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bellperson Crates.io

This is a fork of the great bellman library.

bellman is a crate for building zk-SNARK circuits. It provides circuit traits and primitive structures, as well as basic gadget implementations such as booleans and number abstractions.

Backend

There is currently one backend available for the implementation of Bls12 381:

  • blstrs - optimized with hand tuned assembly, using blst

GPU

This fork contains GPU parallel acceleration to the FFT and Multiexponentation algorithms in the groth16 prover codebase under the compilation features cuda and opencl.

Requirements

  • NVIDIA or AMD GPU Graphics Driver
  • OpenCL

( For AMD devices we recommend ROCm )

Environment variables

The gpu extension contains some env vars that may be set externally to this library.

  • BELLMAN_NO_GPU

    Will disable the GPU feature from the library and force usage of the CPU.

    // Example
env::set_var("BELLMAN_NO_GPU", "1");

  • BELLMAN_VERIFIER

    Chooses the device in which the batched verifier is going to run. Can be cpu, gpu or auto.

    Example
env::set_var("BELLMAN_VERIFIER", "gpu");

  • BELLMAN_CUSTOM_GPU

    Will allow for adding a GPU not in the tested list. This requires researching the name of the GPU device and the number of cores in the format ["name:cores"].

    // Example
env::set_var("BELLMAN_CUSTOM_GPU", "GeForce RTX 2080 Ti:4352, GeForce GTX 1060:1280");

  • BELLMAN_CPU_UTILIZATION

    Can be set in the interval [0,1] to designate a proportion of the multiexponenation calculation to be moved to cpu in parallel to the GPU to keep all hardware occupied.

    // Example
env::set_var("BELLMAN_CPU_UTILIZATION", "0.5");

  • RAYON_NUM_THREADS

    Restricts the number of threads used in the library to roughly twice that number (best effort). In the past this was done using BELLMAN_NUM_CPUS which is now deprecated. The default is set to the number of logical cores reported on the machine.

     // Example
 env::set_var("RAYON_NUM_THREADS", "6");

  • BELLMAN_GPU_FRAMEWORK

    Bellman can be compiled with both, OpenCL and CUDA support. When both are available, BELLMAN_GPU_FRAMEWORK can be used to set it to a specific one, either cuda or opencl.

    // Example
env::set_var("BELLMAN_GPU_FRAMEWORK", "opencl");

  • BELLMAN_CUDA_NVCC_ARGS

    By default the CUDA kernel is compiled for several architectures, which may take a long time. BELLMAN_CUDA_NVCC_ARGS can be used to override those arguments. The input and output file will still be automatically set.

    // Example for compiling the kernel for only the Turing architecture
env::set_var("BELLMAN_CUDA_NVCC_ARGS", "--fatbin --gpu-architecture=sm_75 --generate-code=arch=compute_75,code=sm_75");

Supported / Tested Cards

Depending on the size of the proof being passed to the gpu for work, certain cards will not be able to allocate enough memory to either the FFT or Multiexp kernel. Below are a list of devices that work for small sets. In the future we will add the cuttoff point at which a given card will not be able to allocate enough memory to utilize the GPU.

Device Name Cores Comments
Quadro RTX 6000 4608
TITAN RTX 4608
Tesla V100 5120
Tesla P100 3584
Tesla T4 2560
Quadro M5000 2048
GeForce RTX 3090 10496
GeForce RTX 3080 8704
GeForce RTX 3070 5888
GeForce RTX 2080 Ti 4352
GeForce RTX 2080 SUPER 3072
GeForce RTX 2080 2944
GeForce RTX 2070 SUPER 2560
GeForce GTX 1080 Ti 3584
GeForce GTX 1080 2560
GeForce GTX 2060 1920
GeForce GTX 1660 Ti 1536
GeForce GTX 1060 1280
GeForce GTX 1650 SUPER 1280
GeForce GTX 1650 896
gfx1010 2560 AMD RX 5700 XT
gfx906 7400 AMD RADEON VII
------------------------ ------- ----------------

Running Tests

RUSTFLAGS="-C target-cpu=native" cargo test --release --all

To run using CUDA and OpenCL, you can use:

RUSTFLAGS="-C target-cpu=native" cargo test --release --all --features cuda,opencl

To run the multiexp_consistency test you can use:

RUST_LOG=info cargo test --features cuda,opencl -- --exact multiexp::gpu_multiexp_consistency --nocapture

Considerations

Bellperson uses rust-gpu-tools as its CUDA/OpenCL backend, therefore you may see a directory named ~/.rust-gpu-tools in your home folder, which contains the compiled binaries of OpenCL kernels used in this repository.

License

Licensed under either of

at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.