Bloom Filter Optimization
Application scenario: In RocksDB, the Bloom filter is used to quickly determine whether a key exists in an SST file.
Technical principle: The native implementation logic is to calculate and check the probe locations one by one. If there are a large number of probe locations, the loop and memory access overheads increase. This feature leverages SVE2's parallel computation capabilities to process hash probe positions in batches instead of generating and checking them one by one. This reduces redundant computation and data accesses, and lowers the CPU overhead of a single filter lookup.
Performance metric: The performance on YCSB workloads A to F is improved by 3% on average.
Parent topic: RocksDB Acceleration Kit