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DRAM errors in the wild: a large-scale field study

Published: 15 June 2009 Publication History

Abstract

Errors in dynamic random access memory (DRAM) are a common form of hardware failure in modern compute clusters. Failures are costly both in terms of hardware replacement costs and service disruption. While a large body of work exists on DRAM in laboratory conditions, little has been reported on real DRAM failures in large production clusters. In this paper, we analyze measurements of memory errors in a large fleet of commodity servers over a period of 2.5 years. The collected data covers multiple vendors, DRAM capacities and technologies, and comprises many millions of DIMM days.
The goal of this paper is to answer questions such as the following: How common are memory errors in practice? What are their statistical properties? How are they affected by external factors, such as temperature and utilization, and by chip-specific factors, such as chip density, memory technology and DIMM age?
We find that DRAM error behavior in the field differs in many key aspects from commonly held assumptions. For example, we observe DRAM error rates that are orders of magnitude higher than previously reported, with 25,000 to 70,000 errors per billion device hours per Mbit and more than 8% of DIMMs affected by errors per year. We provide strong evidence that memory errors are dominated by hard errors, rather than soft errors, which previous work suspects to be the dominant error mode. We find that temperature, known to strongly impact DIMM error rates in lab conditions, has a surprisingly small effect on error behavior in the field, when taking all other factors into account. Finally, unlike commonly feared, we don't observe any indication that newer generations of DIMMs have worse error behavior.

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Published In

cover image ACM Conferences
SIGMETRICS '09: Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
June 2009
336 pages
ISBN:9781605585116
DOI:10.1145/1555349
  • cover image ACM SIGMETRICS Performance Evaluation Review
    ACM SIGMETRICS Performance Evaluation Review  Volume 37, Issue 1
    SIGMETRICS '09
    June 2009
    320 pages
    ISSN:0163-5999
    DOI:10.1145/2492101
    Issue’s Table of Contents
Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 15 June 2009

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Author Tags

  1. data corruption
  2. dimm
  3. dram
  4. dram reliability
  5. ecc
  6. empirical study
  7. hard error
  8. large-scale systems
  9. memory
  10. soft error

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  • (2024)Shadow Filesystems: Recovering from Filesystem Runtime Errors via Robust Alternative ExecutionProceedings of the 16th ACM Workshop on Hot Topics in Storage and File Systems10.1145/3655038.3665942(15-22)Online publication date: 8-Jul-2024
  • (2024)Supports for Testing Memory Error Handling Code of In-memory Key Value Stores2024 19th European Dependable Computing Conference (EDCC)10.1109/EDCC61798.2024.00020(41-48)Online publication date: 8-Apr-2024
  • (2024)Investigating Memory Failure Prediction Across CPU Architectures2024 54th Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S)10.1109/DSN-S60304.2024.00033(88-95)Online publication date: 24-Jun-2024
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  • (2023)From Missteps to Milestones: A Journey to Practical Fail-Slow DetectionACM Transactions on Storage10.1145/361769019:4(1-28)Online publication date: 1-Nov-2023
  • (2023)Exploring Error Bits for Memory Failure Prediction: An In-Depth Correlative Study2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)10.1109/ICCAD57390.2023.10323692(01-09)Online publication date: 28-Oct-2023
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