NVIDIA CUDA™ bindings for Node.js
Extension of @node-llama-cpp/linux-x64-cuda - prebuilt binary for node-llama-cpp for Linux x64 with CUDA support
Prebuilt binary for node-llama-cpp for Linux x64 with CUDA support
Extension of @node-llama-cpp/win-x64-cuda - prebuilt binary for node-llama-cpp for Windows x64 with CUDA support
CUDA grammar for tree-sitter
Extension of @realtimex/linux-x64-cuda - prebuilt binary for node-llama-cpp for Linux x64 with CUDA support
Prebuilt binary for node-llama-cpp for Windows x64 with CUDA support
Extension of @realtimex/win-x64-cuda - prebuilt binary for node-llama-cpp for Windows x64 with CUDA support
Native module for An another Node binding of whisper.cpp (linux-x64-cuda)
Prebuilt binary for node-llama-cpp for Windows x64 with CUDA support
Prebuilt binary for node-llama-cpp for Linux x64 with CUDA support
Chunk package for the Windows x64 CUDA fallback backend used by node-llama-cpp (1/6)
Chunk package for the Linux x64 CUDA fallback backend used by node-llama-cpp (1/6)
Chunk package for the Linux x64 CUDA fallback backend used by node-llama-cpp (3/6)
Chunk package for the Linux x64 CUDA fallback backend used by node-llama-cpp (4/6)
Chunk package for the Linux x64 CUDA fallback backend used by node-llama-cpp (5/6)
Chunk package for the Windows x64 CUDA fallback backend used by node-llama-cpp (3/6)
Chunk package for the Linux x64 CUDA fallback backend used by node-llama-cpp (2/6)
Chunk package for the Windows x64 CUDA fallback backend used by node-llama-cpp (2/6)
Chunk package for the Linux x64 CUDA fallback backend used by node-llama-cpp (6/6)
Chunk package for the Windows x64 CUDA fallback backend used by node-llama-cpp (5/6)
Chunk package for the Windows x64 CUDA fallback backend used by node-llama-cpp (4/6)
Native module for An another Node binding of llama.cpp (win32-x64-cuda)
Native module for An another Node binding of llama.cpp (linux-x64-cuda)
CUDA bindings.
GPU acceleration via the actor model. Wraps NVIDIA CUDA libraries (cuBLAS, cuDNN, cuFFT, cuRAND, cuSOLVER, cuSPARSE, cuTENSOR, cuBLASLt, NVRTC, NCCL) as supervised atomr actors with generation-validated buffers and a uniform async surface.
Backend-agnostic compute-acceleration core. Defines the AccelBackend trait, AccelRef<T> typed pointers, AccelError enum, and CompletionStrategy — the abstraction layer that lets atomr-accel-cuda (NVIDIA), and future ROCm / Metal / oneAPI / Vulkan backends plug into the same actor surface.
CUB-backed device-wide reductions, scans, sorts, histograms, and selects, surfaced as an atomr actor compiled per-(op, dtype) via NVRTC against the atomr-accel-cuda Phase 0.6 disk cache.
CUTLASS kernel-template instantiation via NVRTC for atomr-accel. Provides GEMM, grouped GEMM, implicit-GEMM convolution, and EVT (epilogue visitor tree) actors that JIT CUTLASS C++ templates against the per-arch toolchain pinned by atomr-accel-cuda's NvrtcActor.
GPU observability for atomr-accel: NVTX ranges, NVML metrics actor, and CUPTI activity tracing. Implements the KernelTrace hooks exported by atomr-accel-cuda and registers atomr-telemetry probes.
FlashAttention v2 + v3 kernel templates for atomr-accel — fp16/bf16/fp8, causal, varlen, ALiBi, sliding window, sink tokens, MQA/GQA, paged KV-cache, and chunked prefill, dispatched through NVRTC + Phase 0.6 cubin cache.
TensorRT engine builder + runtime as supervised atomr actors. Wraps libnvinfer / libnvonnxparser at runtime (proprietary library, not vendored). ONNX import, INT8/FP8 PTQ calibration, IPluginV3 Rust trampolines, dynamic shapes, refit.
CUDA to Rust transpiler with WebGPU/WASM support
GPU acceleration via the actor model. Wraps NVIDIA CUDA libraries (cuBLAS, cuDNN, cuFFT, cuRAND, cuSOLVER, cuSPARSE, cuTENSOR, cuBLASLt, NVRTC, NCCL) as supervised rakka actors with generation-validated buffers and a uniform async surface.
Backend-agnostic compute-acceleration core. Defines the AccelBackend trait, AccelRef<T> typed pointers, AccelError enum, and CompletionStrategy — the abstraction layer that lets rakka-accel-cuda (NVIDIA), and future ROCm / Metal / oneAPI / Vulkan backends plug into the same actor surface.
A tensor library with GPU support
Apache Arrow CUDA is a common in-memory columnar data store on CUDA. It's useful to share and process large data.
SGC-Ruby-CUDA implements Ruby bindings to Nvidia CUDA SDK. It provides easy access to CUDA-enabled GPU from a Ruby program.
Ruby Adapted CUDA
Neural networks in Ruby and CUDA.
Barracuda is a wrapper library for OpenCL/CUDA GPGPU programming
Barracuda is a wrapper library for OpenCL/CUDA GPGPU programming
Write Ruby extension in C/C++ with NVIDIA CUDA. A simple wrapper command for nvcc and a monkey patch for mkmf.
KappaConfig is a module to give easy access to NVIDIA CUDA from Ruby using the Kappa Library.
Cumo is CUDA aware numerical library whose interface is highly compatible with Ruby Numo.
Ruby gem for running state-of-the-art language models locally. Access LLMs, embeddings, rerankers, and NER models directly from Ruby using Rust-powered Candle with Metal/CUDA acceleration.
Ignis is the foundation of a CUDA-backed deep-learning ecosystem for Ruby that actually targets native Windows. It provides a GPU n-dimensional array (Ignis::NDArray), CUDA memory/device management, a runtime kernel compiler (NVRTC) with a batteries-included kernel library, fp16/bf16 conversion, and cuBLAS GEMM. Kernels are compiled at runtime and libraries are bound via FFI — there are NO C extensions, so installation needs no compiler or devkit (the usual Windows native-gem killer). Requires an NVIDIA GPU + CUDA toolkit/runtime.
simple functinal test tool
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.