Projects sharing features with Cuda Rust

The Rust Programming Language Book is the official technical guide and educational resource for the Rust language. It provides a comprehensive walkthrough of the language's design, focusing on its core identity as a systems programming language that enforces memory safety and high-performance execution without the need for a garbage collector. The project is distinguished by its focus on ownership, borrowing, and lifetime tracking, which allow the compiler to verify memory safety and thread safety at compile time. It covers the language's unique approach to zero-cost abstractions, including t

gpu.cpp is a lightweight C++ library for executing low-level general-purpose GPU computation across different hardware vendors and operating systems. It functions as a portable GPU wrapper, kernel orchestrator, and tensor management system using the WebGPU specification to abstract device initialization, buffer transfers, and compute shader dispatching. The library provides a framework for defining compute kernels from shader code and managing their asynchronous dispatch and synchronization. It enables the execution of cross-platform compute shaders and the orchestration of GPU tasks through

This repository holds the lecture materials for Stanford's CS336 course on building language models from scratch. It consists of lecture scripts written as executable Python programs, along with supporting diagrams and images. The course works from the premise that fundamental research requires understanding the full technology stack, rather than only prompting finished models. The lectures cover several areas: GPU performance engineering, including hardware architecture, custom kernels, profiling, and arithmetic intensity; efficient inference, including quantization, KV cache reduction, spec

jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU hardware. Its primary purpose is to enable real-time computer vision and AI inference at the edge with low latency and high throughput. The project distinguishes itself through high-performance streaming analytics and the ability to execute concurrent AI pipelines on auto-grade silicon. It provides specialized support for multi-sensor stream processing, utilizing zero-copy data transport to load camera frames directly into GPU memory. The codebase covers a broad surface of capabiliti

CUDA.jl provides a programming interface for executing custom kernels and performing parallel array computing directly on NVIDIA graphics hardware using the Julia language. It serves as a framework for compiling and scheduling user-defined functions across multiple processing cores, enabling high-performance data processing and task synchronization. The library distinguishes itself through a custom compiler backend that translates high-level language functions into hardware-specific machine code. It manages complex hardware interactions through asynchronous stream scheduling, unified memory m

Zen-C is a multi-target systems language and source-to-source compiler that translates high-level logic into human-readable GNU C or C11 code. It functions as a JIT-enabled programming language with an in-process compiler for real-time interactive code evaluation and testing. The project serves as a CUDA GPU kernel generator, mapping specialized syntax to CUDA C++ using device attributes to target graphics hardware. It acts as an interoperability layer capable of emitting compatible code for C++, Objective-C, and Lisp to bridge native system frameworks and libraries. The language includes an

Scala Native is an ahead-of-time compiler that transforms Scala source code into standalone native binaries for direct execution on hardware. It provides a native binary toolchain designed to eliminate virtual machine warm-up times and ensure instant startup by compiling code into optimized executables. The project features a C interoperability interface and foreign function interface that map native C headers to language objects, allowing for the direct execution of external libraries. It includes a low-level memory manager that supports direct pointer manipulation and the use of structs for

This project is a collection of reference implementations and benchmarks demonstrating the use of the Vulkan graphics and compute API. It provides a set of cross-platform examples and GPU programming patterns designed for high-performance rendering and hardware-accelerated tasks. The repository includes a suite of performance benchmarks used to measure API behavior across different hardware environments. It features a modular architecture that organizes rendering examples into isolated units, along with command-line utilities for the batch execution of sample sequences. The project covers se

cuda-python provides low-level Python bindings for the CUDA Driver and Runtime APIs. It serves as a programmatic wrapper for controlling device memory, managing hardware toolchains, and orchestrating execution graphs on NVIDIA GPUs, allowing for the compilation and launching of parallel kernels directly from Python. The project enables the development of SIMT kernels and the execution of mathematical algorithms on device memory. It integrates pre-compiled bytecode as custom operators and interfaces with accelerated device libraries to access low-level hardware functions without leaving the la

HIP is a C++ runtime API and kernel language for writing parallel GPU code that runs on AMD GPUs and can also target NVIDIA GPUs. It is part of the AMD ROCm GPU compute platform and lets host code and GPU kernels live together in ordinary C++ source files, which a Clang-based compiler splits into CPU and GPU portions at build time. Kernels are launched with an inline grid-and-block syntax, and the runtime covers launching kernels, managing device memory and coordinating work between CPU and GPU. What sets HIP apart is its close mirroring of the CUDA runtime API. Existing CUDA applications can

Kotlin-native is an ahead-of-time, cross-platform compiler and toolchain that transforms Kotlin source code into standalone native machine binaries. It functions as an LLVM native compiler, producing executable files that run directly on hardware without the requirement of a virtual machine. The project enables cross-platform native development across multiple operating systems and processor architectures, including iOS, Linux, and Windows. This allows for the creation of native Apple platform applications and software for embedded systems programming where direct memory management and minima

Porffor is an ahead-of-time compiler that converts JavaScript and TypeScript source code into native machine code or C binaries. It functions as a native binary generator and transpiler, producing standalone executable files that do not require a runtime or virtual machine. The project translates source code into C language files and WebAssembly binary formats. It includes a direct-to-binary pipeline for TypeScript, allowing for the generation of target executables without a separate transpilation step to JavaScript. The toolset also includes an interactive read-eval-print loop for real-time

TileLang is a Python-embedded domain-specific language compiler that JIT-compiles and autotunes GPU kernels. It uses a tile-based DSL, automatic software pipelining, and parallel autotuning to generate optimized GPU kernels at runtime. It supports tensor core operations with Pythonic syntax, automatic memory management, and thread mapping. The compiler searches over tile sizes, thread counts, and scheduling policies, compiling and benchmarking candidates in parallel to find the fastest kernel. It also caches compiled binaries and tuning results to disk for reuse across sessions. TileLang inc

Rustowl is a diagnostic system and language server protocol extension that maps variable validity and data flow directly into text editors. It serves as a memory management tool designed to visualize lifetime constraints and ownership movement within Rust source code. The project distinguishes itself by providing a visual representation of immutable borrowings, mutable borrowings, and value moves. It specifically tracks the duration of variable validity and identifies invalid overlapping references or lifetime mismatches to assist in memory debugging. The system employs static analysis to tr

This project is an interactive programming education resource and tutorial designed for learning the Rust programming language and systems programming concepts. It provides a collection of runnable and editable code examples that serve as a practical reference for language syntax and implementation. The resource features an interactive code sandbox that allows users to execute and test code snippets in real time. It emphasizes the verification of technical accuracy by executing embedded code blocks during the build process to ensure all examples remain functional. The content covers a compre

cheats.rs is a Rust syntax reference and technical documentation resource provided as a static site. It serves as a curated collection of examples and patterns designed to assist with Rust language learning. The project covers a wide range of language constructs, including memory management, the use of generics, and the implementation of asynchronous logic. It provides guidance on defining data structures, managing memory references, and organizing code modules. Additional coverage includes patterns for control flow, pattern matching, and the use of macros, as well as instructions for perfor

HIP is a C++ GPU kernel language and cross-platform runtime designed for writing portable high-performance compute applications. It provides a programming interface that allows a single source codebase to execute on both AMD and NVIDIA GPU architectures. The project functions as a compatibility layer that enables the conversion and migration of existing CUDA source code to run on AMD hardware. This is achieved through a syntax mapping that mirrors CUDA and a source-to-source translation process during compilation. The toolkit covers the broader surface of cross-platform GPGPU development, in

AITemplate is an ahead-of-time deep learning compiler that translates PyTorch neural networks into standalone C++ source code. It functions as a PyTorch to C++ compiler and a GPU kernel fusion engine, producing self-contained executable binaries that run inference without requiring a Python interpreter or deep learning framework runtime. The project generates optimized CUDA and HIP C++ code specifically for NVIDIA TensorCores and AMD MatrixCores. It focuses on maximizing throughput for half-precision floating-point operations through a system that combines multiple neural network operators in

Carp is a statically typed Lisp compiler that compiles Lisp-like syntax directly to C source code, enabling seamless integration with existing C libraries and low-level system programming. It manages memory deterministically at compile time using ownership tracking and linear types, eliminating garbage collection pauses and runtime overhead while ensuring type safety through an inferred static type system. The language distinguishes itself through compile-time macro expansion and metaprogramming capabilities, allowing code generation and transformation before final binary output. It enforces

Crab is a memory-safe systems programming language and ahead-of-time compiler designed for high-performance software. It utilizes a type system based on strict ownership and borrowing rules to prevent memory access errors at compile time. The toolchain includes an automated documentation generator that produces technical reference manuals and API guides by parsing structured source code annotations. It also features a dependency management tool to resolve external library graphs and ensure consistent project builds. The project covers software build automation, static type checking, and mult

ndarray is a multidimensional array library for Rust that serves as a linear algebra framework and scientific computing tool. It provides the core infrastructure for creating and manipulating n-dimensional arrays, functioning as both a parallel array processor and a toolkit for numerical data analysis. The library distinguishes itself by providing efficient slicing and memory views, allowing for data sharing without copying. It leverages optimized backend math libraries for high-speed matrix multiplication and distributes heavy mathematical iterations across multiple CPU threads to accelerate

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

wazero is a pure Go WebAssembly runtime that compiles and executes Wasm modules without CGO or any external dependencies. It provides a zero-dependency engine that runs on every Go-supported platform, including riscv64, making it a fully self-contained solution for embedding WebAssembly execution inside Go applications. The runtime offers two execution modes: an ahead-of-time compiler that translates WebAssembly modules into platform-specific machine code for near-native performance, and an interpreter that executes bytecode directly for maximum portability across architectures. Each module i

Carbon is an experimental, compiled systems programming language designed as a successor to C++. It focuses on providing a high-performance environment for modern software development while prioritizing memory safety and expressive generic programming. The language is built to support performance-critical engineering, allowing for precise control over memory layout and execution flow. A primary differentiator of the project is its bidirectional interoperability with existing C++ codebases. This allows developers to call functions and share data between languages without manual wrappers, facil