163 research outputs found

    Energy Saving Techniques for Phase Change Memory (PCM)

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    In recent years, the energy consumption of computing systems has increased and a large fraction of this energy is consumed in main memory. Towards this, researchers have proposed use of non-volatile memory, such as phase change memory (PCM), which has low read latency and power; and nearly zero leakage power. However, the write latency and power of PCM are very high and this, along with limited write endurance of PCM present significant challenges in enabling wide-spread adoption of PCM. To address this, several architecture-level techniques have been proposed. In this report, we review several techniques to manage power consumption of PCM. We also classify these techniques based on their characteristics to provide insights into them. The aim of this work is encourage researchers to propose even better techniques for improving energy efficiency of PCM based main memory.Comment: Survey, phase change RAM (PCRAM

    Codeword assignment for cell-write reduction in non-volatile memory technologies

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    This thesis explores a context-independent limited-weight codeword assignment architecture for cell-write reduction in emerging single-level cell (SLC) and multi-level cell (MLC) non-volatile memories (NVMs). Cell-write reduction in NVMs has many practical benefits, including lower write latency, lower dynamic energy, and enhanced endurance. The proposed architecture, which is integrated into the memory controller, relies on an a priori analysis of memory access patterns and a remapping table to minimize overwrites in NVM cells. The baseline for comparison used for comparing our algorithms is a technique known as data-comparison write (DCW) which performs a cell-wise comparison of the write data before each operation. This reduces cell-writes by allowing only the cells whose value changes to be rewritten. Similarly, Flip-N-Write (FNW), a technique which allows each word written to memory to be optionally inverted, serves as the state-of-the-art technique our schemes outperform. Our first algorithm relies on the different frequencies with which each value is written to memory to perform a frequency-based assignment (FBA) of codewords. Based on a set of training data, the most frequently occurring values are mapped to limited-weight codes (LWC) to reduce the number of bit-writes. Our second algorithm further improves upon FBA by considering the sequence in which values transition to one another to perform a sequence-based assignment (SBA) of codewords. All three methods are then modified to provide similar improvements in multi-level cell (MLC) memories. Since bit-write reduction is distinct from cell-write reduction in MLC, the LWCs are changed for FBA, the algorithm used by SBA to calculate node weights are modified, and a different approach to cell inversion for FNW is considered. Trace-based simulations of the SPEC CPU2006 benchmarks show a 33ร— reduction in raw bit-writes in SLC and a 28ร— reduction in raw cell-writes in 2-bit MLC. These correspond to a 19% and 15% improvement over the best state-of-the-art method respectively

    ์ƒ๋ณ€ํ™” ๋ฉ”๋ชจ๋ฆฌ ์‹œ์Šคํ…œ์˜ ๊ฐ„์„ญ ์˜ค๋ฅ˜ ์™„ํ™” ๋ฐ RMW ์„ฑ๋Šฅ ํ–ฅ์ƒ ๊ธฐ๋ฒ•

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ •๋ณด๊ณตํ•™๋ถ€, 2021.8. ์ดํ˜์žฌ.Phase-change memory (PCM) announces the beginning of the new era of memory systems, owing to attractive characteristics. Many memory product manufacturers (e.g., Intel, SK Hynix, and Samsung) are developing related products. PCM can be applied to various circumstances; it is not simply limited to an extra-scale database. For example, PCM has a low standby power due to its non-volatility; hence, computation-intensive applications or mobile applications (i.e., long memory idle time) are suitable to run on PCM-based computing systems. Despite these fascinating features of PCM, PCM is still far from the general commercial market due to low reliability and long latency problems. In particular, low reliability is a painful problem for PCM in past decades. As the semiconductor process technology rapidly scales down over the years, DRAM reaches 10 nm class process technology. In addition, it is reported that the write disturbance error (WDE) would be a serious issue for PCM if it scales down below 54 nm class process technology. Therefore, addressing the problem of WDEs becomes essential to make PCM competitive to DRAM. To overcome this problem, this dissertation proposes a novel approach that can restore meta-stable cells on demand by levering two-level SRAM-based tables, thereby significantly reducing the number WDEs. Furthermore, a novel randomized approach is proposed to implement a replacement policy that originally requires hundreds of read ports on SRAM. The second problem of PCM is a long-latency compared to that of DRAM. In particular, PCM tries to enhance its throughput by adopting a larger transaction unit; however, the different unit size from the general-purpose processor cache line further degrades the system performance due to the introduction of a read-modify-write (RMW) module. Since there has never been any research related to RMW in a PCM-based memory system, this dissertation proposes a novel architecture to enhance the overall system performance and reliability of a PCM-based memory system having an RMW module. The proposed architecture enhances data re-usability without introducing extra storage resources. Furthermore, a novel operation that merges commands regardless of command types is proposed to enhance performance notably. Another problem is the absence of a full simulation platform for PCM. While the announced features of the PCM-related product (i.e., Intel Optane) are scarce due to confidential issues, all priceless information can be integrated to develop an architecture simulator that resembles the available product. To this end, this dissertation tries to scrape up all available features of modules in a PCM controller and implement a dedicated simulator for future research purposes.์ƒ๋ณ€ํ™” ๋ฉ”๋ชจ๋ฆฌ๋Š”(PCM) ๋งค๋ ฅ์ ์ธ ํŠน์„ฑ์„ ํ†ตํ•ด ๋ฉ”๋ชจ๋ฆฌ ์‹œ์Šคํ…œ์˜ ์ƒˆ๋กœ์šด ์‹œ๋Œ€์˜ ์‹œ์ž‘์„ ์•Œ๋ ธ๋‹ค. ๋งŽ์€ ๋ฉ”๋ชจ๋ฆฌ ๊ด€๋ จ ์ œํ’ˆ ์ œ์กฐ์—…์ฒด(์˜ˆ : ์ธํ…”, SK ํ•˜์ด๋‹‰์Šค, ์‚ผ์„ฑ)๊ฐ€ ๊ด€๋ จ ์ œํ’ˆ ๊ฐœ๋ฐœ์— ๋ฐ•์ฐจ๋ฅผ ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค. PCM์€ ๋‹จ์ˆœํžˆ ๋Œ€๊ทœ๋ชจ ๋ฐ์ดํ„ฐ๋ฒ ์ด์Šค์—๋งŒ ๊ตญํ•œ๋˜์ง€ ์•Š๊ณ  ๋‹ค์–‘ํ•œ ์ƒํ™ฉ์— ์ ์šฉ๋  ์ˆ˜ ์žˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, PCM์€ ๋น„ํœ˜๋ฐœ์„ฑ์œผ๋กœ ์ธํ•ด ๋Œ€๊ธฐ ์ „๋ ฅ์ด ๋‚ฎ๋‹ค. ๋”ฐ๋ผ์„œ ๊ณ„์‚ฐ ์ง‘์•ฝ์ ์ธ ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜ ๋˜๋Š” ๋ชจ๋ฐ”์ผ ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์€(์ฆ‰, ๊ธด ๋ฉ”๋ชจ๋ฆฌ ์œ ํœด ์‹œ๊ฐ„) PCM ๊ธฐ๋ฐ˜ ์ปดํ“จํŒ… ์‹œ์Šคํ…œ์—์„œ ์‹คํ–‰ํ•˜๊ธฐ์— ์ ํ•ฉํ•˜๋‹ค. PCM์˜ ์ด๋Ÿฌํ•œ ๋งค๋ ฅ์ ์ธ ํŠน์„ฑ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  PCM์€ ๋‚ฎ์€ ์‹ ๋ขฐ์„ฑ๊ณผ ๊ธด ๋Œ€๊ธฐ ์‹œ๊ฐ„์œผ๋กœ ์ธํ•ด ์—ฌ์ „ํžˆ ์ผ๋ฐ˜ ์‚ฐ์—… ์‹œ์žฅ์—์„œ๋Š” DRAM๊ณผ ๋‹ค์†Œ ๊ฒฉ์ฐจ๊ฐ€ ์žˆ๋‹ค. ํŠนํžˆ ๋‚ฎ์€ ์‹ ๋ขฐ์„ฑ์€ ์ง€๋‚œ ์ˆ˜์‹ญ ๋…„ ๋™์•ˆ PCM ๊ธฐ์ˆ ์˜ ๋ฐœ์ „์„ ์ €ํ•ดํ•˜๋Š” ๋ฌธ์ œ๋‹ค. ๋ฐ˜๋„์ฒด ๊ณต์ • ๊ธฐ์ˆ ์ด ์ˆ˜๋…„์— ๊ฑธ์ณ ๋น ๋ฅด๊ฒŒ ์ถ•์†Œ๋จ์— ๋”ฐ๋ผ DRAM์€ 10nm ๊ธ‰ ๊ณต์ • ๊ธฐ์ˆ ์— ๋„๋‹ฌํ•˜์˜€๋‹ค. ์ด์–ด์„œ, ์“ฐ๊ธฐ ๋ฐฉํ•ด ์˜ค๋ฅ˜ (WDE)๊ฐ€ 54nm ๋“ฑ๊ธ‰ ํ”„๋กœ์„ธ์Šค ๊ธฐ์ˆ  ์•„๋ž˜๋กœ ์ถ•์†Œ๋˜๋ฉด PCM์— ์‹ฌ๊ฐํ•œ ๋ฌธ์ œ๊ฐ€ ๋  ๊ฒƒ์œผ๋กœ ๋ณด๊ณ ๋˜์—ˆ๋‹ค. ๋”ฐ๋ผ์„œ, WDE ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๋Š” ๊ฒƒ์€ PCM์ด DRAM๊ณผ ๋™๋“ฑํ•œ ๊ฒฝ์Ÿ๋ ฅ์„ ๊ฐ–์ถ”๋„๋ก ํ•˜๋Š” ๋ฐ ์žˆ์–ด ํ•„์ˆ˜์ ์ด๋‹ค. ์ด ๋ฌธ์ œ๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•ด ์ด ๋…ผ๋ฌธ์—์„œ๋Š” 2-๋ ˆ๋ฒจ SRAM ๊ธฐ๋ฐ˜ ํ…Œ์ด๋ธ”์„ ํ™œ์šฉํ•˜์—ฌ WDE ์ˆ˜๋ฅผ ํฌ๊ฒŒ ์ค„์—ฌ ํ•„์š”์— ๋”ฐ๋ผ ์ค€ ์•ˆ์ • ์…€์„ ๋ณต์›ํ•  ์ˆ˜ ์žˆ๋Š” ์ƒˆ๋กœ์šด ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ œ์•ˆํ•œ๋‹ค. ๋˜ํ•œ, ์›๋ž˜ SRAM์—์„œ ์ˆ˜๋ฐฑ ๊ฐœ์˜ ์ฝ๊ธฐ ํฌํŠธ๊ฐ€ ํ•„์š”ํ•œ ๋Œ€์ฒด ์ •์ฑ…์„ ๊ตฌํ˜„ํ•˜๊ธฐ ์œ„ํ•ด ์ƒˆ๋กœ์šด ๋žœ๋ค ๊ธฐ๋ฐ˜์˜ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. PCM์˜ ๋‘ ๋ฒˆ์งธ ๋ฌธ์ œ๋Š” DRAM์— ๋น„ํ•ด ์ง€์—ฐ ์‹œ๊ฐ„์ด ๊ธธ๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ํŠนํžˆ PCM์€ ๋” ํฐ ํŠธ๋žœ์žญ์…˜ ๋‹จ์œ„๋ฅผ ์ฑ„ํƒํ•˜์—ฌ ๋‹จ์œ„์‹œ๊ฐ„ ๋‹น ๋ฐ์ดํ„ฐ ์ฒ˜๋ฆฌ๋Ÿ‰ ํ–ฅ์ƒ์„ ๋„๋ชจํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋ฒ”์šฉ ํ”„๋กœ์„ธ์„œ ์บ์‹œ ๋ผ์ธ๊ณผ ๋‹ค๋ฅธ ์œ ๋‹› ํฌ๊ธฐ๋Š” ์ฝ๊ธฐ-์ˆ˜์ •-์“ฐ๊ธฐ (RMW) ๋ชจ๋“ˆ์˜ ๋„์ž…์œผ๋กœ ์ธํ•ด ์‹œ์Šคํ…œ ์„ฑ๋Šฅ์„ ์ €ํ•˜ํ•˜๊ฒŒ ๋œ๋‹ค. PCM ๊ธฐ๋ฐ˜ ๋ฉ”๋ชจ๋ฆฌ ์‹œ์Šคํ…œ์—์„œ RMW ๊ด€๋ จ ์—ฐ๊ตฌ๊ฐ€ ์—†์—ˆ๊ธฐ ๋•Œ๋ฌธ์— ๋ณธ ๋…ผ๋ฌธ์€ RMW ๋ชจ๋“ˆ์„ ํƒ‘์žฌ ํ•œ PCM ๊ธฐ๋ฐ˜ ๋ฉ”๋ชจ๋ฆฌ ์‹œ์Šคํ…œ์˜ ์ „๋ฐ˜์ ์ธ ์‹œ์Šคํ…œ ์„ฑ๋Šฅ๊ณผ ์‹ ๋ขฐ์„ฑ์„ ํ–ฅ์ƒํ•˜๊ฒŒ ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š” ์ƒˆ๋กœ์šด ์•„ํ‚คํ…์ฒ˜๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆ๋œ ์•„ํ‚คํ…์ฒ˜๋Š” ์ถ”๊ฐ€ ์Šคํ† ๋ฆฌ์ง€ ๋ฆฌ์†Œ์Šค๋ฅผ ๋„์ž…ํ•˜์ง€ ์•Š๊ณ ๋„ ๋ฐ์ดํ„ฐ ์žฌ์‚ฌ์šฉ์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚จ๋‹ค. ๋˜ํ•œ, ์„ฑ๋Šฅ ํ–ฅ์ƒ์„ ์œ„ํ•ด ๋ช…๋ น ์œ ํ˜•๊ณผ ๊ด€๊ณ„์—†์ด ๋ช…๋ น์„ ๋ณ‘ํ•ฉํ•˜๋Š” ์ƒˆ๋กœ์šด ์ž‘์—…์„ ์ œ์•ˆํ•œ๋‹ค. ๋˜ ๋‹ค๋ฅธ ๋ฌธ์ œ๋Š” PCM์„ ์œ„ํ•œ ์™„์ „ํ•œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ํ”Œ๋žซํผ์ด ๋ถ€์žฌํ•˜๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. PCM ๊ด€๋ จ ์ œํ’ˆ(์˜ˆ : Intel Optane)์— ๋Œ€ํ•ด ๋ฐœํ‘œ๋œ ์ •๋ณด๋Š” ๋Œ€์™ธ๋น„ ๋ฌธ์ œ๋กœ ์ธํ•ด ๋ถ€์กฑํ•˜๋‹ค. ํ•˜์ง€๋งŒ ์•Œ๋ ค์ ธ ์žˆ๋Š” ์ •๋ณด๋ฅผ ์ ์ ˆํžˆ ์ทจํ•ฉํ•˜๋ฉด ์‹œ์ค‘ ์ œํ’ˆ๊ณผ ์œ ์‚ฌํ•œ ์•„ํ‚คํ…์ฒ˜ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ๋ฅผ ๊ฐœ๋ฐœํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๋ณธ ๋…ผ๋ฌธ์€ PCM ๋ฉ”๋ชจ๋ฆฌ ์ปจํŠธ๋กค๋Ÿฌ์— ํ•„์š”ํ•œ ๋ชจ๋“  ๋ชจ๋“ˆ ์ •๋ณด๋ฅผ ํ™œ์šฉํ•˜์—ฌ ํ–ฅํ›„ ์ด์™€ ๊ด€๋ จ๋œ ์—ฐ๊ตฌ์—์„œ ์ถฉ๋ถ„ํžˆ ์‚ฌ์šฉ ๊ฐ€๋Šฅํ•œ ์ „์šฉ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ๋ฅผ ๊ตฌํ˜„ํ•˜์˜€๋‹ค.1 INTRODUCTION 1 1.1 Limitation of Traditional Main Memory Systems 1 1.2 Phase-Change Memory as Main Memory 3 1.2.1 Opportunities of PCM-based System 3 1.2.2 Challenges of PCM-based System 4 1.3 Dissertation Overview 7 2 BACKGROUND AND PREVIOUS WORK 8 2.1 Phase-Change Memory 8 2.2 Mitigation Schemes for Write Disturbance Errors 10 2.2.1 Write Disturbance Errors 10 2.2.2 Verification and Correction 12 2.2.3 Lazy Correction 13 2.2.4 Data Encoding-based Schemes 14 2.2.5 Sparse-Insertion Write Cache 16 2.3 Performance Enhancement for Read-Modify-Write 17 2.3.1 Traditional Read-Modify-Write 17 2.3.2 Write Coalescing for RMW 19 2.4 Architecture Simulators for PCM 21 2.4.1 NVMain 21 2.4.2 Ramulator 22 2.4.3 DRAMsim3 22 3 IN-MODULE DISTURBANCE BARRIER 24 3.1 Motivation 25 3.2 IMDB: In Module-Disturbance Barrier 29 3.2.1 Architectural Overview 29 3.2.2 Implementation of Data Structures 30 3.2.3 Modification of Media Controller 36 3.3 Replacement Policy 38 3.3.1 Replacement Policy for IMDB 38 3.3.2 Approximate Lowest Number Estimator 40 3.4 Putting All Together: Case Studies 43 3.5 Evaluation 45 3.5.1 Configuration 45 3.5.2 Architectural Exploration 47 3.5.3 Effectiveness of the Replacement Policy 48 3.5.4 Sensitivity to Main Table Configuration 49 3.5.5 Sensitivity to Barrier Buffer Size 51 3.5.6 Sensitivity to AppLE Group Size 52 3.5.7 Comparison with Other Studies 54 3.6 Discussion 59 3.7 Summary 63 4 INTEGRATION OF AN RMW MODULE IN A PCM-BASED SYSTEM 64 4.1 Motivation 65 4.2 Utilization of DRAM Cache for RMW 67 4.2.1 Architectural Design 67 4.2.2 Algorithm 70 4.3 Typeless Command Merging 73 4.3.1 Architectural Design 73 4.3.2 Algorithm 74 4.4 An Alternative Implementation: SRC-RMW 78 4.4.1 Implementation of SRC-RMW 78 4.4.2 Design Constraint 80 4.5 Case Study 82 4.6 Evaluation 85 4.6.1 Configuration 85 4.6.2 Speedup 88 4.6.3 Read Reliability 91 4.6.4 Energy Consumption: Selecting a Proper Page Size 93 4.6.5 Comparison with Other Studies 95 4.7 Discussion 97 4.8 Summary 99 5 AN ALL-INCLUSIVE SIMULATOR FOR A PCM CONTROLLER 100 5.1 Motivation 101 5.2 PCMCsim: PCM Controller Simulator 103 5.2.1 Architectural Overview 103 5.2.2 Underlying Classes of PCMCsim 104 5.2.3 Implementation of Contention Behavior 108 5.2.4 Modules of PCMCsim 109 5.3 Evaluation 116 5.3.1 Correctness of the Simulator 116 5.3.2 Comparison with Other Simulators 117 5.4 Summary 119 6 Conclusion 120 Abstract (In Korean) 141 Acknowledgment 143๋ฐ•

    DESTINY: A Comprehensive Tool with 3D and Multi-Level Cell Memory Modeling Capability

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    To enable the design of large capacity memory structures, novel memory technologies such as non-volatile memory (NVM) and novel fabrication approaches, e.g., 3D stacking and multi-level cell (MLC) design have been explored. The existing modeling tools, however, cover only a few memory technologies, technology nodes and fabrication approaches. We present DESTINY, a tool for modeling 2D/3D memories designed using SRAM, resistive RAM (ReRAM), spin transfer torque RAM (STT-RAM), phase change RAM (PCM) and embedded DRAM (eDRAM) and 2D memories designed using spin orbit torque RAM (SOT-RAM), domain wall memory (DWM) and Flash memory. In addition to single-level cell (SLC) designs for all of these memories, DESTINY also supports modeling MLC designs for NVMs. We have extensively validated DESTINY against commercial and research prototypes of these memories. DESTINY is very useful for performing design-space exploration across several dimensions, such as optimizing for a target (e.g., latency, area or energy-delay product) for a given memory technology, choosing the suitable memory technology or fabrication method (i.e., 2D v/s 3D) for a given optimization target, etc. We believe that DESTINY will boost studies of next-generation memory architectures used in systems ranging from mobile devices to extreme-scale supercomputers. The latest source-code of DESTINY is available from the following git repository: https://bitbucket.org/sparsh_mittal/destiny_v2
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