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Odd-ECC: On-demand DRAM error correcting codes

Alirad Malek (Institutionen för data- och informationsteknik, Datorteknik (Chalmers)) ; Evangelos Vasilakis (Institutionen för data- och informationsteknik, Datorteknik (Chalmers)) ; V. Papaefstathiou ; P. Trancoso ; I. Sourdis
ACM International Conference Proceeding Series Vol. Part F131197 (2017), p. 96-101.
[Konferensbidrag, refereegranskat]

An application may have different sensitivity to faults in different subsets of the data it uses. Some data regions may therefore be more critical than others. Capitalizing on this observation, Odd-ECC provides a mechanism to dynamically select the memory fault tolerance of each allocated page of a program on demand depending on the criticality of the respective data. Odd-ECC error correcting codes (ECCs) are stored in separate physical pages and hidden by the OS as pages unavailable to the user. Still, these ECCs are physically aligned with the data they protect so the memory controller can efficiently access them. Thereby, capacity, performance and energy overheads of memory fault tolerance are proportional to the criticality of the data stored. Odd-ECC is applied to memory systems that use conventional 2D DRAM DIMMs as well as to 3D-stacked DRAMs and evaluated using various applications. Compared to flat memory protection schemes, Odd-ECC substantially reduces ECCs capacity overheads while achieving the same Mean Time to Failure (MTTF) and in addition it slightly improves performance and energy costs. Under the same capacity constraints, Odd-ECC achieves substantially higher MTTF, compared to a flat memory protection. This comes at a performance and energy cost, which is however still a fraction of the cost introduced by a flat equally strong scheme.

Nyckelord: 3D-Stacked memory , Applications reliability analysis , DRAM , Error correcting codes , Main memory reliability

Denna post skapades 2017-12-22.
CPL Pubid: 254025


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Institutioner (Chalmers)

Institutionen för data- och informationsteknik, Datorteknik (Chalmers)


Data- och informationsvetenskap

Chalmers infrastruktur