muda
by MuGdxy
μ-Cuda, COVER THE LAST MILE OF CUDA. With features: intellisense-friendly, structured launch, automatic cuda graph generation and updating.
AI summary
CUDA framework
A comprehensive CUDA programming framework that provides tools for structured launch and automatic graph generation.
- stars
- 159
- forks
- 8
- watching
- 5
Similar projects
Found by comparing what the projects do, not just their names.
jgbit/vuda869
GPU acceleration framework
Provides a Vulkan-based interface to CUDA's runtime API for GPU-accelerated applications
GPU Clojure Library
Provides Clojure bindings for CUDA programming, enabling GPU-accelerated computation in Clojure applications.
GPU compiler
A toolset that compiles Ada and SPARK code to NVIDIA GPUs
CUDA library wrapper
A dynamic binding to the CUDA library for use in programming languages
Deep learning library
Provides a CUDA backend for the PyTorch deep learning framework
Deep Learning Framework
A framework for deep learning using C++ and modularity to speed up development.
GPU interface
Provides Common Lisp interfaces to NVIDIA CUDA for efficient GPU programming
torch/cunn215
GPU library
A CUDA implementation of neural network modules and related GPU operations
Rx framework
An implementation of the Rx methodology in Ada 2012
Business framework
A framework for building and evolving complex business systems using Domain Driven Design principles
GPU language binding
Enables efficient data exchange and invocation of existing GPU kernels from host languages in the GraalVM
coreylowman/dfdx1.8K
Deep learning library
A deep learning library for Rust with GPU acceleration and ergonomic API.
CUDA API wrappers
A set of unified C++ wrappers for NVIDIA's CUDA execution ecosystem APIs
CC4.0 framework
An open-source implementation of deep learning framework Caffe tailored for the CC4.0 platform
Action recognition framework
An optimized deep learning framework for action recognition tasks
