GSSA: A Resource Allocation Scheme Customized for 3D NAND SSDs

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dc.contributor.authorLiu, Chun-Yiko
dc.contributor.authorLee, Yunjuko
dc.contributor.authorChoi, Wonilko
dc.contributor.authorJung, Myoungsooko
dc.contributor.authorKandemir, Mahmut Taylanko
dc.contributor.authorDas, Chitako
dc.identifier.citation27th Annual IEEE International Symposium on High Performance Computer Architecture, HPCA 2021, pp.426 - 439-
dc.description.abstractThe high density of 3D NAND-based SSDs comes with longer write latencies due to the increasing program complexity. To address this write performance degradation issue, NAND flash manufacturers implement a 3D NAND-specific full-sequence program (FSP) operation. The FSP can program multiple-bit information into a cell simultaneously with the same latency as the baseline program operation, thereby dramatically boosting the write performance. However, directly adopting the (large granularity) FSP operation in SSD firmware can result in a lifetime degradation problem, where small writes are amplified to large granularities with a significant fraction of empty data. This problem cannot completely be mitigated by the DRAM buffer in the SSDs since the 'sync' commands from the host prevent the DRAM buffer from accumulating enough written data. To solve this FSP-induced performance/lifetime dilemma, in this work, we propose and evaluate GSSA (Generalized and Specialized Scramble Allocation), a novel written-data allocation scheme in SSD firmware, which considers both various 3D NAND program operations and the internal 3D NAND flash architecture. By adopting GSSA, SSDs can enjoy the performance benefits brought by the FSP without excessively consuming the lifetime. Our experimental evaluations reveal that GSSA can achieve the throughput and the spent-lifetime of the best-performance and best-lifetime single granularity schemes, respectively.-
dc.publisherIEEE Computer Society-
dc.titleGSSA: A Resource Allocation Scheme Customized for 3D NAND SSDs-
dc.citation.publicationname27th Annual IEEE International Symposium on High Performance Computer Architecture, HPCA 2021-
dc.contributor.localauthorJung, Myoungsoo-
dc.contributor.nonIdAuthorLiu, Chun-Yi-
dc.contributor.nonIdAuthorLee, Yunju-
dc.contributor.nonIdAuthorChoi, Wonil-
dc.contributor.nonIdAuthorKandemir, Mahmut Taylan-
dc.contributor.nonIdAuthorDas, Chita-
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EE-Conference Papers(학술회의논문)
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