cuSBF – faster Bloom filter on GPUs for DNA sequences
92× faster insert and 234× faster query than CPU Super Bloom on GPU.
High-Performance GPU Super Bloom Filter
92× faster than CPU Super Bloom with minimizer-based shard selection.
Bioinformatics researchers, computational biologists working with genome sequences
cuCollections GBBF · GPU Cuckoo Filter · Counting Quotient Filter
92× faster insert and 234× faster query than CPU Super Bloom on GPU.
350x faster GPU Bloom filter with academic paper backing the performance claims.
First GPU-accelerated poker solver, free when PioSolver costs hundreds.
50x faster than PaddleOCR Python with real TensorRT benchmarks on RTX 5090.
This reads like a GPU engineer's field notes — one ~3,400-line CUDA file implements a full per-thread crypto pipeline (key gen → EC multiply → SHA-256 → RIPEMD-160) and a two-stage bloom+binary-search matcher to check ~3,100 targets at ~100M keys per batch. The article digs into concrete low-level choices (LUT layout, memory hierarchy, __ldg reads, atomicCAS reporting, and per-mode keygen strategies), which is rare in public writeups; downside is it's closed-source and the dual-use/ethical implications should be called out more explicitly.
CUDA pipeline hits 60 FPS on 45MP RAW files, competing with Darktable.