423 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

    Improving Phase Change Memory Performance with Data Content Aware Access

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    A prominent characteristic of write operation in Phase-Change Memory (PCM) is that its latency and energy are sensitive to the data to be written as well as the content that is overwritten. We observe that overwriting unknown memory content can incur significantly higher latency and energy compared to overwriting known all-zeros or all-ones content. This is because all-zeros or all-ones content is overwritten by programming the PCM cells only in one direction, i.e., using either SET or RESET operations, not both. In this paper, we propose data content aware PCM writes (DATACON), a new mechanism that reduces the latency and energy of PCM writes by redirecting these requests to overwrite memory locations containing all-zeros or all-ones. DATACON operates in three steps. First, it estimates how much a PCM write access would benefit from overwriting known content (e.g., all-zeros, or all-ones) by comprehensively considering the number of set bits in the data to be written, and the energy-latency trade-offs for SET and RESET operations in PCM. Second, it translates the write address to a physical address within memory that contains the best type of content to overwrite, and records this translation in a table for future accesses. We exploit data access locality in workloads to minimize the address translation overhead. Third, it re-initializes unused memory locations with known all-zeros or all-ones content in a manner that does not interfere with regular read and write accesses. DATACON overwrites unknown content only when it is absolutely necessary to do so. We evaluate DATACON with workloads from state-of-the-art machine learning applications, SPEC CPU2017, and NAS Parallel Benchmarks. Results demonstrate that DATACON significantly improves system performance and memory system energy consumption compared to the best of performance-oriented state-of-the-art techniques.Comment: 18 pages, 21 figures, accepted at ACM SIGPLAN International Symposium on Memory Management (ISMM

    Exploiting Inter- and Intra-Memory Asymmetries for Data Mapping in Hybrid Tiered-Memories

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    Modern computing systems are embracing hybrid memory comprising of DRAM and non-volatile memory (NVM) to combine the best properties of both memory technologies, achieving low latency, high reliability, and high density. A prominent characteristic of DRAM-NVM hybrid memory is that it has NVM access latency much higher than DRAM access latency. We call this inter-memory asymmetry. We observe that parasitic components on a long bitline are a major source of high latency in both DRAM and NVM, and a significant factor contributing to high-voltage operations in NVM, which impact their reliability. We propose an architectural change, where each long bitline in DRAM and NVM is split into two segments by an isolation transistor. One segment can be accessed with lower latency and operating voltage than the other. By introducing tiers, we enable non-uniform accesses within each memory type (which we call intra-memory asymmetry), leading to performance and reliability trade-offs in DRAM-NVM hybrid memory. We extend existing NVM-DRAM OS in three ways. First, we exploit both inter- and intra-memory asymmetries to allocate and migrate memory pages between the tiers in DRAM and NVM. Second, we improve the OS's page allocation decisions by predicting the access intensity of a newly-referenced memory page in a program and placing it to a matching tier during its initial allocation. This minimizes page migrations during program execution, lowering the performance overhead. Third, we propose a solution to migrate pages between the tiers of the same memory without transferring data over the memory channel, minimizing channel occupancy and improving performance. Our overall approach, which we call MNEME, to enable and exploit asymmetries in DRAM-NVM hybrid tiered memory improves both performance and reliability for both single-core and multi-programmed workloads.Comment: 15 pages, 29 figures, accepted at ACM SIGPLAN International Symposium on Memory Managemen

    Staged reads: mitigating the impact of DRAM writes on DRAM reads

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    Journal ArticleMain memory latencies have always been a concern for system performance. Given that reads are on the criti- cal path for CPU progress, reads must be prioritized over writes. However, writes must be eventually processed and they often delay pending reads. In fact, a single channel in the main memory system offers almost no parallelism between reads and writes. This is because a single off-chip memory bus is shared by reads and writes and the direction of the bus has to be explicitly turned around when switching from writes to reads. This is an expensive operation and its cost is amortized by carrying out a burst of writes or reads every time the bus direction is switched. As a result, no reads can be processed while a memory channel is busy servicing writes. This paper proposes a novel mechanism to boost read-write parallelism and perform useful components of read operations even when the memory system is busy performing writes. If some of the banks are busy servicing writes, we start issuing reads to the other idle banks. The results of these reads are stored in a few registers near the memory chip's I/O pads. These results are quickly returned immediately following the bus turnaround. The process is referred to as a Staged Read because it decouples a single read operation into two stages, with the first step being performed in parallel with writes. This innovation can also be viewed as a form of prefetch that is internal to a memory chip. The proposed tech- nique works best when there is bank imbalance in the write stream. We also introduce a write scheduling algorithm that artificially creates bank imbalance and allows useful read operations to be performed during the write drain. Across a suite of memory-intensive workloads, we show that Staged Reads can boost throughput by up to 33% (average 7%) with an average DRAM access latency improvement of 17%, while incurring a very small cost (0.25%) in terms of memory chip area. The throughput improvements are even greater when considering write-intensive work-loads (average 11%) or future systems (average 12%)

    Constructing Reliable Super Dense Phase Change Memory under Write Disturbance

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    Phase Change Memory (PCM) has better scalability and smaller cell size comparing to DRAM. However, further scaling PCM cell in deep sub-micron regime results in significant thermal based write disturbance. Naively allocating large inter-cell space increases cell size from ideal 4F^2 to 12F^2. While a recent work mitigates write disturbance along word-lines through disturbance resilient data encoding, which can shrink PCM cell size from 12F^2 to 8F^2, it is ineffective for write disturbance along bit-lines, which is more severe due to widely adopted uTrench structure in constructing PCM cell arrays. In this thesis, we propose SD-PCM, an architecture to achieve reliable write operations in Super Dense PCM. In particular, we focus on mitigating write disturbance along bit-lines such that we can construct super dense PCM chips with 4F^2 cell size, i.e., the minimal for diode-switch based PCM. Based on simple verification-n-correction (VnC), we propose LazyCorrection and PreRead to effectively reduce VnC overhead and minimize cascading verification during write. We further propose (n:m)-Alloc for achieving good tradeoff between VnC overhead minimization and memory capacity loss. Our experimental results show that, comparing to a write disturbance-free low density PCM, SD-PCM achieves 80% capacity improvement in cell arrays while incurring around 0-10% performance degradation when using different (n:m) allocators

    Aging-Aware Request Scheduling for Non-Volatile Main Memory

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    Modern computing systems are embracing non-volatile memory (NVM) to implement high-capacity and low-cost main memory. Elevated operating voltages of NVM accelerate the aging of CMOS transistors in the peripheral circuitry of each memory bank. Aggressive device scaling increases power density and temperature, which further accelerates aging, challenging the reliable operation of NVM-based main memory. We propose HEBE, an architectural technique to mitigate the circuit aging-related problems of NVM-based main memory. HEBE is built on three contributions. First, we propose a new analytical model that can dynamically track the aging in the peripheral circuitry of each memory bank based on the bank's utilization. Second, we develop an intelligent memory request scheduler that exploits this aging model at run time to de-stress the peripheral circuitry of a memory bank only when its aging exceeds a critical threshold. Third, we introduce an isolation transistor to decouple parts of a peripheral circuit operating at different voltages, allowing the decoupled logic blocks to undergo long-latency de-stress operations independently and off the critical path of memory read and write accesses, improving performance. We evaluate HEBE with workloads from the SPEC CPU2017 Benchmark suite. Our results show that HEBE significantly improves both performance and lifetime of NVM-based main memory.Comment: To appear in ASP-DAC 202

    Architectural Techniques for Multi-Level Cell Phase Change Memory Based Main Memory

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    Phase change memory (PCM) recently has emerged as a promising technology to meet the fast growing demand for large capacity main memory in modern computing systems. Multi-level cell (MLC) PCM storing multiple bits in a single cell offers high density with low per-byte fabrication cost. However, PCM suffers from long write latency, short cell endurance, limited write throughput and high peak power, which makes it challenging to be integrated in the memory hierarchy. To address the long write latency, I propose write truncation to reduce the number of write iterations with the assistance of an extra error correction code (ECC). I also propose form switch (FS) to reduce the storage overhead of the ECC. By storing highly compressible lines in single level cell (SLC) form, FS improves read latency as well. To attack the short cell endurance and large peak power, I propose elastic RESET (ER) to construct triple-level cell PCM. By reducing RESET energy, ER significantly reduces peak power and prolongs PCM lifetime. To improve the write concurrency, I propose fine-grained write power budgeting (FPB) observing a global power budget and regulates power across write iterations according to the step-down power demand of each iteration. A global charge pump is also integrated onto a DIMM to boost power for hot PCM chips while staying within the global power budget. To further reduce the peak power, I propose intra-write RESET scheduling distributing cell RESET initializations in the whole write operation duration, so that the on-chip charge pump size can also be reduced

    Re-designing Main Memory Subsystems with Emerging Monolithic 3D (M3D) Integration and Phase Change Memory Technologies

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    Over the past two decades, Dynamic Random-Access Memory (DRAM) has emerged as the dominant technology for implementing the main memory subsystems of all types of computing systems. However, inferring from several recent trends, computer architects in both the industry and academia have widely accepted that the density (memory capacity per chip area) and latency of DRAM based main memory subsystems cannot sufficiently scale in the future to meet the requirements of future data-centric workloads related to Artificial Intelligence (AI), Big Data, and Internet-of-Things (IoT). In fact, the achievable density and access latency in main memory subsystems presents a very fundamental trade-off. Pushing for a higher density inevitably increases access latency, and pushing for a reduced access latency often leads to a decreased density. This trade-off is so fundamental in DRAM based main memory subsystems that merely looking to re-architect DRAM subsystems cannot improve this trade-off, unless disruptive technological advancements are realized for implementing main memory subsystems. In this thesis, we focus on two key contributions to overcome the density (represented as the total chip area for the given capacity) and access latency related challenges in main memory subsystems. First, we show that the fundamental area-latency trade-offs in DRAM can be significantly improved by redesigning the DRAM cell-array structure using the emerging monolithic 3D (M3D) integration technology. A DRAM bank structure can be split across two or more M3D-integrated tiers on the same DRAM chip, to consequently be able to significantly reduce the total on-chip area occupancy of the DRAM bank and its access peripherals. This approach is fundamentally different from the well known approach of through-silicon vias (TSVs)-based 3D stacking of DRAM tiers. This is because the M3D integration based approach does not require a separate DRAM chip per tier, whereas the 3D-stacking based approach does. Our evaluation results for PARSEC benchmarks show that our designed M3D DRAM cellarray organizations can yield up to 9.56% less latency and up to 21.21% less energy-delay product (EDP), with up to 14% less DRAM die area, compared to the conventional 2D DDR4 DRAM. Second, we demonstrate a pathway for eliminating the write disturbance errors in single-level-cell PCM, thereby positioning the PCM technology, which has inherently more relaxed density and latency trade-off compared to DRAM, as a more viable option for replacing the DRAM technology. We introduce low-temperature partial-RESET operations for writing ‘0’s in PCM cells. Compared to traditional operations that write \u270\u27s in PCM cells, partial-RESET operations do not cause disturbance errors in neighboring cells during PCM writes. The overarching theme that connects the two individual contributions into this single thesis is the density versus latency argument. The existing PCM technology has 3 to 4× higher write latency compared to DRAM; nevertheless, the existing PCM technology can store 2 to 4 bits in a single cell compared to one bit per cell storage capacity of DRAM. Therefore, unlike DRAM, it becomes possible to increase the density of PCM without consequently increasing PCM latency. In other words, PCM exhibits inherently improved (more relaxed) density and latency trade-off. Thus, both of our contributions in this thesis, the first contribution of re-designing DRAM with M3D integration technology and the second contribution of making the PCM technology a more viable replacement of DRAM by eliminating the write disturbance errors in PCM, connect to the common overarching goal of improving the density and latency trade-off in main memory subsystems. In addition, we also discuss in this thesis possible future research directions that are aimed at extending the impacts of our proposed ideas so that they can transform the performance of main memory subsystems of the future

    The Design of A High Capacity and Energy Efficient Phase Change Main Memory

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    Higher energy-efficiency has become essential in servers for a variety of reasons that range from heavy power and thermal constraints, environmental issues and financial savings. With main memory responsible for at least 30% of the energy consumed by a server, a low power main memory is fundamental to achieving this energy efficiency DRAM has been the technology of choice for main memory for the last three decades primarily because it traditionally combined relatively low power, high performance, low cost and high density. However, with DRAM nearing its density limit, alternative low-power memory technologies, such as Phase-change memory (PCM), have become a feasible replacement. PCM limitations, such as limited endurance and low write performance, preclude simple drop-in replacement and require new architectures and algorithms to be developed. A PCM main memory architecture (PMMA) is introduced in this dissertation, utilizing both DRAM and PCM, to create an energy-efficient main memory that is able to replace a DRAM-only memory. PMMA utilizes a number of techniques and architectural changes to achieve a level of performance that is par with DRAM. PMMA achieves gains in energy-delay of up to 65%, with less than 5% of performance loss and extremely high energy gains. To address the other major shortcoming of PCM, namely limited endurance, a novel, low- overhead wear-leveling algorithm that builds on PMMA is proposed that increases the lifetime of PMMA to match the expected server lifetime so that both server and memory subsystems become obsolete at about the same time. We also study how to better use the excess capacity, traditionally available on PCM devices, to obtain the highest lifetime possible. We show that under specific endurance distributions, the naive choice does not achieve the highest lifetime. We devise rules that empower the designer to select algorithms and parameters to achieve higher lifetime or simplify the design knowing the impact on the lifetime. The techniques presented also apply to other storage class memories (SCM) memories that suffer from limited endurance
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