Non-blocking Read Service (NBRS) Analysis Tested on PRAM-only (PRAM)

51 RAW Latency of Non-NBRS PRAM Read-after-write (RAW) Sense amp. Blocked! RAW Req1: partition 0 (cache eviction /persistent operation) Req2: partition 1 Req3: partition 15 Decoder Partition 0 Partition 1 Partition 15 Non-NBRS PRAM bank Avg. read-afterwrite latency (us) echo tpccycsb Non-NBRS NBRS ctree hashmap vacation RAW latency of Non-NBRS: 19.8 us on average. ( PRAM write latency)

52 RAW Latency of NBRS PRAM Sense amp. NBRS! RAW RAR Read-after-write (RAW) Req1: partition 0 (cache eviction /persistent operation) Req2: partition 1 Req3: partition 15 Decoder Partition 0 Partition 1 Partition 15 NBRS PRAM bank Avg. read-afterwrite latency (us) Non-NBRS NBRS Many partition conflicts Many write echo tpccycsb ctree hashmap vacation RAW latency of NBRS: 52% reduced on average.

53 Demo Normal Version sec DRAM PRAM 1 Performance 1.27 sec comparison (memory access with synthetic, 3 readwrite inter-mixed trace) BIBIM sec

54 Conclusion BIBIM can achieve both high capacity and short latency Avg. latency (us) PRAM-Only 0.87 BIBIM Our main contributions: 1) Multi-partition aware scheduler (NBRS) 2) New physical layer (PHY) 3) Persistent support for hybrid memory

An Analysis of Persistent Memory Use with WHISPER

An Analysis of Persistent Memory Use with WHISPER An Analysis of Persistent Memory Use with WHISPER Sanketh Nalli, Swapnil Haria, Michael M. Swift, Mark D. Hill, Haris Volos*, Kimberly Keeton* University of Wisconsin- Madison & *Hewlett- Packard Labs

More information

An Analysis of Persistent Memory Use with WHISPER

An Analysis of Persistent Memory Use with WHISPER An Analysis of Persistent Memory Use with WHISPER Sanketh Nalli, Swapnil Haria, Michael M. Swift, Mark D. Hill, Haris Volos*, Kimberly Keeton* University of Wisconsin- Madison & *Hewlett- Packard Labs

More information

Emerging NVM Memory Technologies

Emerging NVM Memory Technologies Emerging NVM Memory Technologies Yuan Xie Associate Professor The Pennsylvania State University Department of Computer Science & Engineering www.cse.psu.edu/~yuanxie yuanxie@cse.psu.edu Position Statement

More information

ROSS: A Design of Read-Oriented STT-MRAM Storage for Energy-Efficient Non-Uniform Cache Architecture

ROSS: A Design of Read-Oriented STT-MRAM Storage for Energy-Efficient Non-Uniform Cache Architecture ROSS: A Design of Read-Oriented STT-MRAM Storage for Energy-Efficient Non-Uniform Cache Architecture Jie Zhang, Miryeong Kwon, Changyoung Park, Myoungsoo Jung, Songkuk Kim Computer Architecture and Memory

More information

Evaluating STT-RAM as an Energy-Efficient Main Memory Alternative

Evaluating STT-RAM as an Energy-Efficient Main Memory Alternative Evaluating STT-RAM as an Energy-Efficient Main Memory Alternative Emre Kültürsay *, Mahmut Kandemir *, Anand Sivasubramaniam *, and Onur Mutlu * Pennsylvania State University Carnegie Mellon University

More information

Big and Fast. Anti-Caching in OLTP Systems. Justin DeBrabant

Big and Fast. Anti-Caching in OLTP Systems. Justin DeBrabant Big and Fast Anti-Caching in OLTP Systems Justin DeBrabant Online Transaction Processing transaction-oriented small footprint write-intensive 2 A bit of history 3 OLTP Through the Years relational model

More information

Lecture 8: Virtual Memory. Today: DRAM innovations, virtual memory (Sections )

Lecture 8: Virtual Memory. Today: DRAM innovations, virtual memory (Sections ) Lecture 8: Virtual Memory Today: DRAM innovations, virtual memory (Sections 5.3-5.4) 1 DRAM Technology Trends Improvements in technology (smaller devices) DRAM capacities double every two years, but latency

More information

Developing a Prototyping Board for Emerging Memory

Developing a Prototyping Board for Emerging Memory Developing a Prototyping Board for Emerging Memory 2013. 10. 25 Sungjoo Yoo Embedded System Architecture Lab. POSTECH Introduction scaling problem [ITRS, 2012] Year 2012 2013 2014 2015 2016 2017 2018 2019

More information

Spring 2016 :: CSE 502 Computer Architecture. Caches. Nima Honarmand

Spring 2016 :: CSE 502 Computer Architecture. Caches. Nima Honarmand Caches Nima Honarmand Motivation 10000 Performance 1000 100 10 Processor Memory 1 1985 1990 1995 2000 2005 2010 Want memory to appear: As fast as CPU As large as required by all of the running applications

More information

Phase Change Memory An Architecture and Systems Perspective

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,

More information

Emerging NVM Enabled Storage Architecture:

Emerging NVM Enabled Storage Architecture: Emerging NVM Enabled Storage Architecture: From Evolution to Revolution. Yiran Chen Electrical and Computer Engineering University of Pittsburgh Sponsors: NSF, DARPA, AFRL, and HP Labs 1 Outline Introduction

More information

Will Phase Change Memory (PCM) Replace DRAM or NAND Flash?

Will Phase Change Memory (PCM) Replace DRAM or NAND Flash? Will Phase Change Memory (PCM) Replace DRAM or NAND Flash? Dr. Mostafa Abdulla High-Speed Engineering Sr. Manager, Micron Marc Greenberg Product Marketing Director, Cadence August 19, 2010 Flash Memory

More information

A Memory Management Scheme for Hybrid Memory Architecture in Mission Critical Computers

A Memory Management Scheme for Hybrid Memory Architecture in Mission Critical Computers A Memory Management Scheme for Hybrid Memory Architecture in Mission Critical Computers Soohyun Yang and Yeonseung Ryu Department of Computer Engineering, Myongji University Yongin, Gyeonggi-do, Korea

More information

CSE502: Computer Architecture CSE 502: Computer Architecture

CSE502: Computer Architecture CSE 502: Computer Architecture CSE 502: Computer Architecture Memory Hierarchy & Caches Motivation 10000 Performance 1000 100 10 Processor Memory 1 1985 1990 1995 2000 2005 2010 Want memory to appear: As fast as CPU As large as required

More information

Views of Memory. Real machines have limited amounts of memory. Programmer doesn t want to be bothered. 640KB? A few GB? (This laptop = 2GB)

Views of Memory. Real machines have limited amounts of memory. Programmer doesn t want to be bothered. 640KB? A few GB? (This laptop = 2GB) CS6290 Memory Views of Memory Real machines have limited amounts of memory 640KB? A few GB? (This laptop = 2GB) Programmer doesn t want to be bothered Do you think, oh, this computer only has 128MB so

More information

Scalable High Performance Main Memory System Using PCM Technology

Scalable High Performance Main Memory System Using PCM Technology Scalable High Performance Main Memory System Using PCM Technology Moinuddin K. Qureshi Viji Srinivasan and Jude Rivers IBM T. J. Watson Research Center, Yorktown Heights, NY International Symposium on

More information

Hybrid Memory Platform

Hybrid Memory Platform Hybrid Memory Platform Kenneth Wright, Sr. Driector Rambus / Emerging Solutions Division Join the Conversation #OpenPOWERSummit 1 Outline The problem / The opportunity Project goals Roadmap - Sub-projects/Tracks

More information

Novel Nonvolatile Memory Hierarchies to Realize "Normally-Off Mobile Processors" ASP-DAC 2014

Novel Nonvolatile Memory Hierarchies to Realize Normally-Off Mobile Processors ASP-DAC 2014 Novel Nonvolatile Memory Hierarchies to Realize "Normally-Off Mobile Processors" ASP-DAC 2014 Shinobu Fujita, Kumiko Nomura, Hiroki Noguchi, Susumu Takeda, Keiko Abe Toshiba Corporation, R&D Center Advanced

More information

Portland State University ECE 587/687. Caches and Memory-Level Parallelism

Portland State University ECE 587/687. Caches and Memory-Level Parallelism Portland State University ECE 587/687 Caches and Memory-Level Parallelism Revisiting Processor Performance Program Execution Time = (CPU clock cycles + Memory stall cycles) x clock cycle time For each

More information

CSE502: Computer Architecture CSE 502: Computer Architecture

CSE502: Computer Architecture CSE 502: Computer Architecture CSE 502: Computer Architecture Memory / DRAM SRAM = Static RAM SRAM vs. DRAM As long as power is present, data is retained DRAM = Dynamic RAM If you don t do anything, you lose the data SRAM: 6T per bit

More information

registers data 1 registers MEMORY ADDRESS on-chip cache off-chip cache main memory: real address space part of virtual addr. sp.

registers data 1 registers MEMORY ADDRESS on-chip cache off-chip cache main memory: real address space part of virtual addr. sp. 13 1 CMPE110 Computer Architecture, Winter 2009 Andrea Di Blas 110 Winter 2009 CMPE Cache Direct-mapped cache Reads and writes Cache associativity Cache and performance Textbook Edition: 7.1 to 7.3 Third

More information

Reducing DRAM Latency at Low Cost by Exploiting Heterogeneity. Donghyuk Lee Carnegie Mellon University

Reducing DRAM Latency at Low Cost by Exploiting Heterogeneity. Donghyuk Lee Carnegie Mellon University Reducing DRAM Latency at Low Cost by Exploiting Heterogeneity Donghyuk Lee Carnegie Mellon University Problem: High DRAM Latency processor stalls: waiting for data main memory high latency Major bottleneck

More information

Page 1. Multilevel Memories (Improving performance using a little cash )

Page 1. Multilevel Memories (Improving performance using a little cash ) Page 1 Multilevel Memories (Improving performance using a little cash ) 1 Page 2 CPU-Memory Bottleneck CPU Memory Performance of high-speed computers is usually limited by memory bandwidth & latency Latency

More information

Memory technology and optimizations ( 2.3) Main Memory

Memory technology and optimizations ( 2.3) Main Memory Memory technology and optimizations ( 2.3) 47 Main Memory Performance of Main Memory: Latency: affects Cache Miss Penalty» Access Time: time between request and word arrival» Cycle Time: minimum time between

More information

Exploring System Challenges of Ultra-Low Latency Solid State Drives

Exploring System Challenges of Ultra-Low Latency Solid State Drives Exploring System Challenges of Ultra-Low Latency Solid State Drives Sungjoon Koh Changrim Lee, Miryeong Kwon, and Myoungsoo Jung Computer Architecture and Memory systems Lab Executive Summary Motivation.

More information

CS698Y: Modern Memory Systems Lecture-16 (DRAM Timing Constraints) Biswabandan Panda

CS698Y: Modern Memory Systems Lecture-16 (DRAM Timing Constraints) Biswabandan Panda CS698Y: Modern Memory Systems Lecture-16 (DRAM Timing Constraints) Biswabandan Panda biswap@cse.iitk.ac.in https://www.cse.iitk.ac.in/users/biswap/cs698y.html Row decoder Accessing a Row Access Address

More information

Phase Change Memory An Architecture and Systems Perspective

Phase Change Memory An Architecture and Systems Perspective Phase Change Memory An Architecture and Systems Perspective Benjamin Lee Electrical Engineering Stanford University Stanford EE382 2 December 2009 Benjamin Lee 1 :: PCM :: 2 Dec 09 Memory Scaling density,

More information

Course Administration

Course Administration Spring 207 EE 363: Computer Organization Chapter 5: Large and Fast: Exploiting Memory Hierarchy - Avinash Kodi Department of Electrical Engineering & Computer Science Ohio University, Athens, Ohio 4570

More information

Onyx: A Prototype Phase-Change Memory Storage Array

Onyx: A Prototype Phase-Change Memory Storage Array Onyx: A Prototype Phase-Change Memory Storage Array Ameen Akel * Adrian Caulfield, Todor Mollov, Rajesh Gupta, Steven Swanson Non-Volatile Systems Laboratory, Department of Computer Science and Engineering

More information

ELEC 5200/6200 Computer Architecture and Design Spring 2017 Lecture 7: Memory Organization Part II

ELEC 5200/6200 Computer Architecture and Design Spring 2017 Lecture 7: Memory Organization Part II ELEC 5200/6200 Computer Architecture and Design Spring 2017 Lecture 7: Organization Part II Ujjwal Guin, Assistant Professor Department of Electrical and Computer Engineering Auburn University, Auburn,

More information

CMU Introduction to Computer Architecture, Spring 2014 HW 5: Virtual Memory, Caching and Main Memory

CMU Introduction to Computer Architecture, Spring 2014 HW 5: Virtual Memory, Caching and Main Memory CMU 18-447 Introduction to Computer Architecture, Spring 2014 HW 5: Virtual Memory, Caching and Main Memory Instructor: Prof. Onur Mutlu TAs: Rachata Ausavarungnirun, Varun Kohli, Xiao Bo Zhao, Paraj Tyle

More information

Adapting Controllers for STT-MRAM

Adapting Controllers for STT-MRAM Adapting Controllers for STT-MRAM Joe O Hare Everspin Technologies, Inc. CTRL 301-1 Flash Controller Design Options Room: GAMR2 8:30 10:50AM August 9, 2018 Flash Memory Summit 2018 Santa Clara, CA 1 Adapting

More information

A Hybrid Solid-State Storage Architecture for the Performance, Energy Consumption, and Lifetime Improvement

A Hybrid Solid-State Storage Architecture for the Performance, Energy Consumption, and Lifetime Improvement A Hybrid Solid-State Storage Architecture for the Performance, Energy Consumption, and Lifetime Improvement Guangyu Sun, Yongsoo Joo, Yibo Chen Dimin Niu, Yuan Xie Pennsylvania State University {gsun,

More information

Memory Hierarchy: Caches, Virtual Memory

Memory Hierarchy: Caches, Virtual Memory Memory Hierarchy: Caches, Virtual Memory Readings: 5.1-5.4, 5.8 Big memories are slow Computer Fast memories are small Processor Memory Devices Control Input Datapath Output Need to get fast, big memories

More information

15-740/ Computer Architecture Lecture 19: Main Memory. Prof. Onur Mutlu Carnegie Mellon University

15-740/ Computer Architecture Lecture 19: Main Memory. Prof. Onur Mutlu Carnegie Mellon University 15-740/18-740 Computer Architecture Lecture 19: Main Memory Prof. Onur Mutlu Carnegie Mellon University Last Time Multi-core issues in caching OS-based cache partitioning (using page coloring) Handling

More information

Lecture 17 Introduction to Memory Hierarchies" Why it s important " Fundamental lesson(s)" Suggested reading:" (HP Chapter

Lecture 17 Introduction to Memory Hierarchies Why it s important  Fundamental lesson(s) Suggested reading: (HP Chapter Processor components" Multicore processors and programming" Processor comparison" vs." Lecture 17 Introduction to Memory Hierarchies" CSE 30321" Suggested reading:" (HP Chapter 5.1-5.2)" Writing more "

More information

Page 1. Memory Hierarchies (Part 2)

Page 1. Memory Hierarchies (Part 2) Memory Hierarchies (Part ) Outline of Lectures on Memory Systems Memory Hierarchies Cache Memory 3 Virtual Memory 4 The future Increasing distance from the processor in access time Review: The Memory Hierarchy

More information

Mohsen Imani. University of California San Diego. System Energy Efficiency Lab seelab.ucsd.edu

Mohsen Imani. University of California San Diego. System Energy Efficiency Lab seelab.ucsd.edu Mohsen Imani University of California San Diego Winter 2016 Technology Trend for IoT http://www.flashmemorysummit.com/english/collaterals/proceedi ngs/2014/20140807_304c_hill.pdf 2 Motivation IoT significantly

More information

Caches. Han Wang CS 3410, Spring 2012 Computer Science Cornell University. See P&H 5.1, 5.2 (except writes)

Caches. Han Wang CS 3410, Spring 2012 Computer Science Cornell University. See P&H 5.1, 5.2 (except writes) Caches Han Wang CS 3410, Spring 2012 Computer Science Cornell University See P&H 5.1, 5.2 (except writes) This week: Announcements PA2 Work-in-progress submission Next six weeks: Two labs and two projects

More information

CSE502: Computer Architecture CSE 502: Computer Architecture

CSE502: Computer Architecture CSE 502: Computer Architecture CSE 502: Computer Architecture Memory / DRAM SRAM = Static RAM SRAM vs. DRAM As long as power is present, data is retained DRAM = Dynamic RAM If you don t do anything, you lose the data SRAM: 6T per bit

More information

Buffer Caching Algorithms for Storage Class RAMs

Buffer Caching Algorithms for Storage Class RAMs Issue 1, Volume 3, 29 Buffer Caching Algorithms for Storage Class RAMs Junseok Park, Hyunkyoung Choi, Hyokyung Bahn, and Kern Koh Abstract Due to recent advances in semiconductor technologies, storage

More information

EECS151/251A Spring 2018 Digital Design and Integrated Circuits. Instructors: John Wawrzynek and Nick Weaver. Lecture 19: Caches EE141

EECS151/251A Spring 2018 Digital Design and Integrated Circuits. Instructors: John Wawrzynek and Nick Weaver. Lecture 19: Caches EE141 EECS151/251A Spring 2018 Digital Design and Integrated Circuits Instructors: John Wawrzynek and Nick Weaver Lecture 19: Caches Cache Introduction 40% of this ARM CPU is devoted to SRAM cache. But the role

More information

CS24: INTRODUCTION TO COMPUTING SYSTEMS. Spring 2014 Lecture 14

CS24: INTRODUCTION TO COMPUTING SYSTEMS. Spring 2014 Lecture 14 CS24: INTRODUCTION TO COMPUTING SYSTEMS Spring 2014 Lecture 14 LAST TIME! Examined several memory technologies: SRAM volatile memory cells built from transistors! Fast to use, larger memory cells (6+ transistors

More information

1/19/2009. Data Locality. Exploiting Locality: Caches

1/19/2009. Data Locality. Exploiting Locality: Caches Spring 2009 Prof. Hyesoon Kim Thanks to Prof. Loh & Prof. Prvulovic Data Locality Temporal: if data item needed now, it is likely to be needed again in near future Spatial: if data item needed now, nearby

More information

EE 4683/5683: COMPUTER ARCHITECTURE

EE 4683/5683: COMPUTER ARCHITECTURE EE 4683/5683: COMPUTER ARCHITECTURE Lecture 6A: Cache Design Avinash Kodi, kodi@ohioedu Agenda 2 Review: Memory Hierarchy Review: Cache Organization Direct-mapped Set- Associative Fully-Associative 1 Major

More information

Caches. Samira Khan March 23, 2017

Caches. Samira Khan March 23, 2017 Caches Samira Khan March 23, 2017 Agenda Review from last lecture Data flow model Memory hierarchy More Caches The Dataflow Model (of a Computer) Von Neumann model: An instruction is fetched and executed

More information

EFFICIENTLY ENABLING CONVENTIONAL BLOCK SIZES FOR VERY LARGE DIE- STACKED DRAM CACHES

EFFICIENTLY ENABLING CONVENTIONAL BLOCK SIZES FOR VERY LARGE DIE- STACKED DRAM CACHES EFFICIENTLY ENABLING CONVENTIONAL BLOCK SIZES FOR VERY LARGE DIE- STACKED DRAM CACHES MICRO 2011 @ Porte Alegre, Brazil Gabriel H. Loh [1] and Mark D. Hill [2][1] December 2011 [1] AMD Research [2] University

More information

FlashShare: Punching Through Server Storage Stack from Kernel to Firmware for Ultra-Low Latency SSDs

FlashShare: Punching Through Server Storage Stack from Kernel to Firmware for Ultra-Low Latency SSDs FlashShare: Punching Through Server Storage Stack from Kernel to Firmware for Ultra-Low Latency SSDs Jie Zhang, Miryeong Kwon, Donghyun Gouk, Sungjoon Koh, Changlim Lee, Mohammad Alian, Myoungjun Chun,

More information

Introduction to cache memories

Introduction to cache memories Course on: Advanced Computer Architectures Introduction to cache memories Prof. Cristina Silvano Politecnico di Milano email: cristina.silvano@polimi.it 1 Summary Summary Main goal Spatial and temporal

More information

Spring 2018 :: CSE 502. Cache Design Basics. Nima Honarmand

Spring 2018 :: CSE 502. Cache Design Basics. Nima Honarmand Cache Design Basics Nima Honarmand Storage Hierarchy Make common case fast: Common: temporal & spatial locality Fast: smaller, more expensive memory Bigger Transfers Registers More Bandwidth Controlled

More information

COSC 6385 Computer Architecture - Memory Hierarchies (I)

COSC 6385 Computer Architecture - Memory Hierarchies (I) COSC 6385 Computer Architecture - Memory Hierarchies (I) Edgar Gabriel Spring 2018 Some slides are based on a lecture by David Culler, University of California, Berkley http//www.eecs.berkeley.edu/~culler/courses/cs252-s05

More information

Multilevel Memories. Joel Emer Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology

Multilevel Memories. Joel Emer Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology 1 Multilevel Memories Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Based on the material prepared by Krste Asanovic and Arvind CPU-Memory Bottleneck 6.823

More information

Lecture: Memory Technology Innovations

Lecture: Memory Technology Innovations Lecture: Memory Technology Innovations Topics: memory schedulers, refresh, state-of-the-art and upcoming changes: buffer chips, 3D stacking, non-volatile cells, photonics Multiprocessor intro 1 Row Buffers

More information

CSE 431 Computer Architecture Fall Chapter 5A: Exploiting the Memory Hierarchy, Part 1

CSE 431 Computer Architecture Fall Chapter 5A: Exploiting the Memory Hierarchy, Part 1 CSE 431 Computer Architecture Fall 2008 Chapter 5A: Exploiting the Memory Hierarchy, Part 1 Mary Jane Irwin ( www.cse.psu.edu/~mji ) [Adapted from Computer Organization and Design, 4 th Edition, Patterson

More information

Caches (Writing) P & H Chapter 5.2 3, 5.5. Hakim Weatherspoon CS 3410, Spring 2013 Computer Science Cornell University

Caches (Writing) P & H Chapter 5.2 3, 5.5. Hakim Weatherspoon CS 3410, Spring 2013 Computer Science Cornell University Caches (Writing) P & H Chapter 5.2 3, 5.5 Hakim Weatherspoon CS 34, Spring 23 Computer Science Cornell University Welcome back from Spring Break! Welcome back from Spring Break! Big Picture: Memory Code

More information

Overcoming System Memory Challenges with Persistent Memory and NVDIMM-P

Overcoming System Memory Challenges with Persistent Memory and NVDIMM-P Overcoming System Memory Challenges with Persistent Memory and NVDIMM-P JEDEC Server Forum 2017 Bill Gervasi, Discobolus Designs Copyright 2017 Jonathan Hinkle, Lenovo Datacenter Research and Technology

More information

Chapter 5A. Large and Fast: Exploiting Memory Hierarchy

Chapter 5A. Large and Fast: Exploiting Memory Hierarchy Chapter 5A Large and Fast: Exploiting Memory Hierarchy Memory Technology Static RAM (SRAM) Fast, expensive Dynamic RAM (DRAM) In between Magnetic disk Slow, inexpensive Ideal memory Access time of SRAM

More information

Lecture-14 (Memory Hierarchy) CS422-Spring

Lecture-14 (Memory Hierarchy) CS422-Spring Lecture-14 (Memory Hierarchy) CS422-Spring 2018 Biswa@CSE-IITK The Ideal World Instruction Supply Pipeline (Instruction execution) Data Supply - Zero-cycle latency - Infinite capacity - Zero cost - Perfect

More information

Memory. Lecture 22 CS301

Memory. Lecture 22 CS301 Memory Lecture 22 CS301 Administrative Daily Review of today s lecture w Due tomorrow (11/13) at 8am HW #8 due today at 5pm Program #2 due Friday, 11/16 at 11:59pm Test #2 Wednesday Pipelined Machine Fetch

More information

15-740/ Computer Architecture Lecture 20: Main Memory II. Prof. Onur Mutlu Carnegie Mellon University

15-740/ Computer Architecture Lecture 20: Main Memory II. Prof. Onur Mutlu Carnegie Mellon University 15-740/18-740 Computer Architecture Lecture 20: Main Memory II Prof. Onur Mutlu Carnegie Mellon University Today SRAM vs. DRAM Interleaving/Banking DRAM Microarchitecture Memory controller Memory buses

More information

CS 31: Intro to Systems Caching. Kevin Webb Swarthmore College March 24, 2015

CS 31: Intro to Systems Caching. Kevin Webb Swarthmore College March 24, 2015 CS 3: Intro to Systems Caching Kevin Webb Swarthmore College March 24, 205 Reading Quiz Abstraction Goal Reality: There is no one type of memory to rule them all! Abstraction: hide the complex/undesirable

More information

Cache Architectures Design of Digital Circuits 217 Srdjan Capkun Onur Mutlu http://www.syssec.ethz.ch/education/digitaltechnik_17 Adapted from Digital Design and Computer Architecture, David Money Harris

More information

CSF Improving Cache Performance. [Adapted from Computer Organization and Design, Patterson & Hennessy, 2005]

CSF Improving Cache Performance. [Adapted from Computer Organization and Design, Patterson & Hennessy, 2005] CSF Improving Cache Performance [Adapted from Computer Organization and Design, Patterson & Hennessy, 2005] Review: The Memory Hierarchy Take advantage of the principle of locality to present the user

More information

A Comprehensive Analytical Performance Model of DRAM Caches

A Comprehensive Analytical Performance Model of DRAM Caches A Comprehensive Analytical Performance Model of DRAM Caches Authors: Nagendra Gulur *, Mahesh Mehendale *, and R Govindarajan + Presented by: Sreepathi Pai * Texas Instruments, + Indian Institute of Science

More information

Slide Set 9. for ENCM 369 Winter 2018 Section 01. Steve Norman, PhD, PEng

Slide Set 9. for ENCM 369 Winter 2018 Section 01. Steve Norman, PhD, PEng Slide Set 9 for ENCM 369 Winter 2018 Section 01 Steve Norman, PhD, PEng Electrical & Computer Engineering Schulich School of Engineering University of Calgary March 2018 ENCM 369 Winter 2018 Section 01

More information

ARCHITECTURAL TECHNIQUES TO ENHANCE DRAM SCALING. Thesis Defense Yoongu Kim

ARCHITECTURAL TECHNIQUES TO ENHANCE DRAM SCALING. Thesis Defense Yoongu Kim ARCHITECTURAL TECHNIQUES TO ENHANCE DRAM SCALING Thesis Defense Yoongu Kim CPU+CACHE MAIN MEMORY STORAGE 2 Complex Problems Large Datasets High Throughput 3 DRAM Module DRAM Chip 1 0 DRAM Cell (Capacitor)

More information

Question?! Processor comparison!

Question?! Processor comparison! 1! 2! Suggested Readings!! Readings!! H&P: Chapter 5.1-5.2!! (Over the next 2 lectures)! Lecture 18" Introduction to Memory Hierarchies! 3! Processor components! Multicore processors and programming! Question?!

More information

Migration Based Page Caching Algorithm for a Hybrid Main Memory of DRAM and PRAM

Migration Based Page Caching Algorithm for a Hybrid Main Memory of DRAM and PRAM Migration Based Page Caching Algorithm for a Hybrid Main Memory of DRAM and PRAM Hyunchul Seok Daejeon, Korea hcseok@core.kaist.ac.kr Youngwoo Park Daejeon, Korea ywpark@core.kaist.ac.kr Kyu Ho Park Deajeon,

More information

COMP 3221: Microprocessors and Embedded Systems

COMP 3221: Microprocessors and Embedded Systems COMP 3: Microprocessors and Embedded Systems Lectures 7: Cache Memory - III http://www.cse.unsw.edu.au/~cs3 Lecturer: Hui Wu Session, 5 Outline Fully Associative Cache N-Way Associative Cache Block Replacement

More information

Memory Hierarchy. Maurizio Palesi. Maurizio Palesi 1

Memory Hierarchy. Maurizio Palesi. Maurizio Palesi 1 Memory Hierarchy Maurizio Palesi Maurizio Palesi 1 References John L. Hennessy and David A. Patterson, Computer Architecture a Quantitative Approach, second edition, Morgan Kaufmann Chapter 5 Maurizio

More information

18-447: Computer Architecture Lecture 25: Main Memory. Prof. Onur Mutlu Carnegie Mellon University Spring 2013, 4/3/2013

18-447: Computer Architecture Lecture 25: Main Memory. Prof. Onur Mutlu Carnegie Mellon University Spring 2013, 4/3/2013 18-447: Computer Architecture Lecture 25: Main Memory Prof. Onur Mutlu Carnegie Mellon University Spring 2013, 4/3/2013 Reminder: Homework 5 (Today) Due April 3 (Wednesday!) Topics: Vector processing,

More information

TDT Coarse-Grained Multithreading. Review on ILP. Multi-threaded execution. Contents. Fine-Grained Multithreading

TDT Coarse-Grained Multithreading. Review on ILP. Multi-threaded execution. Contents. Fine-Grained Multithreading Review on ILP TDT 4260 Chap 5 TLP & Hierarchy What is ILP? Let the compiler find the ILP Advantages? Disadvantages? Let the HW find the ILP Advantages? Disadvantages? Contents Multi-threading Chap 3.5

More information

Chapter 2: Memory Hierarchy Design Part 2

Chapter 2: Memory Hierarchy Design Part 2 Chapter 2: Memory Hierarchy Design Part 2 Introduction (Section 2.1, Appendix B) Caches Review of basics (Section 2.1, Appendix B) Advanced methods (Section 2.3) Main Memory Virtual Memory Fundamental

More information

CS 152 Computer Architecture and Engineering. Lecture 7 - Memory Hierarchy-II

CS 152 Computer Architecture and Engineering. Lecture 7 - Memory Hierarchy-II CS 152 Computer Architecture and Engineering Lecture 7 - Memory Hierarchy-II Krste Asanovic Electrical Engineering and Computer Sciences University of California at Berkeley http://www.eecs.berkeley.edu/~krste

More information

Chapter 5. Large and Fast: Exploiting Memory Hierarchy

Chapter 5. Large and Fast: Exploiting Memory Hierarchy Chapter 5 Large and Fast: Exploiting Memory Hierarchy Principle of Locality Programs access a small proportion of their address space at any time Temporal locality Items accessed recently are likely to

More information

SOLVING THE DRAM SCALING CHALLENGE: RETHINKING THE INTERFACE BETWEEN CIRCUITS, ARCHITECTURE, AND SYSTEMS

SOLVING THE DRAM SCALING CHALLENGE: RETHINKING THE INTERFACE BETWEEN CIRCUITS, ARCHITECTURE, AND SYSTEMS SOLVING THE DRAM SCALING CHALLENGE: RETHINKING THE INTERFACE BETWEEN CIRCUITS, ARCHITECTURE, AND SYSTEMS Samira Khan MEMORY IN TODAY S SYSTEM Processor DRAM Memory Storage DRAM is critical for performance

More information

The Memory Hierarchy & Cache Review of Memory Hierarchy & Cache Basics (from 350):

The Memory Hierarchy & Cache Review of Memory Hierarchy & Cache Basics (from 350): The Memory Hierarchy & Cache Review of Memory Hierarchy & Cache Basics (from 350): Motivation for The Memory Hierarchy: { CPU/Memory Performance Gap The Principle Of Locality Cache $$$$$ Cache Basics:

More information

EEM 486: Computer Architecture. Lecture 9. Memory

EEM 486: Computer Architecture. Lecture 9. Memory EEM 486: Computer Architecture Lecture 9 Memory The Big Picture Designing a Multiple Clock Cycle Datapath Processor Control Memory Input Datapath Output The following slides belong to Prof. Onur Mutlu

More information

Why memory hierarchy? Memory hierarchy. Memory hierarchy goals. CS2410: Computer Architecture. L1 cache design. Sangyeun Cho

Why memory hierarchy? Memory hierarchy. Memory hierarchy goals. CS2410: Computer Architecture. L1 cache design. Sangyeun Cho Why memory hierarchy? L1 cache design Sangyeun Cho Computer Science Department Memory hierarchy Memory hierarchy goals Smaller Faster More expensive per byte CPU Regs L1 cache L2 cache SRAM SRAM To provide

More information

The Memory Hierarchy 1

The Memory Hierarchy 1 The Memory Hierarchy 1 What is a cache? 2 What problem do caches solve? 3 Memory CPU Abstraction: Big array of bytes Memory memory 4 Performance vs 1980 Processor vs Memory Performance Memory is very slow

More information

CS311 Lecture 21: SRAM/DRAM/FLASH

CS311 Lecture 21: SRAM/DRAM/FLASH S 14 L21-1 2014 CS311 Lecture 21: SRAM/DRAM/FLASH DARM part based on ISCA 2002 tutorial DRAM: Architectures, Interfaces, and Systems by Bruce Jacob and David Wang Jangwoo Kim (POSTECH) Thomas Wenisch (University

More information

ECE 2300 Digital Logic & Computer Organization. Caches

ECE 2300 Digital Logic & Computer Organization. Caches ECE 23 Digital Logic & Computer Organization Spring 217 s Lecture 2: 1 Announcements HW7 will be posted tonight Lab sessions resume next week Lecture 2: 2 Course Content Binary numbers and logic gates

More information

LECTURE 11. Memory Hierarchy

LECTURE 11. Memory Hierarchy LECTURE 11 Memory Hierarchy MEMORY HIERARCHY When it comes to memory, there are two universally desirable properties: Large Size: ideally, we want to never have to worry about running out of memory. Speed

More information

CPS104 Computer Organization and Programming Lecture 16: Virtual Memory. Robert Wagner

CPS104 Computer Organization and Programming Lecture 16: Virtual Memory. Robert Wagner CPS104 Computer Organization and Programming Lecture 16: Virtual Memory Robert Wagner cps 104 VM.1 RW Fall 2000 Outline of Today s Lecture Virtual Memory. Paged virtual memory. Virtual to Physical translation:

More information

Tri-Hybrid SSD with storage class memory (SCM) and MLC/TLC NAND Flash Memories

Tri-Hybrid SSD with storage class memory (SCM) and MLC/TLC NAND Flash Memories Tri-Hybrid SSD with storage class memory (SCM) and MLC/TLC NAND Flash Memories Chihiro Matsui, Tomoaki Yamada, Yusuke Sugiyama, Yusuke Yamaga, and Ken Takeuchi Chuo University, Japan Santa Clara, CA 1

More information

CENG 3420 Computer Organization and Design. Lecture 08: Cache Review. Bei Yu

CENG 3420 Computer Organization and Design. Lecture 08: Cache Review. Bei Yu CENG 3420 Computer Organization and Design Lecture 08: Cache Review Bei Yu CEG3420 L08.1 Spring 2016 A Typical Memory Hierarchy q Take advantage of the principle of locality to present the user with as

More information

Caches 3/23/17. Agenda. The Dataflow Model (of a Computer)

Caches 3/23/17. Agenda. The Dataflow Model (of a Computer) Agenda Caches Samira Khan March 23, 2017 Review from last lecture Data flow model Memory hierarchy More Caches The Dataflow Model (of a Computer) Von Neumann model: An instruction is fetched and executed

More information

NBM: An Efficient Cache Replacement Algorithm for Nonvolatile Buffer Caches

NBM: An Efficient Cache Replacement Algorithm for Nonvolatile Buffer Caches : An Efficient Cache Replacement Algorithm for Nonvolatile Buffer Caches JUNSEOK PARK and KERN KOH Seoul National University 56-1 Shillim-dong, Kwanak-gu, Seoul, 151-742 REPUBLIC OF KOREA HYUNKYOUNG CHOI

More information

Cache Memory COE 403. Computer Architecture Prof. Muhamed Mudawar. Computer Engineering Department King Fahd University of Petroleum and Minerals

Cache Memory COE 403. Computer Architecture Prof. Muhamed Mudawar. Computer Engineering Department King Fahd University of Petroleum and Minerals Cache Memory COE 403 Computer Architecture Prof. Muhamed Mudawar Computer Engineering Department King Fahd University of Petroleum and Minerals Presentation Outline The Need for Cache Memory The Basics

More information

Memory Hierarchy. 2/18/2016 CS 152 Sec6on 5 Colin Schmidt

Memory Hierarchy. 2/18/2016 CS 152 Sec6on 5 Colin Schmidt Memory Hierarchy 2/18/2016 CS 152 Sec6on 5 Colin Schmidt Agenda Review Memory Hierarchy Lab 2 Ques6ons Return Quiz 1 Latencies Comparison Numbers L1 Cache 0.5 ns L2 Cache 7 ns 14x L1 cache Main Memory

More information

Chapter 6 Memory 11/3/2015. Chapter 6 Objectives. 6.2 Types of Memory. 6.1 Introduction

Chapter 6 Memory 11/3/2015. Chapter 6 Objectives. 6.2 Types of Memory. 6.1 Introduction Chapter 6 Objectives Chapter 6 Memory Master the concepts of hierarchical memory organization. Understand how each level of memory contributes to system performance, and how the performance is measured.

More information

Spring 2018 :: CSE 502. Main Memory & DRAM. Nima Honarmand

Spring 2018 :: CSE 502. Main Memory & DRAM. Nima Honarmand Main Memory & DRAM Nima Honarmand Main Memory Big Picture 1) Last-level cache sends its memory requests to a Memory Controller Over a system bus of other types of interconnect 2) Memory controller translates

More information

Staged Memory Scheduling

Staged Memory Scheduling Staged Memory Scheduling Rachata Ausavarungnirun, Kevin Chang, Lavanya Subramanian, Gabriel H. Loh*, Onur Mutlu Carnegie Mellon University, *AMD Research June 12 th 2012 Executive Summary Observation:

More information

Evalua&ng STT- RAM as an Energy- Efficient Main Memory Alterna&ve

Evalua&ng STT- RAM as an Energy- Efficient Main Memory Alterna&ve Evalua&ng STT- RAM as an Energy- Efficient Main Memory Alterna&ve Emre Kültürsay *, Mahmut Kandemir *, Anand Sivasubramaniam *, and Onur Mutlu * Pennsylvania State University Carnegie Mellon University

More information

Chapter 5. Large and Fast: Exploiting Memory Hierarchy

Chapter 5. Large and Fast: Exploiting Memory Hierarchy Chapter 5 Large and Fast: Exploiting Memory Hierarchy Processor-Memory Performance Gap 10000 µproc 55%/year (2X/1.5yr) Performance 1000 100 10 1 1980 1983 1986 1989 Moore s Law Processor-Memory Performance

More information

Understanding Reduced-Voltage Operation in Modern DRAM Devices

Understanding Reduced-Voltage Operation in Modern DRAM Devices Understanding Reduced-Voltage Operation in Modern DRAM Devices Experimental Characterization, Analysis, and Mechanisms Kevin Chang A. Giray Yaglikci, Saugata Ghose,Aditya Agrawal *, Niladrish Chatterjee

More information

registers data 1 registers MEMORY ADDRESS on-chip cache off-chip cache main memory: real address space part of virtual addr. sp.

registers data 1 registers MEMORY ADDRESS on-chip cache off-chip cache main memory: real address space part of virtual addr. sp. Cache associativity Cache and performance 12 1 CMPE110 Spring 2005 A. Di Blas 110 Spring 2005 CMPE Cache Direct-mapped cache Reads and writes Textbook Edition: 7.1 to 7.3 Second Third Edition: 7.1 to 7.3

More information

Caches Part 1. Instructor: Sören Schwertfeger. School of Information Science and Technology SIST

Caches Part 1. Instructor: Sören Schwertfeger.   School of Information Science and Technology SIST CS 110 Computer Architecture Caches Part 1 Instructor: Sören Schwertfeger http://shtech.org/courses/ca/ School of Information Science and Technology SIST ShanghaiTech University Slides based on UC Berkley's

More information

Cache/Memory Optimization. - Krishna Parthaje

Cache/Memory Optimization. - Krishna Parthaje Cache/Memory Optimization - Krishna Parthaje Hybrid Cache Architecture Replacing SRAM Cache with Future Memory Technology Suji Lee, Jongpil Jung, and Chong-Min Kyung Department of Electrical Engineering,KAIST

More information

Balancing DRAM Locality and Parallelism in Shared Memory CMP Systems

Balancing DRAM Locality and Parallelism in Shared Memory CMP Systems Balancing DRAM Locality and Parallelism in Shared Memory CMP Systems Min Kyu Jeong, Doe Hyun Yoon^, Dam Sunwoo*, Michael Sullivan, Ikhwan Lee, and Mattan Erez The University of Texas at Austin Hewlett-Packard

More information