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Rust-GPU/rust-cuda

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5,245 स्टार्स·237 फोर्क्स·Rust·Apache-2.0·5 व्यूज़

Rust Cuda

rust-cuda is a GPU programming framework and device compiler that allows for the development and execution of high-performance kernels on NVIDIA hardware using Rust. It provides a driver wrapper to manage device memory allocation and kernel launching, effectively serving as a system for writing GPU compute logic without relying on C++.

The project includes a compute library with hardware-optimized primitives for neural network acceleration and hardware-accelerated raytracing. It utilizes a compilation toolchain that translates source code into a low-level intermediate representation for execution on graphics processors.

The framework covers device resource management, kernel development, and the simulation of high-precision integer operations. It also supports device-side random number generation and target-specific compute optimizations.

Pre-configured container images are available to simplify the provisioning of the compiler toolchain and development environment across different hardware architectures.

Features

  • GPU Compilers - Provides a complete toolchain that translates Rust source code into optimized NVIDIA GPU hardware instructions.
  • GPU Kernel Programming - Provides a framework for writing and executing high-performance GPU kernels using Rust.
  • Compute Libraries - Ships a compute library with hardware-optimized primitives for neural networks and raytracing.
  • GPU Resource Management - Implements a high-level driver interface to manage the lifecycle and allocation of GPU buffers and kernels.
  • CUDA Driver Wrappers - Provides a programmatic abstraction for controlling NVIDIA GPU device memory and kernel execution.
  • GPU Kernel Development - Provides a framework for managing thread indices and memory allocation to create device-side logic.
  • CUDA Kernel Compilers - Compiles GPU source code into target-specific CUDA kernels with a Rust interface.
  • GPU Compute Toolchains - Provides an integrated development environment and compiler for writing high-performance Rust compute kernels.
  • Intermediate Representations - Compiles Rust source code into a PTX-based intermediate representation for GPU execution.
  • CUDA Accelerated Neural Networks - Implements hardware-optimized primitives to accelerate deep learning workloads on NVIDIA GPUs.
  • GPU Kernel Primitives - Provides highly tuned GPU kernels for standard deep learning operations tuned for tensor cores.
  • Raytracing Primitives - Interfaces directly with specialized GPU circuits to compute light paths and perform image denoising.
  • Raytracing Simulations - Uses specialized GPU circuits to implement physical light transport and path tracing simulations.
  • Real-Time Raytracing - Implements real-time raytracing techniques using specialized hardware circuits for physical light transport.
  • Hardware Driver API Mappings - Provides mappings that link high-level programmatic calls to native NVIDIA hardware driver and runtime APIs.
  • Binary Instruction Execution - Executes low-level binary instructions on graphics hardware using a specialized intermediate representation.
  • Compilation Target Specifications - Defines specific hardware compute capabilities during compilation to optimize machine code for target versions.
  • Hardware-Targeted Compilation - Configures compilation rules to optimize binaries for specific GPU hardware revisions and architectures.

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Rust Cuda को शामिल करने वाली क्यूरेटेड खोजें

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Rust Cuda के ओपन-सोर्स विकल्प

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    This repository is a collection of reference implementations and programming examples for the CUDA Toolkit. It serves as a GPGPU implementation guide and a parallel computing reference, providing code for using graphics hardware to perform general-purpose calculations and high-performance parallel processing. The project provides specific samples for GPU kernel development and resource management. These include demonstrations of multi-GPU communication, peer-to-peer memory access, and system hardware inspection to coordinate distributed GPU resources. The codebase covers a wide range of capa

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Rust Cuda के सभी 30 विकल्प देखें→

अक्सर पूछे जाने वाले प्रश्न

rust-gpu/rust-cuda क्या करता है?

rust-cuda is a GPU programming framework and device compiler that allows for the development and execution of high-performance kernels on NVIDIA hardware using Rust. It provides a driver wrapper to manage device memory allocation and kernel launching, effectively serving as a system for writing GPU compute logic without relying on C++.

rust-gpu/rust-cuda की मुख्य विशेषताएं क्या हैं?

rust-gpu/rust-cuda की मुख्य विशेषताएं हैं: GPU Compilers, GPU Kernel Programming, Compute Libraries, GPU Resource Management, CUDA Driver Wrappers, GPU Kernel Development, CUDA Kernel Compilers, GPU Compute Toolchains।

rust-gpu/rust-cuda के कुछ ओपन-सोर्स विकल्प क्या हैं?

rust-gpu/rust-cuda के ओपन-सोर्स विकल्पों में शामिल हैं: nvidia/cuda-python — cuda-python provides low-level Python bindings for the CUDA Driver and Runtime APIs. It serves as a programmatic… answerdotai/gpu.cpp — gpu.cpp is a lightweight C++ library for executing low-level general-purpose GPU computation across different hardware… z-libs/zen-c — Zen-C is a multi-target systems language and source-to-source compiler that translates high-level logic into… nvidia/cuda-samples — This repository is a collection of reference implementations and programming examples for the CUDA Toolkit. It serves… microsoft/directx-graphics-samples — This project is a collection of reference implementations and technical guides for building high-performance 3D… vladmandic/sdnext — SD.Next is an all-in-one web interface and multi-backend inference engine for generating, editing, and processing…