Topics / #gpgpu

Gpgpu projects on GitHub

General-purpose computing on GPUs for parallel workloads like hashing.

As of , the most-starred Gpgpu projects on GitHub are hashcat (27K stars), gpu.js (15.5K stars) and john (13.8K stars). GitHub.Locker tracks 7 Gpgpu repositories with 77.4K stars combined. The fastest-growing on October 16 was hashcat, with +8 stars in a day.

7Projects
77.4KStars in total
+20Stars in a day

Hot right now

Most stars gained in a day · Oct 16

The all-time top

7 projects · by stars

  1. #1 · hashcat/hashcat

    hashcat

    hashcat is a highly optimized password recovery platform: you feed it password hashes and it recovers the passwords behind them, billed as the world's fastest password cracker.

    27K
  2. #2 · gpujs/gpu.js

    gpu.js

    GPU.js is a JavaScript library that takes the functions you write and runs them on your GPU as shaders instead of on the CPU — a big speedup for parallel math like matrix multiplication.

    15.5K
  3. #3 · openwall/john

    john

    A fast, offline password cracker. Its primary purpose is detecting weak Unix passwords, but the jumbo build supports hundreds of hash and cipher types and runs on Unix, macOS, Windows and more.

    13.8K
  1. 4

    taskflow

    12.2Ktaskflow/taskflow · C++

    Taskflow is a C++ library that helps you write high-performance task-parallel programs with high programming productivity, letting you build and run graphs of dependent tasks across CPU threads and GPUs.

  2. 5

    turbo-fieldfare

    6.9Kdrumih/turbo-fieldfare · Swift

    TurboFieldfare is a custom Swift and Metal runtime that runs the instruction-tuned Gemma 4 26B-A4B model on Apple Silicon Macs using only about 2 GB of RAM, even on 8 GB machines, by streaming only the experts needed for each token from SSD instead of loading the full 14.3 GB model.

  3. 6

    NoGraphicsAPI

    1.6Ksebbbi/NoGraphicsAPI · C++

    NoGraphicsAPI is an experimental Vulkan 1.4 implementation of Sebastian Aaltonen's 'No Graphics API' idea, exploring what disappears from a conventional graphics API when shaders use raw 64-bit GPU pointers instead of buffer objects and bindings.

  4. 7

    CUDA-for-AMD-Windows

    321Speedstu/CUDA-for-AMD-Windows · Python

    A Windows compatibility stack that runs CUDA-targeted applications on AMD GPUs via ZLUDA plus AMD ROCm/HIP, with tooling to verify the work truly executes on the GPU instead of silently falling back to CPU or producing wrong results.

Often tagged together