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Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)
Antares: an automatic engine for multi-platform kernel generation and optimization. Supporting CPU, CUDA, ROCm, DirectX12, GraphCore, SYCL for CPU/GPU, OpenCL for AMD/NVIDIA, Android CPU/GPU backends.
A simple implementation of the Google File System in golang
A list of awesome compiler projects and papers for tensor computation and deep learning.
A single-header C++ library for simplifying the use of CUDA Runtime Compilation (NVRTC).
STREAM, for lots of devices written in many programming models
Collection of recent methods on (deep) neural network compression and acceleration.
A collection of examples for the ROCm software stack
Representation and Reference Lowering of ONNX Models in MLIR Compiler Infrastructure
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
A GPU-driven system framework for scalable AI applications
A list of papers, docs, codes about model quantization. This repo is aimed to provide the info for model quantization research, we are continuously improving the project. Welcome to PR the works (p…
nndeploy是一款模型端到端部署框架。以多端推理以及基于有向无环图模型部署为基础，致力为用户提供跨平台、简单易用、高性能的模型部署体验。
⭐⭐⭐zk的设计与使用（集群，dubbo，分布式锁，master选举，负载均衡，watch，权限等）
You like pytorch? You like micrograd? You love tinygrad! ❤️
Rafiki is a distributed system that supports training and deployment of machine learning models using AutoML, built with ease-of-use in mind.
AISystem 主要是指AI系统，包括AI芯片、AI编译器、AI推理和训练框架等AI全栈底层技术
Tutorial for the Vulkan graphics and compute API
Development repository for the Triton language and compiler
Seamless operability between C++11 and Python
《Machine Learning Systems: Design and Implementation》- Chinese Version
Open deep learning compiler stack for cpu, gpu and specialized accelerators
SGI STL source code analysis and note from 《STL源码剖析》 by 侯捷（包含电子书、源码注释及测试代码）
Mirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitti…