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DAC2023Top-tier venue

HUNTER: Releasing Persistent Memory Write Performance with A Novel PM-DRAM Collaboration Architecture

Yanqi Pan, Yifeng Zhang, Wen Xia, Xiangyu Zou, Cai Deng

2023Year
1Citations
1Top-tier citations

Abstract

We present HUNTER, a POSIX-compliant persistent memory (PM) file system that fully releases PM’s write performance. Compared to state-of-the-art ones, HUNTER proposes a novel PM-DRAM collaboration architecture to significantly eliminate/reduce software overheads in the write path. Expensive in-PM metadata are updated asynchronously to hide their performance penalties. Furthermore, in-PM metadata/data are laid out separately for locality awareness, enabling collaboration with asynchronous architecture. HUNTER also adopts several lightweight in-DRAM allocators/indexes to manage PM efficiently.Experimental results suggest that HUNTER achieves 2.0–3.4× write bandwidth compared to state-of-the-art PM file systems in write-intensive workloads and shows similar write bandwidth compared to bare PM.

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