How I accidently created the fastest CSV parser ever made
7 hours ago
- #simd
- #csv-parsing
- #performance
- The project started as a fun experiment to create an extremely fast CSV parser using branchless programming and SIMD (Single Instruction, Multiple Data) techniques.
- Traditional CSV parsers are slow due to branch mispredictions, cache misses, and single-byte processing, which modern CPUs with SIMD capabilities can overcome.
- The parser leverages AVX-512, Intel's 512-bit wide SIMD instruction set, to process 64 characters in parallel, drastically improving performance.
- Memory optimization techniques like memory-mapped files (mmap) and huge pages (MADV_HUGEPAGE) reduce overhead and improve throughput.
- Benchmarks show the parser outperforms existing solutions, achieving speeds up to 60.80 MB/s in Node.js bindings and handling 1TB of data in ~10 minutes.
- The project highlights the importance of understanding CPU architecture, cache locality, and memory access patterns for high-performance computing.
- The parser is available as an open-source project on GitHub and an npm package, offering both synchronous and streaming APIs for different use cases.
- Future applications of these techniques extend beyond CSV parsing to other data-intensive tasks requiring high throughput.