osobhandClaude Opus 5.5
78c769f179
A full read of a contiguous dataset is one memcpy from the mapped file, yet ran at a quarter of h5py's speed on one thread: the fresh output Vec took a page fault and a kernel page clear for every 4 KiB page written, 16384 per 64 MiB, costing several times the copy (the benchmark spent 6.2 s of 8 s in the kernel, 4.3M minor faults). numpy, so h5py, madvises MADV_HUGEPAGE on allocations of 4 MiB or more; the typed readers' output, the raw contiguous read and the chunk assembly buffer now do the same (Linux only, libc as a Linux-only dependency; no-op otherwise). New h5py comparison tests cover full and selection reads of contiguous data for every 1-8-byte integer and float type, both byte orders, ranks 1-4, empty selections, and datasets past the 4 MiB threshold. Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
clawhdf5-format
Pure-Rust HDF5 binary format parsing and writing — no C dependencies.
Features
- Zero-copy superblock, object header, and B-tree parsing
- Chunked dataset read/write with filter pipelines
no_stdsupport (disablestdfeature)- Optional parallel reads via Rayon
- SHA-256 provenance tracking
Usage
use clawhdf5_format::Superblock;
let data = std::fs::read("data.h5").unwrap();
let sb = Superblock::from_bytes(&data).unwrap();
println!("HDF5 version {}.{}", sb.version_major(), sb.version_minor());
License
MIT