VulkanTutorial is a comprehensive educational guide and instructional resource for implementing low-level rendering and compute pipelines using the Vulkan API. It serves as a GPU programming course and a step-by-step guide for building high-performance graphics applications from scratch. The project provides detailed instruction on the full graphics pipeline, including the compilation of shaders to SPIR-V bytecode, the configuration of rasterization states, and the implementation of 3D graphics pipelines. It also covers general-purpose GPU compute programming, focusing on the execution of par
This project provides a comprehensive toolset for WebGPU, serving as a graphics API wrapper, compute shader framework, resource manager, and shader toolchain. It enables browser-based GPU acceleration by offloading memory-intensive tasks and data processing from the CPU to the GPU. The framework manages the full lifecycle of GPU operations, from requesting physical hardware adapters and initializing logical devices to configuring programmable render and compute pipelines. It specifically supports the coordination of parallel workgroups and collective subgroup operations for general-purpose co
IREE is an MLIR-based compiler toolchain and runtime designed to translate machine learning models from various frameworks into optimized binaries for execution across diverse hardware targets. It provides a unified pipeline to ingest models from PyTorch, TensorFlow, JAX, and ONNX, lowering them into a common intermediate representation for deployment on CPUs, GPUs, and bare-metal embedded systems. The project distinguishes itself through a bytecode virtual machine and a hardware abstraction layer that decouple high-level model logic from specific hardware instruction sets. It supports sophis
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
gpu.cpp ist eine leichtgewichtige C++-Bibliothek zur Ausführung von Low-Level-General-Purpose-GPU-Berechnungen über verschiedene Hardwareanbieter und Betriebssysteme hinweg. Sie fungiert als portabler GPU-Wrapper, Kernel-Orchestrator und Tensor-Managementsystem unter Verwendung der WebGPU-Spezifikation, um Geräteinitialisierung, Pufferübertragungen und Compute-Shader-Dispatching zu abstrahieren.
The main features of answerdotai/gpu.cpp are: WebGPU Implementations, GPU Hardware Abstraction Layers, Compute Shader Programming, Tensor Lifecycle Management, GPU Compute Frameworks, GPU Resource Management, Compute Shader Dispatchers, Tensor Memory Lifetime Management.
Open-source alternatives to answerdotai/gpu.cpp include: overv/vulkantutorial — VulkanTutorial is a comprehensive educational guide and instructional resource for implementing low-level rendering… gpuweb/gpuweb — This project provides a comprehensive toolset for WebGPU, serving as a graphics API wrapper, compute shader framework,… iree-org/iree — IREE is an MLIR-based compiler toolchain and runtime designed to translate machine learning models from various… nvidia/cuda-samples — This repository is a collection of reference implementations and programming examples for the CUDA Toolkit. It serves… gfx-rs/gfx — gfx is a hardware-agnostic graphics API abstraction that translates a unified set of graphics and compute commands… gfx-rs/wgpu — This project is a cross-platform graphics and compute framework that provides a unified, hardware-agnostic abstraction…
