Hey everyone,
I've been working on an open-source secp256k1 elliptic curve library focused on
raw throughput across heterogeneous hardware. Sharing it here for feedback.
## What is it?
A zero-dependency C++20 secp256k1 library with GPU acceleration (CUDA, OpenCL,
Metal, ROCm) and support for 12+ platforms including embedded (ESP32, STM32).
## GPU Numbers (RTX 5060 Ti, kernel-level)
| Operation | Throughput | Time/Op |
|-----------|-----------|---------|
| ECDSA Sign (RFC 6979) | **4.88 M/s** | 204.8 ns |
| ECDSA Verify (Shamir+GLV) | **2.44 M/s** | 410.1 ns |
| Schnorr Sign (BIP-340) | **3.66 M/s** | 273.4 ns |
| Schnorr Verify (BIP-340) | **2.82 M/s** | 354.6 ns |
| Field Multiplication | **4,142 M/s** | 0.2 ns |
## What makes it different?
- **Zero dependencies** — no Boost, no OpenSSL. Pure C++20.
- **4 GPU backends** — CUDA, OpenCL, Metal, ROCm. Only open-source lib
doing full ECDSA+Schnorr sign/verify on GPU.
- **Dual security model** — FAST path (variable-time, max throughput) +
CT path (constant-time, no secret-dependent branches). Both always compiled in.
- **12+ platforms** — x86-64, ARM64, RISC-V, WASM, iOS, Android, ESP32-S3,
ESP32, STM32, plus GPU backends.
- **Stable C ABI** (`ufsecp`) with 45 functions — bindings for C#, Python,
Go, Rust, Java, Node.js, Dart, PHP, Ruby, Swift, React Native.
- **Full protocol suite** — ECDSA, Schnorr/BIP-340, ECDH, BIP-32/44,
MuSig2, Taproot, FROST (t-of-n threshold), Pedersen commitments,
adaptor signatures, batch verification.
- **5×52 field repr** with `__int128` lazy reduction — 2.76× faster than 4×64.
- **ESP32-S3** does scalar×G in 2.5ms — viable for IoT signing.
## Packages
Available on npm (`ufsecp`, `react-native-ufsecp`), NuGet, RubyGems, Maven,
plus downloadable archives for Python, Go, Rust, Dart, PHP, Swift, C/C++ headers.
## Important caveat
**This is a research project. It has NOT been independently audited.**
For production systems, use [bitcoin-core/secp256k1](https://github.com/bitcoin-core/secp256k1).
If you need maximum throughput on GPU/embedded/multi-platform and understand the
risks, this might be interesting.
## Links
- **GitHub**: https://github.com/shrec/UltrafastSecp256k1
- **License**: AGPL-3.0
- **Benchmarks**: https://github.com/shrec/UltrafastSecp256k1/blob/main/docs/BENCHMARKS.md
- **API Reference**: https://github.com/shrec/UltrafastSecp256k1/blob/main/docs/API_REFERENCE.md
Happy to answer any questions about the implementation, architecture decisions,
or GPU kernel design.
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