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Design-Induced Latency Variation in Modern DRAM Chips: Characterization, Analysis, and Latency Reduction Mechanisms

Published: 05 June 2017 Publication History

Abstract

Variation has been shown to exist across the cells within a modern DRAM chip. Prior work has studied and exploited several forms of variation, such as manufacturing-process- or temperature-induced variation. We empirically demonstrate a new form of variation that exists within a real DRAM chip, induced by the design and placement of different components in the DRAM chip: different regions in DRAM, based on their relative distances from the peripheral structures, require different minimum access latencies for reliable operation. In particular, we show that in most real DRAM chips, cells closer to the peripheral structures can be accessed much faster than cells that are farther. We call this phenomenon design-induced variation in DRAM. Our goals are to i) understand design-induced variation that exists in real, state-of-the-art DRAM chips, ii) exploit it to develop low-cost mechanisms that can dynamically find and use the lowest latency at which to operate a DRAM chip reliably, and, thus, iii) improve overall system performance while ensuring reliable system operation. To this end, we first experimentally demonstrate and analyze designed-induced variation in modern DRAM devices by testing and characterizing 96 DIMMs (768 DRAM chips). Our experimental study shows that i) modern DRAM chips exhibit design-induced latency variation in both row and column directions, ii) access latency gradually increases in the row direction within a DRAM cell array (mat) and this pattern repeats in every mat, and iii) some columns require higher latency than others due to the internal hierarchical organization of the DRAM chip.
Our characterization identifies DRAM regions that are vulnerable to errors, if operated at lower latency, and finds consistency in their locations across a given DRAM chip generation, due to design-induced variation. Variations in the vertical and horizontal dimensions, together, divide the cell array into heterogeneous-latency regions, where cells in some regions require longer access latencies for reliable operation. Reducing the latency uniformly across all regions in DRAM would improve performance, but can introduce failures in the inherently slower regions that require longer access latencies for correct operation. We refer to these inherently slower regions of DRAM as design-induced vulnerable regions.
Based on our extensive experimental analysis, we develop two mechanisms that reliably reduce DRAM latency. First, DIVI Profiling uses runtime profiling to dynamically identify the lowest DRAM latency that does not introduce failures. DIVA Profiling exploits design-induced variation and periodically profiles only the vulnerable regions to determine the lowest DRAM latency at low cost. It is the first mechanism to dynamically determine the lowest latency that can be used to operate DRAM reliably. DIVA Profiling reduces the latency of read/write requests by 35.1%/57.8%, respectively, at 55C. Our second mechanism, DIVA Shuffling, shuffles data such that values stored in vulnerable regions are mapped to multiple error-correcting code (ECC) codewords. As a result, DIVA Shuffling can correct 26% more multi-bit errors than conventional ECC. Combined together, our two mechanisms reduce read/write latency by 40.0%/60.5%, which translates to an overall system performance improvement of 14.7%/13.7%/13.8% (in 2-/4-/8-core systems) over a variety of workloads, while ensuring reliable operation.

Cited By

View all
  • (2023)RowPress: Amplifying Read Disturbance in Modern DRAM ChipsProceedings of the 50th Annual International Symposium on Computer Architecture10.1145/3579371.3589063(1-18)Online publication date: 17-Jun-2023
  • (2023)A Low-Cost Reduced-Latency DRAM Architecture With Dynamic Reconfiguration of Row DecoderIEEE Transactions on Very Large Scale Integration (VLSI) Systems10.1109/TVLSI.2022.321943731:1(128-141)Online publication date: Jan-2023
  • (2023)DRAM Bender: An Extensible and Versatile FPGA-Based Infrastructure to Easily Test State-of-the-Art DRAM ChipsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2023.328217242:12(5098-5112)Online publication date: Dec-2023
  • Show More Cited By

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Published In

cover image ACM Conferences
SIGMETRICS '17 Abstracts: Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems
June 2017
84 pages
ISBN:9781450350327
DOI:10.1145/3078505
  • cover image ACM SIGMETRICS Performance Evaluation Review
    ACM SIGMETRICS Performance Evaluation Review  Volume 45, Issue 1
    Performance evaluation review
    June 2017
    70 pages
    ISSN:0163-5999
    DOI:10.1145/3143314
    Issue’s Table of Contents
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 June 2017

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Author Tags

  1. DRAM
  2. fault tolerance
  3. latency variation
  4. memory systems

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  • Abstract

Funding Sources

  • NSF
  • VMware
  • Google
  • Nvidia
  • Samsung
  • The Intel Science and Technology Center for Cloud Computing, and the Semiconductor Research Corporation
  • Intel

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SIGMETRICS '17
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SIGMETRICS '17 Abstracts Paper Acceptance Rate 27 of 76 submissions, 36%;
Overall Acceptance Rate 459 of 2,691 submissions, 17%

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Cited By

View all
  • (2023)RowPress: Amplifying Read Disturbance in Modern DRAM ChipsProceedings of the 50th Annual International Symposium on Computer Architecture10.1145/3579371.3589063(1-18)Online publication date: 17-Jun-2023
  • (2023)A Low-Cost Reduced-Latency DRAM Architecture With Dynamic Reconfiguration of Row DecoderIEEE Transactions on Very Large Scale Integration (VLSI) Systems10.1109/TVLSI.2022.321943731:1(128-141)Online publication date: Jan-2023
  • (2023)DRAM Bender: An Extensible and Versatile FPGA-Based Infrastructure to Easily Test State-of-the-Art DRAM ChipsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2023.328217242:12(5098-5112)Online publication date: Dec-2023
  • (2023)CDAR-DRAM: Enabling Runtime DRAM Performance and Energy Optimization via In-Situ Charge Detection and Adaptive Data RestorationIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2023.323829242:9(3078-3091)Online publication date: Sep-2023
  • (2023)An Experimental Analysis of RowHammer in HBM2 DRAM Chips2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S)10.1109/DSN-S58398.2023.00042(151-156)Online publication date: Jun-2023
  • (2023)Extending Memory Capacity in Modern Consumer Systems With Emerging Non-Volatile Memory: Experimental Analysis and Characterization Using the Intel Optane SSDIEEE Access10.1109/ACCESS.2023.331788411(105843-105871)Online publication date: 2023
  • (2023)High-Performance and Power-Saving Mechanism for Page Activations Based on Full Independent DRAM Sub-Arrays in Multi-Core SystemsIEEE Access10.1109/ACCESS.2023.329984811(79801-79822)Online publication date: 2023
  • (2023)Using Approximate DRAM for Enabling Energy-Efficient, High-Performance Deep Neural Network InferenceEmbedded Machine Learning for Cyber-Physical, IoT, and Edge Computing10.1007/978-3-031-19568-6_10(275-314)Online publication date: 1-Oct-2023
  • (2022)PiDRAM: A Holistic End-to-end FPGA-based Framework for Processing-in-DRAMACM Transactions on Architecture and Code Optimization10.1145/356369720:1(1-31)Online publication date: 17-Nov-2022
  • (2022)pLUTo: Enabling Massively Parallel Computation in DRAM via Lookup TablesProceedings of the 55th Annual IEEE/ACM International Symposium on Microarchitecture10.1109/MICRO56248.2022.00067(900-919)Online publication date: 1-Oct-2022
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