StringZilla 🦖

Strings are the first fundamental data type every programming language implements in software rather than hardware, so dedicated CPU instructions are rare - and the few that exist are hardly ideal. That's why most languages lean on the C standard library (libc) for their string operations, which, despite its name, ships its hottest code in hand-tuned assembly. It does exploit SIMD, but it isn't perfect. 1️⃣ Even on ubiquitous hardware - over a billion 64-bit ARM CPUs - routines such as strstr and memmem top out at roughly one-third of available throughput. 2️⃣ SIMD coverage is uneven: fast forward scans don't guarantee speedy reverse searches, hashing and case-mapping is not even part of the standard. 3️⃣ Many higher-level languages can't rely on libc at all because their strings aren't NUL-terminated - or may even contain embedded zeroes. That's why StringZilla exists: predictable, high performance on every modern platform, OS, and programming language.

StringZilla is the GodZilla of string libraries, using SIMD and SWAR to accelerate binary and UTF-8 string operations on modern CPUs and GPUs. It delivers up to 10x higher CPU throughput in C, C++, Rust, Python, and other languages, and can be 100x faster than existing GPU kernels, covering a broad range of functionality. It accelerates exact and fuzzy string matching, hashing, edit distance computations, sorting, provides allocation-free lazily-evaluated smart-iterators, and even random-string generators.

• 🐂 C: Upgrade LibC's <string.h> to <stringzilla/stringzilla.h> in C 99
• 🐉 C++: Upgrade STL's <string> to <stringzilla/stringzilla.hpp> in C++ 11
• 🧮 CUDA: Process in-bulk with <stringzillas/stringzillas.cuh> in CUDA C++ 17
• 🐍 Python: Upgrade your str to faster Str
• 🦀 Rust: Use the StringZilla traits crate
• 🦫 Go: Use the StringZilla cGo module
• 🍎 Swift: Use the String+StringZilla extension
• 🟨 JavaScript: Use the StringZilla library
• 🐚 Shell: Accelerate common CLI tools with sz- prefix
• 📚 Researcher? Jump to Algorithms & Design Decisions
• 💡 Thinking to contribute? Look for "good first issues"
• 🤝 And check the guide to set up the environment
• Want more bindings or features? Let me know!

Who is this for?

• For data-engineers parsing large datasets, like the CommonCrawl, RedPajama, or LAION.
• For software engineers optimizing strings in their apps and services.
• For bioinformaticians and search engineers looking for edit-distances for USearch.
• For DBMS devs, optimizing LIKE, ORDER BY, and GROUP BY operations.
• For hardware designers, needing a SWAR baseline for string-processing functionality.
• For students studying SIMD/SWAR applications to non-data-parallel operations.

Performance