Combining static and dynamic defect-tolerance techniques for nanoscale memory systems

Authors:
Susmit Biswas;Gang Wang;Tzvetan S. Metodi;Ryan Kastner;Frederic T. Chong
Affiliations:
University of California, Santa Barbara, CA;University of California, Santa Barbara, CA;University of California, Davis, CA;University of California, Santa Barbara, CA;University of California, Santa Barbara, CA
Venue:
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Year:
2007

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Abstract

Nanoscale technology promises dramatically increased device density, but also decreased reliability. With bit error rates projected to be as high as 10%, designing a usable nanoscale memory system poses a significant challenge. In particular, we need to bootstrap a sea of unreliable bits into contiguous address ranges which are preferably as large as 4K-byte virtual memory pages. We accomplish this bootstrapping through a combination of dynamic error correction codes within 32-bit blocks and a static defect map which tracks usability of these blocks. The key insight is that statically-determined defect locations can be much more powerful than dynamically correcting for unknown locations, but that defect maps are only practical at a coarse granularity. Using a combination of BCH error correction codes and a Bloom-Filter-based defect map, we achieve a memory efficiency of 60% and 13% for 4K-byte pages at 1% and 10% bit-error rates, respectively.