Data-Dependent Sparing to Manage Better-Than-Bad Blocks

Rakan Maddah, Sangyeun Cho and Rami Melhem.

Proceedings of the Non-Volatile Memories Workshop (NVMW), San Diego, California, March 2013.

Abstract:

We forecast that bad block management will remain critical for future systems built with advanced and emerging memory technologies. We argue that the conventional block retirement and sparing approach---a block is retired as soon as it shows faulty behavior---is overly conservative. We observe that it is highly unlikely that all faulty bits in a block manifest errors. Consequently, we propose data dependent sparing, a relaxed block retirement and sparing approach that recycles faulty storage blocks.