The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Poster Type: Research Posters
Author: Darren Ng (University of California, Merced), Duo Zhang (University of California, Merced), Sheng Di (Argonne National Laboratory (ANL)), Zhaorui Zhang (The Hong Kong Polytechnic University), Xiaoyi Lu (University of California, Merced)
Supervisor:
Abstract: Lossy compression is widely used to reduce storage costs and I/O demands, especially on SCSI-HDDs. However, its benefits diminish on NVMe-SSDs, where compression and decompression runtimes often exceed raw I/O speed. To address this, we conduct a detailed study of compression runtimes, control methods, and NVMe parameters. We find that existing error-bounded methods fail to optimize compression ratios, and serial pipelines remain inefficient. With the low-level NVMe driver SPDK, we take a systematic approach to evaluating the limitations within implementing lossy-compressed I/O for NVMe-SSDs and expose numerous observations towards motivating our design.
Best Poster Finalist (BP): no
Poster: PDF
Poster Summary: PDF