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Log-Structured-Merge (LSM) tree-based key value stores are facing criticalchallenges of fully leveraging the dramatic performance improvements of theunderlying storage devices, which makes the compaction operations of LSM keyvalue stores become CPU-bound, and slow compactions significantly degrade keyvalue store performance. To address this issue, we propose LUDA, an LSM keyvalue store with CUDA, which uses a GPU to accelerate compaction operations ofLSM key value stores. How to efficiently parallelize compaction procedures aswell as accommodate the optimal performance contract of the GPU architecturechallenge LUDA. Specifically, LUDA overcomes these challenges by exploiting thedata independence between compaction procedures and using cooperative sortmechanism and judicious data movements. Running on a commodity GPU underdifferent levels of CPU overhead, evaluation results show that LUDA provides upto 2x higher throughput and 2x data processing speed, and achieves more stable99th percentile latencies than LevelDB and RocksDB.

LUDA: Boost LSM Key Value Store Compactions with GPUs