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── 99129 repos indexed ── | filtered by tag: #sumcheck
spaceandtimefdn/blitzar ★ 4864 159 APPLICATION

Blitzar is a high-performance C++ library for GPU-accelerated cryptographic zero-knowledge proofs, developed by Space and Time. It provides multi-scalar multiplication (MSM), Pedersen commitments, inner product arguments, sumcheck proofs, and sequential commitments over multiple elliptic curves (Curve25519/Ristretto255, BLS12-381, BN254, Grumpkin). The library supports both CPU and CUDA GPU backends, with a stable C API and Rust bindings (blitzar-sys). It is designed for use in Space and Time's Proof of SQL, enabling analytic queries on large datasets with sub-second proof generation. The codebase is well-structured with extensive unit tests, benchmarks, and a Bazel/Nix build system. It incorporates optimized algorithms (Pippenger, bucket methods) and low-level field/curve arithmetic adopted from libsodium and zkcrypto, demonstrating strong engineering craftsmanship in GPU cryptography.

RATING: 8.9/10 MAINT: active DRIFT: low
▸ 5 reusable components found
inference-labs-inc/JSTprove ★ 1319 15 APPLICATION

JSTprove is a production-grade zero-knowledge proof system for verifying ONNX neural network inference. It compiles ML models into arithmetic circuits using the Expander Compiler Collection (ECC) frontend, generates witnesses, and produces proofs via a GKR/sumcheck-based prover with multiple polynomial commitment schemes (KZG, Hyrax, Orion, Basefold, WHIR). The system supports multiple efficient field arithmetics (Mersenne31, BabyBear, Goldilocks, BN254, GF2) with SIMD/AVX/NEON optimizations, and provides hardware acceleration through Metal and CUDA backends. The codebase is organized as a Rust workspace with ~30 crates, offering a CLI (`jstprove`, `jstprove-remainder`), Python bindings via PyO3, and a zkVM guest (Jolt). It is actively maintained by Inference Labs with regular commits, CI/CD pipelines, and e2e tests covering full model pipelines (LeNet, CIFAR CNN, MiniResNet). While primarily an application toolkit, it contains deep cryptographic research contributions in the form of advanced polynomial commitment constructions (sparse WHIR, hyper-bivariate KZG) and circuit optimizations (cross-layer GKR, LogUp range checks). Some hints (e.g., sigmoid, gridsample) carry documented soundness caveats, and the system relies on nightly Rust and platform-specific intrinsics, which may limit portability.

RATING: 8.8/10 MAINT: active DRIFT: low
▸ 6 reusable components found
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