实验室论文被IEEE TCAD录用

发布者:邓玉辉发布时间:2025-11-24浏览次数:10

实验室硕士生张来福撰写的论文《 AGCB: Adaptive Garbage Collection for Enhancing Lifetime and Performance of Bit-Alterable Flash Memory》被《  IEEE Transactions on Computer-Aided Design of Integrated Circuits and  Systems》录用。 IEEE Transactions on Computer-Aided Design of Integrated  Circuits and Systems为CCF 推荐A类国际期刊。论文将于2024年正式发表。


Abstract—Bit-alterable flash-based SSDs, offering page-level erase operation, allows individual flash pages in a block to be erased independently. The page-level erase operation alleviates the overhead of page migration during garbage collection and improves the SSD lifetime. However, when the number of invalid pages within a block exceeds a certain threshold, the latency of page-level garbage collections using page-level erase may exceed that of block-level garbage collections. In bit-alterable flash memory, existing garbage collection strategies dynamically choose between page-level and block-level garbage collections based on their latency. This often fails to fully exploit the advantage of page-level garbage collection in reducing write amplification under low-load conditions.To address this limitation, we propose an adaptive garbage collection strategy called AGCB to dynamically adjust garbage collection operations by the runtime workload of flash channels, thereby enhancing SSD performance and lifetime. Specifically, AGCB classifies flash channels as busy or idle by monitoring the depth of the transaction queue in cache. According to this classification, AGCB selectively applies page-level or block-level garbage collection operations, aiming to minimize the impact of garbage collections with host I/O requests. Meanwhile, we introduce a staged victim block selection scheme to further improve garbage collection efficiency and wear leveling. The experimental results unveil that compared with the existing schemes, AGCB reduces the number of garbage collection operations, average response time, and blocked user requests by an average of 14.6%, 14.7%, and 17.3%, respectively.