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arXiv · 2306.16037

Retrospective: An Experimental Study of Data Retention Behavior in Modern DRAM Devices: Implications for Retention Time Profiling Mechanisms

Abstract

Our ISCA 2013 paper provides a fundamental empirical understanding of two major factors that make it very difficult to determine the minimum data retention time of a DRAM cell, based on the first comprehensive experimental characterization of retention time behavior of a large number of modern commodity DRAM chips from 5 major vendors. We study the prevalence, effects, and technology scaling characteristics of two significant phenomena: 1) data pattern dependence (DPD), where the minimum retention time of a DRAM cell is affected by data stored in other DRAM cells, and 2) variable retention time (VRT), where the minimum retention time of a DRAM cell changes unpredictably over time. To this end, we built a flexible FPGA-based testing infrastructure to test DRAM chips, which has enabled a large amount of further experimental research in DRAM. Our ISCA 2013 paper's results using this infrastructure clearly demonstrate that DPD and VRT phenomena are significant issues that must be addressed for correct operation in DRAM-based systems and their effects are getting worse as DRAM scales to smaller technology node sizes. Our work also provides ideas on how to accurately identify data retention times in the presence of DPD and VRT, e.g., online profiling with error correcting codes, which later works examined and enabled. Most modern DRAM chips now incorporate ECC, especially to account for VRT effects. This short retrospective provides a brief analysis of our ISCA 2013 paper and its impact. We describe why we did the work, what we found and its implications, what the findings as well as the infrastructure we built to discover them have enabled in later works, and our thoughts on what the future may bring.

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BibTeXRIS

Onur Mutlu. 2023-06-28. Retrospective: An Experimental Study of Data Retention Behavior in Modern DRAM Devices: Implications for Retention Time Profiling Mechanisms. https://arxiv.org/abs/2306.16037

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