gpu-guide

Graphics Processing Unit (GPU) Architecture Guide
https://github.com/mikeroyal/gpu-guide

Last synced: about 11 hours ago
JSON representation

Game Engines
- Unigine - platform game engine designed for development teams (C++/C# programmers, 3D artists) working on interactive 3D apps.
- Unity - platform game development platform. Use Unity to build high-quality 3D and 2D games, deploy them across mobile, desktop, VR/AR, consoles or the Web, and connect with loyal and enthusiastic players and customers.
- Unreal Engine 4 - time 3D creation tool. Continuously evolving to serve not only its original purpose as a state-of-the-art game engine, today it gives creators across industries the freedom and control to deliver cutting-edge content, interactive experiences, and immersive virtual worlds.
- Godot Engine - packed, cross-platform game engine to create 2D and 3D games from a unified interface. It provides a comprehensive set of common tools, so that users can focus on making games without having to reinvent the wheel. Games can be exported in one click to a number of platforms, including the major desktop platforms (Linux, Mac OSX, Windows) as well as mobile (Android, iOS) and web-based (HTML5) platforms.
- If you would like to Donate to the Godot Project
- Blender
- If you would like to Donate to the Blender Project
OpenGL Learning Resources
- WebGL 2.0 Specification
- OpenGL ES™
- WebGL™ - platform, royalty-free web standard for a low-level 3D graphics API based on OpenGL ES, exposed to JavaScript via the HTML5 Canvas element.
- Top OpenGL Courses Online | Udemy
- Getting Started with OpenGL
- WebGL Public Wiki
- Top OpenGL Courses Online | Coursera
- OpenGL Reference Cards
- OpenGL Online Training Courses | LinkedIn Learning
Augmented Reality (AR) & Virtual Reality (VR)
- Libsurvive
- ARKit - reality apps for iOS developed by Apple. The latest version ARKit 3.5 takes advantage of the new LiDAR Scanner and depth sensing system on iPad Pro(2020) to support a new generation of AR apps that use Scene Geometry for enhanced scene understanding and object occlusion.
- RealityKit - performance 3D simulation and rendering with information provided by the ARKit framework to seamlessly integrate virtual objects into the real world.
- ARCore
- SteamVR
- OpenVR
- OpenHMD - mounted display) devices such as Oculus Rift, HTC Vive, Sony PSVR, and others.
- Monado - start development of an open source XR ecosystem and provide the fundamental building blocks for device vendors to target the GNU/Linux platform.
- Simula - 638454156)).
- OpenVR Benchmark on Steam
Parallel Computing Tools, Libraries, and Frameworks
- Apache Mesos
- Apache HBase™ - source, NoSQL, distributed big data store. It enables random, strictly consistent, real-time access to petabytes of data. HBase is very effective for handling large, sparse datasets. HBase serves as a direct input and output to the Apache MapReduce framework for Hadoop, and works with Apache Phoenix to enable SQL-like queries over HBase tables.
- Hadoop Distributed File System (HDFS) - yarn/hadoop-yarn-site/YARN.html).
- Apache Arrow - independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware like CPUs and GPUs.
- Apache Spark™ - scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing.
- Apache PredictionIO
- Microsoft Project Bonsai - code AI platform that speeds AI-powered automation development and part of the Autonomous Systems suite from Microsoft. Bonsai is used to build AI components that can provide operator guidance or make independent decisions to optimize process variables, improve production efficiency, and reduce downtime.
- Cluster Manager for Apache Kafka(CMAK)
- BigDL
- Apache Beam - specific SDKs for defining and executing data processing workflows, and also data ingestion and integration flows, supporting Enterprise Integration Patterns (EIPs) and Domain Specific Languages (DSLs).
- Jupyter Notebook - source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Jupyter is used widely in industries that do data cleaning and transformation, numerical simulation, statistical modeling, data visualization, data science, and machine learning.
- Neo4j - strength graph database that combines native graph storage, advanced security, scalable speed-optimized architecture, and ACID compliance to ensure predictability and integrity of relationship-based queries.
- ElasticSearch - capable full-text search engine with an HTTP web interface and schema-free JSON documents. Elasticsearch is developed in Java.
- Logstash
- Kibana
- Trino - us/azure/architecture/data-guide/relational-data/etl), allow them all to use standard SQL statement, and work with numerous data sources and targets all in the same system.
- Redis(REmote DIctionary Server) - memory data structure store, used as a database, cache, and message broker. It provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
- Apache OpenNLP - source library for a machine learning based toolkit used in the processing of natural language text. It features an API for use cases like [Named Entity Recognition](https://en.wikipedia.org/wiki/Named-entity_recognition), [Sentence Detection](), [POS(Part-Of-Speech) tagging](https://en.wikipedia.org/wiki/Part-of-speech_tagging), [Tokenization](https://en.wikipedia.org/wiki/Tokenization_(data_security)) [Feature extraction](https://en.wikipedia.org/wiki/Feature_extraction), [Chunking](https://en.wikipedia.org/wiki/Chunking_(psychology)), [Parsing](https://en.wikipedia.org/wiki/Parsing), and [Coreference resolution](https://en.wikipedia.org/wiki/Coreference).
- Open Neural Network Exchange(ONNX) - in operators and standard data types.
- Back to the Top
- AutoGluon - accuracy deep learning models on tabular, image, and text data.
- Statistics and Machine Learning Toolbox™
- CUDA®
- OpenMP - platform shared-memory parallel programming in C/C++ and Fortran. The OpenMP API defines a portable, scalable model with a simple and flexible interface for developing parallel applications on platforms from the desktop to the supercomputer.
- Message Passing Interface (MPI) - passing standard designed to function on parallel computing architectures.
- Slurm - source workload manager designed specifically to satisfy the demanding needs of high performance computing.
- Numba - aware optimizing compiler for Python sponsored by Anaconda, Inc. It uses the LLVM compiler project to generate machine code from Python syntax. Numba can compile a large subset of numerically-focused Python, including many NumPy functions. Additionally, Numba has support for automatic parallelization of loops, generation of GPU-accelerated code, and creation of ufuncs and C callbacks.
- Chainer - based deep learning framework aiming at flexibility. It provides automatic differentiation APIs based on the define-by-run approach (dynamic computational graphs) as well as object-oriented high-level APIs to build and train neural networks. It also supports CUDA/cuDNN using [CuPy](https://github.com/cupy/cupy) for high performance training and inference.
- cuML - learn.
- Apache Flume
- AWS ParallelCluster - supported open source cluster management tool that makes it easy for you to deploy and manage High Performance Computing (HPC) clusters on AWS. ParallelCluster uses a simple text file to model and provision all the resources needed for your HPC applications in an automated and secure manner.
- Parallel Computing Toolbox™ - intensive problems using multicore processors, GPUs, and computer clusters. High-level constructs such as parallel for-loops, special array types, and parallelized numerical algorithms enable you to parallelize MATLAB® applications without CUDA or MPI programming. The toolbox lets you use parallel-enabled functions in MATLAB and other toolboxes. You can use the toolbox with Simulink® to run multiple simulations of a model in parallel. Programs and models can run in both interactive and batch modes.
- XGBoost
OpenCL Learning Resources
- Open Computing Language (OpenCL) - to-parallel-computing-zNrIS) of heterogeneous platforms consisting of CPUs, GPUs, and other hardware accelerators found in supercomputers, cloud servers, personal computers, mobile devices and embedded platforms.
- OpenCL | NVIDIA Developer
- Introduction to OpenCL on FPGAs Course | Coursera
- Compiling OpenCL Kernel to FPGAs Course | Coursera
- Introduction to Intel® OpenCL Tools
- OpenCL Tutorials - StreamHPC
OpenCL Tools, Libraries and Frameworks
- GPUVerify
- OpenCL ICD Loader
- clBLAS
- clFFT
- clSPARSE
- clRNG
- CLsmith - core environment, OpenCL. Its primary feature is the generation of random OpenCL kernels, exercising many features of the language. It also brings a novel idea of applying EMI, via dead-code injection.
- Oclgrind - races and barrier divergence, collecting instruction histograms, and for interactive OpenCL kernel debugging. The simulator is built on an interpreter for LLVM IR.
- NVIDIA® Nsight™ Visual Studio Edition
- Radeon™ GPU Profiler
- Radeon™ GPU Analyzer
- AMD Radeon ProRender - based rendering engine that enables creative professionals to produce stunningly photorealistic images on virtually any GPU, any CPU, and any OS in over a dozen leading digital content creation and CAD applications.
- Intel® SDK For OpenCL™ Applications - intensive workloads. Customize heterogeneous compute applications and accelerate performance with kernel-based programming.
- NVIDIA cuDNN - accelerated library of primitives for [deep neural networks](https://developer.nvidia.com/deep-learning). cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. cuDNN accelerates widely used deep learning frameworks, including [Caffe2](https://caffe2.ai/), [Chainer](https://chainer.org/), [Keras](https://keras.io/), [MATLAB](https://www.mathworks.com/solutions/deep-learning.html), [MxNet](https://mxnet.incubator.apache.org/), [PyTorch](https://pytorch.org/), and [TensorFlow](https://www.tensorflow.org/).
- NVIDIA Container Toolkit - container) and utilities to automatically configure containers to leverage NVIDIA GPUs.
CUDA Learning Resources
- CUDA Toolkit Documentation
- CUDA Quick Start Guide
- CUDA on WSL
- CUDA GPU support for TensorFlow
CUDA Tools Libraries, and Frameworks
- CUDA Toolkit - accelerated applications. The CUDA Toolkit allows you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms and HPC supercomputers. The toolkit includes GPU-accelerated libraries, debugging and optimization tools, a C/C++ compiler, and a runtime library to build and deploy your application on major architectures including x86, Arm and POWER.
- CUDA-X HPC - X HPC includes highly tuned kernels essential for high-performance computing (HPC).
- CUTLASS - performance matrix-multiplication (GEMM) at all levels and scales within CUDA. It incorporates strategies for hierarchical decomposition and data movement similar to those used to implement cuBLAS.
- CUB
- Tensorman
- CuPy - compatible multi-dimensional array on CUDA. CuPy consists of the core multi-dimensional array class, cupy.ndarray, and many functions on it. It supports a subset of numpy.ndarray interface.
- CatBoost
- cuDF - like API that will be familiar to data engineers & data scientists, so they can use it to easily accelerate their workflows without going into the details of CUDA programming.
- ArrayFire - purpose library that simplifies the process of developing software that targets parallel and massively-parallel architectures including CPUs, GPUs, and other hardware acceleration devices.
- Thrust - level interface greatly enhances programmer productivity while enabling performance portability between GPUs and multicore CPUs.
- AresDB - powered real-time analytics storage and query engine. It features low query latency, high data freshness and highly efficient in-memory and on disk storage management.
- Arraymancer - dimensional array) project in Nim. The main focus is providing a fast and ergonomic CPU, Cuda and OpenCL ndarray library on which to build a scientific computing ecosystem.
- Kintinuous - time dense visual SLAM system capable of producing high quality globally consistent point and mesh reconstructions over hundreds of metres in real-time with only a low-cost commodity RGB-D sensor.
- Fuzzy logic - tree processing and better integration with rules-based programming.
- ResearchGate
- Support Vector Machine (SVM) - group classification problems.
- OpenClipArt
- Convolutional Neural Networks (R-CNN)
- CS231n
- Slideteam
- Multilayer Perceptrons (MLPs) - layer neural networks composed of multiple layers of [perceptrons](https://en.wikipedia.org/wiki/Perceptron) with a threshold activation.
- wikimedia
- Decision trees - structured models for classification and regression.
- CMU
- Naive Bayes - theorem.html) with strong independence assumptions between the features.
- mathisfun
Learning Resources for ML
- Machine Learning by Stanford University from Coursera
- Machine Learning Scholarship Program for Microsoft Azure from Udacity
- Machine Learning Crash Course for Google Cloud
- Scheduling Jupyter notebooks on Amazon SageMaker ephemeral instances
- Machine Learning Courses Online from Udemy
- Learn Machine Learning with Online Courses and Classes from edX
- Learning Machine learning and artificial intelligence from Google Cloud Training
ML Frameworks, Libraries, and Tools
- Amazon SageMaker
- Azure Databricks - based big data analytics service designed for data science and data engineering. Azure Databricks, sets up your Apache Spark environment in minutes, autoscale, and collaborate on shared projects in an interactive workspace. Azure Databricks supports Python, Scala, R, Java, and SQL, as well as data science frameworks and libraries including TensorFlow, PyTorch, and scikit-learn.
- Apple CoreML - tune models, all on the user's device. A model is the result of applying a machine learning algorithm to a set of training data. You use a model to make predictions based on new input data.
- Tensorflow_macOS - optimized version of TensorFlow and TensorFlow Addons for macOS 11.0+ accelerated using Apple's ML Compute framework.
- Anaconda
- PlaidML
- OpenCV - time computer vision applications. The C++, Python, and Java interfaces support Linux, MacOS, Windows, iOS, and Android.
- Scikit-Learn
- Caffe
- Theano - dimensional arrays efficiently including tight integration with NumPy.
- nGraph - of-use to AI developers.
- Apache Spark Connector for SQL Server and Azure SQL - performance connector that enables you to use transactional data in big data analytics and persists results for ad-hoc queries or reporting. The connector allows you to use any SQL database, on-premises or in the cloud, as an input data source or output data sink for Spark jobs.
- Eclipse Deeplearning4J (DL4J) - based(Scala, Kotlin, Clojure, and Groovy) deep learning application. This means starting with the raw data, loading and preprocessing it from wherever and whatever format it is in to building and tuning a wide variety of simple and complex deep learning networks.
Deep Learning Learning Resources
- Top Deep Learning Courses Online | Udemy
- Learn Deep Learning with Online Courses and Lessons | edX
- Deep Learning Online Course Nanodegree | Udacity
- Data Science: Deep Learning and Neural Networks in Python | Udemy
- Understanding Machine Learning with Python | Pluralsight
- How to Think About Machine Learning Algorithms | Pluralsight
- Deep Learning Courses | Stanford Online
- Deep Learning - UW Professional & Continuing Education
- Deep Learning Online Courses | Harvard University
- Artificial Intelligence Expert Course: Platinum Edition | Udemy
- Learn Artificial Intelligence with Online Courses and Lessons | edX
- Artificial Intelligence Nanodegree program
- Artificial Intelligence (AI) Online Courses | Udacity
- Intro to Artificial Intelligence Course | Udacity
- Edge AI for IoT Developers Course | Udacity
- Expert Systems and Applied Artificial Intelligence
- Introduction to Microsoft Project Bonsai
- Autonomous Maritime Systems Training | AMC Search
- Top Autonomous Cars Courses Online | Udemy
- Applied Control Systems 1: autonomous cars: Math + PID + MPC | Udemy
- Learn Autonomous Robotics with Online Courses and Lessons | edX
- Autonomous Systems Online Courses & Programs | Udacity
- Autonomous Systems MOOC and Free Online Courses | MOOC List
- Robotics and Autonomous Systems Graduate Program | Standford Online
- Mobile Autonomous Systems Laboratory | MIT OpenCourseWare
- Autonomous Systems - Microsoft AI
Deep Learning Tools, Libraries, and Frameworks
- AMD FidelityFX Super Resolution (FSR) - quality solution for producing high resolution frames from lower resolution inputs. It uses a collection of cutting-edge Deep Learning algorithms with a particular emphasis on creating high-quality edges, giving large performance improvements compared to rendering at native resolution directly. FSR enables “practical performance” for costly render operations, such as hardware ray tracing for the AMD RDNA™ and AMD RDNA™ 2 architectures.
- Intel Xe Super Sampling (XeSS) - cores to run XeSS. The GPUs will have Xe Matrix eXtenstions matrix (XMX) engines for hardware-accelerated AI processing. XeSS will be able to run on devices without XMX, including integrated graphics, though, the performance of XeSS will be lower on non-Intel graphics cards because it will be powered by [DP4a instruction](https://www.intel.com/content/dam/www/public/us/en/documents/reference-guides/11th-gen-quick-reference-guide.pdf).
- Deep Learning Toolbox™ - term memory (LSTM) networks to perform classification and regression on image, time-series, and text data. You can build network architectures such as generative adversarial networks (GANs) and Siamese networks using automatic differentiation, custom training loops, and shared weights. With the Deep Network Designer app, you can design, analyze, and train networks graphically. It can exchange models with TensorFlow™ and PyTorch through the ONNX format and import models from TensorFlow-Keras and Caffe. The toolbox supports transfer learning with DarkNet-53, ResNet-50, NASNet, SqueezeNet and many other pretrained models.
- Reinforcement Learning Toolbox™ - making algorithms for complex applications such as resource allocation, robotics, and autonomous systems.
- Deep Learning HDL Toolbox™ - built bitstreams for running a variety of deep learning networks on supported Xilinx® and Intel® FPGA and SoC devices. Profiling and estimation tools let you customize a deep learning network by exploring design, performance, and resource utilization tradeoffs.
- LIBSVM - SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class classification.
- Microsoft AirSim - source, cross platform, and supports [software-in-the-loop simulation](https://www.mathworks.com/help///ecoder/software-in-the-loop-sil-simulation.html) with popular flight controllers such as PX4 & ArduPilot and [hardware-in-loop](https://www.ni.com/en-us/innovations/white-papers/17/what-is-hardware-in-the-loop-.html) with PX4 for physically and visually realistic simulations. It is developed as an Unreal plugin that can simply be dropped into any Unreal environment. AirSim is being developed as a platform for AI research to experiment with deep learning, computer vision and reinforcement learning algorithms for autonomous vehicles.
- CARLA - source simulator for autonomous driving research. CARLA has been developed from the ground up to support development, training, and validation of autonomous driving systems. In addition to open-source code and protocols, CARLA provides open digital assets (urban layouts, buildings, vehicles) that were created for this purpose and can be used freely.
- ROS/ROS2 bridge for CARLA(package) - way communication between ROS and CARLA. The information from the CARLA server is translated to ROS topics. In the same way, the messages sent between nodes in ROS get translated to commands to be applied in CARLA.
- ROS Toolbox
- Robotics Toolbox™ - holonomic vehicle. The Toolbox also including a detailed Simulink model for a quadrotor flying robot.
- Image Processing Toolbox™ - standard algorithms and workflow apps for image processing, analysis, visualization, and algorithm development. You can perform image segmentation, image enhancement, noise reduction, geometric transformations, image registration, and 3D image processing.
- Computer Vision Toolbox™
- Model Predictive Control Toolbox™ - loop simulations, you can evaluate controller performance.
- Predictive Maintenance Toolbox™ - based and model-based techniques, including statistical, spectral, and time-series analysis.
- Vision HDL Toolbox™ - streaming algorithms for the design and implementation of vision systems on FPGAs and ASICs. It provides a design framework that supports a diverse set of interface types, frame sizes, and frame rates. The image processing, video, and computer vision algorithms in the toolbox use an architecture appropriate for HDL implementations.
- Automated Driving Toolbox™ - eye-view plot and scope for sensor coverage, detections and tracks, and displays for video, lidar, and maps. The toolbox lets you import and work with HERE HD Live Map data and OpenDRIVE® road networks. It also provides reference application examples for common ADAS and automated driving features, including FCW, AEB, ACC, LKA, and parking valet. The toolbox supports C/C++ code generation for rapid prototyping and HIL testing, with support for sensor fusion, tracking, path planning, and vehicle controller algorithms.
- UAV Toolbox
- Navigation Toolbox™ - based path planners, as well as metrics for validating and comparing paths. You can create 2D and 3D map representations, generate maps using SLAM algorithms, and interactively visualize and debug map generation with the SLAM map builder app.
- Lidar Toolbox™ - camera cross calibration for workflows that combine computer vision and lidar processing.
- Mapping Toolbox™
Computer Vision Learning Resources
- Computer Vision
- OpenCV Courses
- Top Computer Vision Courses Online | Udemy
- Learn Computer Vision with Online Courses and Lessons | edX
- Computer Vision and Image Processing Fundamentals | edX
- Introduction to Computer Vision Courses | Udacity
- Computer Vision Nanodegree program | Udacity
- Computer Vision Training Courses | NobleProg
- Visual Computing Graduate Program | Stanford Online
- Exploring Computer Vision in Microsoft Azure
- Top Computer Vision Courses Online | Coursera
Computer Vision Tools, Libraries, and Frameworks
- LRSLibrary - Rank and Sparse Tools for Background Modeling and Subtraction in Videos. The library was designed for moving object detection in videos, but it can be also used for other computer vision and machine learning problems.
- Partial Differential Equation Toolbox™
- Data Acquisition Toolbox™
Performance Benchmarks
- Geekbench 5 - platform benchmark that measures your system's performance with the press of a button.
- Phoronix Test Suite
- UNIGINE Superposition
Apple Arcade
- Apple Arcade - app purchases.
Game Streaming
- Geforce NOW
- Moonlight Game Streaming
- Chiaki
- Xbox Project xCloud - based Xbox game-streaming technology **(currently in Beta)**. **Play games like Forza Horizon 4, Halo 5: Guardians, Gears of War 4, Sea of Thieves, Cuphead, Red Dead Redemption 2, and 100+ other games on your mobile device or Chrome web browser**. Microsoft's Xbox Project xCloud does require an [Xbox Game Pass Ultimate](https://www.xbox.com/en-US/xbox-game-pass/cloud-gaming) subscription.
- Amazon Luna
Game Emulators
- RetroArch
- Citra - source emulator for the Nintendo 3DS capable of playing many of your favorite games.
- yuzu - source emulator for the Nintendo Switch from the creators of Citra.
- DOSBox - source DOS emulator which primarily focuses on running DOS Games.
- MAME
- xemu
- Dolphin
Game Development Tools, Libraries, and Frameworks
- Panda3D - source and free for any purpose, including commercial ventures.
- Source 2 - Life: Alyx.
- AutoDesk 3ds Max
- Houdini
- Open Graphics Library(OpenGL) - accelerated rendering of 2D/3D vector graphics currently developed by the [Khronos Group](https://www.khronos.org/).
- High Level Shading Language(HLSL) - like programmable shaders for the Direct3D pipeline. HLSL was first created with DirectX 9 to set up the programmable 3D pipeline.
- Vulkan - platform graphics and compute API that provides high-efficiency, cross-platform access to modern GPUs used in a wide variety of devices from PCs and consoles to mobile phones and embedded platforms. Vulkan is currently in development by the Khronos consortium.
- Metal - level GPU programming framework used for rendering 2D and 3D graphics on Apple platforms such as iOS, iPadOS, macOS, watchOS and tvOS.
- LibGDX - platform Java game development framework based on OpenGL (ES) that works on Windows, Linux, Mac OS X, Android, your WebGL enabled browser and iOS.
- cocos2d-x - platform framework for building 2d games, interactive books, demos and other graphical applications. It is based on cocos2d-iphone, but instead of using Objective-C, it uses C++. It works on iOS, Android, macOS, Windows and Linux.
- MonoGame - platform games. The spiritual successor to XNA with thousands of titles shipped across desktop, mobile, and console platforms. MonoGame is a fully managed .NET open source game framework without any black boxes.
- HGIG
- Vivox
- GameBlocks - Cheat & Middleware software.
- OpenGL Shading Language(GLSL) - style language, so it covers most of the features a user would expect with such a language. Such as control structures (for-loops, if-else statements, etc) exist in GLSL, including the switch statement.
- MoltenVK
- Superpowers - time collaborative projects . You can use it solo like a regular offline game maker, or setup a password and let friends join in on your project through their Web browser.
Game Development Learning Resources
- Unreal Online Learning - on video courses and guided learning paths.
- Unreal Engine Authorized Training Program
- Unreal Engine for education
- Unreal Engine Training & Simulation
- Unity Certifications
- Game Design Online Courses from Udemy
- Game Design Online Courses from Skillshare
- Learn Game Design with Online Courses and Classes from edX
OpenGL Tools, Libraries, and Frameworks
- BuGLe - like OSes. BuGLe combines a graphical OpenGL debugger with a selection of filters on the OpenGL command stream. The debugger allows viewing of state, textures, framebuffers and shaders, while the filters allow for logging, error checking, video capture and more.
- gDEBugger - featured and free debugger and profiler representing the state-of-the-art in OpenGL and OpenGL ES debugging and profiling on Windows and Linux.
- KTX
- Equalizer
- GLee - platform extension loading library that takes the burden off your application. GLee makes it easy to check for OpenGL extension and core version availability, automatically setting up the entry points with no effort on your part.
- GLEW - source cross-platform extension loading library with thread-safe support for multiple rendering contexts and automatic code generation capability. GLEW provides easy-to-use and efficient methods for checking OpenGL extensions and core functionality.
- libktx
- OpenSceneGraph - level 3D graphics toolkit exposing OpenGL's capabilities while providing many capabilities of its own. OpenSceneGraph boasts a large user community and has been employed for visual simulation, games, virtual reality, scientific visualization, and modeling.
- Mesa 3D Graphics Library - source implementation of the OpenGL specification. A system for rendering interactive 3D graphics. Mesa ties into several other open-source projects: the [Direct Rendering Infrastructure](https://dri.freedesktop.org/), [X.org](https://x.org/), and [Wayland](https://wayland.freedesktop.org/) to provide OpenGL support on Linux, FreeBSD, and other operating systems.
Vulkan Learning Resources
- Khronos Group GitHub
- Vulkan Documentation
- Vulkan GLSL Ray Tracing Emulator Tutorial
- Getting Started with Vulkan
- Vulkan Samples
- Khronos Community Forums
- HLSL to SPIR-V Feature Mapping Manual
Vulkan Tools, Libraries, and Frameworks
- SPIRV-Reflect - V shader bytecode in Vulkan applications.
- Vulkan® Tools
- Vulkan-Hpp
- Vulkan® Memory Allocator (VMA)
- AMD Open Source Driver for Vulkan® - source Vulkan driver for AMD Radeon™ graphics adapters on Linux®.
- Radeon™ Memory Visualizer (RMV)
- DXVK - based translation layer for Direct3D 9/10/11 which allows running 3D applications on Linux using Wine.
- PerfDoc - platform Vulkan layer which checks Vulkan applications for [best practices on Arm Mali](https://developer.arm.com/graphics/developer-guides/mali-gpu-best-practices) devices.
- GLFW - platform library for OpenGL, OpenGL ES and Vulkan application development. It provides a simple, platform-independent API for creating windows, contexts and surfaces, reading input, handling events, etc. GLFW natively supports Windows, macOS and Linux and other Unix-like systems. On Linux both X11 and Wayland are supported.
- VulkanSharp
- Vortice.Vulkan - level bindings for Vulkan API.
- VKD3D-Proton
- ImGui - free graphical user interface library for C++. It outputs optimized vertex buffers that you can render anytime in your 3D-pipeline enabled application. It is fast, portable, renderer agnostic and self-contained (no external dependencies).
- Ash
- gfx-rs - level, cross-platform graphics and compute abstraction library in Rust.
- Vulkan.jl
- Vulkan SDK
DirectX Learning Resources
- Microsoft DirectX® - level API that handles tasks related to multimedia for game programming and video on Microsoft platforms(Windows & Xbox).
- Getting Started with DirectX 12 Ultimate
- Getting Started with the DirectX 12 Agility SDK
- DirectX— Feature Level 12_2
- DirectX 12 Technology | NVIDIA
- AMD DirectX® 12 (DX12) Technology | AMD
- Top Microsoft DirectX Courses Online | Udemy
- DirectX - Learn Microsoft DirectX from Scratch Course | Udemy
- DirectX 11 Programming Course | Udemy
- DirectX 12 and Graphics Education | YouTube
DirectX Tools, Libraries, and Frameworks
- Visual Studio - rich application that can be used for many aspects of software development. Visual Studio makes it easy to edit, debug, build, and publish your app. By using Microsoft software development platforms such as Windows API, Windows Forms, Windows Presentation Foundation, and Windows Store.
- Visual Studio Code
- DirectX-Graphics-Samples
- PIX on Windows
- DirectStorage API - us/2020/07/14/a-closer-look-at-xbox-velocity-architecture/) to Windows. The DirectX API is architected in a way that takes all this into account and maximizes performance throughout the entire pipeline from NVMe drive all the way to the GPU. It does this in several ways: by reducing per-request NVMe overhead, enabling batched many-at-a-time parallel IO requests which can be efficiently fed to the GPU, and giving games finer grain control over when they get notified of IO request completion instead of having to react to every tiny IO completion. The DirectStorage API will be available on [Windows 11](https://www.microsoft.com/en-us/windows/windows-11) PCs with NVMe SSDs, but will also be support in [Windows 10](https://www.microsoft.com/software-download/windows10) version 1909 and newer.
- FNA
- Simple DirectMedia Layer - platform development library designed to provide low level access to audio, keyboard, mouse, joystick, and graphics hardware via OpenGL and Direct3D. It is used by video playback software, emulators, and popular games including Valve's award winning catalog.
- NVRHI (NVIDIA Rendering Hardware Interface)
- RTXMU - RTX Memory Utility SDK
Audio/Video Learning Resources
- 10 Video Production Tools That Make the Difference Between a Good Video and a Bad One by Dann Albright
- Online Audio Editing Classes from Skillshare
- Online Video Editing Classes Skillshare
- Video Editing Courses from Udemy
- Audio Editing Courses from udemy
- Audacity Podcast Production Course: Audio Editing for Podcasters
- Video Editing Online Training Courses from LinkedIn Learning
- Audio Editing Online Training Courses from LinkedIn Learning
Audio/Video Tools and Equipment
- H.264(AVC) - oriented and motion-compensated integer-DCT coding that defines multiple profiles (tools) and levels (max bitrates and resolutions) with support up to 8K.
- H.265(HEVC) - rate.
- FFmpeg
- HandBrake
- HTTP Live Streaming (HLS)
- OpenMAX™ - platform API that provides comprehensive streaming media codec and application portability by enabling accelerated multimedia components to be developed, integrated and programmed across multiple operating systems and silicon platforms.
- GStreamer - handling components. The applications it supports range from simple Ogg/Vorbis playback, audio/video streaming to complex audio (mixing) and video (non-linear editing) processing. Applications can take advantage of advances in codec and filter technology transparently.
- Media Source Extensions (MSE) - source) that allows JavaScript to send byte streams to media codecs within Web browsers that support HTML5 video and audio. Also, this allows the implementation of client-side prefetching and buffering code for streaming media entirely in JavaScript.
- WebRTC - source project that adds real-time communication capabilities to your application that works on top of an open standard. It supports video, voice, and generic data to be sent between peers, allowing developers to build powerful voice- and video-communication solutions.
- Premiere Pro - leading video editing software for film, TV, and the web. Creative tools, integration with other apps and services, and the power of Adobe Sensei help you craft footage into polished films and videos. With [Premiere Rush](https://www.adobe.com/products/premiere-rush.html) you can create and edit new projects from any device.
- Final Cut Pro
- Kdenlive
- OpenShot - source video editing tool that's designed for users new in the editing environment. It has simple features such as a simple drag-and-drop function, it provides an easy-to-use and quick-to-learn user interface. The powerful video editor offers tons of efficient ways to cut and trim down your videos. You can freely utilize the unlimited tracks, video effects engine, title editor, 3D animations, slow motion, and time effects. It supports commonly used video codecs that are supported by FFmpeg like WebM (VP9), AVCHD (libx264), HEVC (libx265) and audio codecs like mp3 (libmp3lame) and aac (libfaac). The program can render MPEG4, ogv, Blu-ray and DVD video, and Full HD videos for uploading to the internet video websites like YouTube.
- Blender - in video sequence editor allows you to perform basic actions like video cuts and splicing, as well as more complex tasks like video masking or color grading. The Video Editor includes: Live preview, luma waveform, chroma vectorscope and histogram displays. Audio mixing, syncing, scrubbing and waveform visualization.
- Shotcut - platform video editor. You can perform various actions such as video editing (including 4K video quality), add effects, create new movies, import most image files formats, export to almost any file format and much more.
- OBS (Open Broadcaster Software)
- REAPER
- Logic Pro
- Avid Pro Tools
- Adobe Audition
- JACK Audio Connection Kit AKA JACK - time, low-latency connections for both audio and MIDI data between applications that implement its API. JACK can be configured to send audio data over a network to a main machine, which then outputs the audio to a physical device. This can be useful to mix audio from a number of linked computers without requiring additional cables or hardware mixers, and keeping the audio path digital for as long as possible.
- JACK2 - latency audio server for multi-processor machines. It is a new implementation of the JACK server core features that aims at removing some limitations of the JACK1 design. The activation system has been changed for a data flow model and lock-free programming techniques for graph access have been used to have a more dynamic and robust system.
- Propellerhead Reason
- Cockos Reaper
- PreSonus Studio One
- LMMS
- Ardour
- Audacity - to-use, multi-track audio editor and recorder for Windows, Mac OS X, GNU/Linux and other operating systems. Developed by a group of volunteers as open source and offered free of charge. Amazing support community.
- Lightworks - linear video editing appluication for editing and mastering digital video used by the film industry. Its professional edition has been used for box office hits, such as Shutter Island, Pulp Fiction, and Mission Impossible. Intimidating user interface. Like professional video editors, such as Adobe Premiere Pro, Lightworks is rather complicated to use for new users.
- Ableton Live
- Image-Line FL Studio - Line.
- PreSonus Studio One
- Steinberg Cubase
- Digital Performer
- Sonic Visualiser - source application for Windows, Linux, and Mac, designed to be the first program you reach for when want to study a music recording closely.
- PipeWire - latency, graph based processing engine on top of audio and video devices that can be used to support the use cases currently handled by both pulseaudio and JACK. PipeWire was designed with a powerful security model that makes interacting with audio and video devices from containerized applications easy. Nodes in the graph can be implemented as separate processes, communicating with sockets and exchanging multimedia content using fd passing.
3D Graphics and Design Learning Resources
- Intro to using Universal Scene Description with NVIDIA
- First steps with Universal Scene Description in Blender
- AMD Radeon ProRender Developer Suite
- Blender Foundation
- Blender Foundation Certification Training
- Blender Institute
- Blender Education
- Blender Network
- Blender Courses from Udemy
- AutoDesk Learning, Training & Certification
- AutoDesk Design Academy
- Graphic Design Masterclass(Photoshop, Illustrator, InDesign) from Udemy
- Vectr: Beginner's Guide To Graphic Design from udemy
- Canva MasterClass: Design For EveryDay Use from Udemy
- AutoDesk Courses and Specializations from Coursera
- Cinema 4D Quick Tips
- Getting Started with Cinema 4D
3D Graphics and Design Tools
- Adobe Creative Cloud
- Autodesk®
- Maya®
- Maya LT™ - looking characters, props, and environments using the sophisticated 3D modeling and animation tools.
- Arnold
- ReCap™ - built conditions to gain insights and make better decisions.
- Flame®
- Mudbox®
- Cinema 4D
- Vuforia - ranging solution suite ensures that we can provide the right AR technology to every customer based on their business needs.
- Vuforia Studio
- OpenVX™ - source, royalty-free standard for cross platform acceleration of computer vision applications. OpenVX enables performance and power-optimized computer vision processing, especially important in embedded and real-time use cases such as face, body and gesture tracking, smart video surveillance, advanced driver assistance systems (ADAS), object and scene reconstruction, augmented reality, visual inspection, robotics and more.
- GPUImage framework - licensed iOS library that lets you apply GPU-accelerated filters and other effects to images, live camera video, and movies. In comparison to Core Image (part of iOS 5.0), GPUImage allows you to write your own custom filters, supports deployment to iOS 4.0, and has a simpler interface. However, it currently lacks some of the more advanced features of Core Image, such as facial detection.
- GPUImage3 - accelerated image and video processing on Mac and iOS. The original GPUImage framework was written in Objective-C and targeted Mac and iOS, the second iteration rewritten in Swift using OpenGL to target Mac, iOS, and Linux, and now this third generation is redesigned to use Metal in place of OpenGL.
- VDPAU
- VA API - source library and API specification, which provides access to graphics hardware acceleration capabilities for video processing.
- XvMC
- Universal Scene Description - sampled scene description for interchange between graphics applications.
- OpenSubdiv
- Affinity Designer - quality concept art.
- Krita
- Vectr
- Glimpse - platform raster graphics editor based on the GNU Image Manipulation Program available for Linux, macOS, and Windows. A great tool for making YouTube video thumbnails.
- GNU Image Manipulation Program(GIMP) - platform raster graphics editor based on the GNU Image Manipulation Program(GIMP) available for Linux, macOS, and Windows. A great free alternative for Photoshop.
- PhotoGIMP
- Photopea
- Inkscape - source vector graphics editor; it can be used to create or edit vector graphics such as illustrations, diagrams, line arts, charts, logos and complex paintings.
- Gthree
- Dust3D - platform open-source modeling software. It helps you create a 3D watertight model in seconds. Use it to speed up your character modeling in game making, 3D printing, and so on.
- Goxel
- Sketchfab - source 3D models ready to view, buy, and download for free.
- M1 compatible games master list | AppleGamingWiki
- M1 Parallels Windows compatible games list | AppleGamingWiki
- Apple Hypervisor - party kernel extensions. Hypervisor provides C APIs so you can interact with virtualization technologies in user space, without writing kernel extensions (KEXTs). As a result, the apps you create using this framework are suitable for distribution on the [Mac App Store](https://www.appstore.com/).
- Apple A-series - bit ARM-based system on a chip (SoC) used in their iPhones and iPads. Though, at WWDC 2020 it was announced that [Apple Silicon](https://developer.apple.com/documentation/apple_silicon) would [transition into Mac laptops](https://www.apple.com/newsroom/2020/06/apple-announces-mac-transition-to-apple-silicon/).
- Apple
- Apple M1 Pro Chip - core system-on-a-chip (SoC) architecture designed for pro systems in the [MacBook Pro 14”](https://www.apple.com/shop/buy-mac/macbook-pro/14-inch). The chip features fast unified memory, industry-leading performance per watt, and incredible power efficiency, along with increased memory bandwidth and capacity. The M1 Pro offers up to 200GB/s of memory bandwidth with support for up to 32GB of unified memory and a GPU (14-core or 16-core option).
- Xcode 12 - based CPUs and Apple Silicon. It includes a unified macOS SDK that features all the frameworks, compilers, debuggers, and other tools you need to build apps that run natively on Apple Silicon and the Intel x86_64 CPU.
- Universal App Quick Start Program
- OpenTimelineIO - less library for dealing strictly with time, opentime.
- Ultimaker Cura - depth control.
- Writing ARM64 Code for Apple Platforms
- Porting Your macOS Apps to Apple Silicon
- Building a Universal macOS Binary
- Addressing Architectural Differences in Your macOS Code
- Porting Just-In-Time(JIT) Compilers to Apple Silicon
- Porting Your Audio Code to Apple Silicon
- Porting Your Metal Code to Apple Silicon
- Tuning Your Code’s Performance for Apple Silicon
- Learn how Rosetta translates executables and what Rosetta can’t translate
- Running Your iOS Apps on macOS
- Adapting iOS Code to Run in the macOS Environment
- Implementing Drivers, System Extensions, and Kexts
- Installing a Custom Kernel Extension
- Debugging a Custom Kernel Extension
- macOS
- Apple
- iOS
- Apple
- iPadOS
- Apple
- WatchOS
- Apple
- FreeCAD - source general-purpose parametric 3D CAD modeler and a building information modeling software with finite-element-method support.
Core ML Learning Resources
- Core ML Models
- Core ML API Reference
- Core ML Specification
- Apple Developer Forums for Core ML
- Top Core ML Courses Online | Udemy
- IBM Watson Services for Core ML | IBM
- Introduction to Core ML
- Integrating a Core ML Model into your App
- Top Core ML Courses Online | Coursera
- Generate Core ML assets using IBM Maximo Visual Inspection | IBM
Core ML Tools, Libraries, and Frameworks
- Core ML tools
- Create ML
- Apple Vision
- SwiftUI
- UIKit - Touch and other types of input to your app, and the main run loop needed to manage interactions among the user, the system, and your app.
- AppKit
- Instruments - analysis and testing tool that’s part of the Xcode tool set. It’s designed to help you profile your iOS, watchOS, tvOS, and macOS apps, processes, and devices in order to better understand and optimize their behavior and performance.
- Cocoapods - C used in Xcode projects by specifying the dependencies for your project in a simple text file. CocoaPods then recursively resolves dependencies between libraries, fetches source code for all dependencies, and creates and maintains an Xcode workspace to build your project.
- AppCode - fixes to resolve them automatically. AppCode provides lots of code inspections for Objective-C, Swift, C/C++, and a number of code inspections for other supported languages.
Metal Learning Resources
- Apple Developer Documentation
- Metal Shading Language Specification
- Metal Sample code
- Metal plugin for TensorFlow
- MetalKit
- Using Metal Feature Set Tables
- Metal Performance Shaders
- Optimizing Performance with the GPU Counters Instrument
- Enabling Frame Capture
- Reducing the Memory Footprint of Metal Apps
- Metal Developer Tools for Windows
- Metal Developer discussions
Metal Tools, Libraries, and Frameworks
- Apple Foundation Framework
- Apple Core Animation Framework
- Apple Core Graphics Framework - level, lightweight 2D rendering with unmatched output fidelity.
- Paravirtualized Graphics Framework - accelerated graphics for macOS running in a virtual machine, hereafter known as the guest. The macOS operating system provides a graphics driver that runs inside the guest, communicating with the framework in the host operating system to take advantage of Metal-accelerated graphics.
MATLAB Learning Resources
- MATLAB
- MATLAB Documentation
- Getting Started with MATLAB
- MathWorks Certification Program
- Apache Spark Basics | MATLAB & Simulink
- MATLAB Hadoop and Spark | MATLAB & Simulink
- MATLAB Online Courses from Udemy
- MATLAB Online Courses from Coursera
- MATLAB Online Courses from edX
- Building a MATLAB GUI
- MATLAB Style Guidelines 2.0
- Setting Up Git Source Control with MATLAB & Simulink
- Pull, Push and Fetch Files with Git with MATLAB & Simulink
- Create New Repository with MATLAB & Simulink
- PRMLT
- MATLAB and Simulink Training from MATLAB Academy
MATLAB Tools, Libraries, Frameworks
- MATLAB and Simulink Services & Applications List
- MATLAB in the Cloud - cloud) including [AWS](https://aws.amazon.com/) and [Azure](https://azure.microsoft.com/).
- Simulink - Based Design. It supports simulation, automatic code generation, and continuous testing of embedded systems.
- Simulink Online™
- MATLAB Drive™
- MATLAB Schemer
- SoC Blockset™
- Wireless HDL Toolbox™ - verified, hardware-ready Simulink® blocks and subsystems for developing 5G, LTE, and custom OFDM-based wireless communication applications. It includes reference applications, IP blocks, and gateways between frame and sample-based processing.
- ThingSpeak™ - of-concept IoT systems that require analytics.
- SEA-MAT
- Gramm - level interface to produce publication-quality plots of complex data with varied statistical visualizations. Gramm is inspired by R's ggplot2 library.
- hctsa - series analysis using Matlab.
- YALMIP
- GNU Octave - level interpreted language, primarily intended for numerical computations. It provides capabilities for the numerical solution of linear and nonlinear problems, and for performing other numerical experiments. It also provides extensive graphics capabilities for data visualization and manipulation.
- MATLAB Online™
- Plotly
C/C++ Learning Resources
- C++ - platform language that can be used to build high-performance applications developed by Bjarne Stroustrup, as an extension to the C language.
- C - purpose, high-level language that was originally developed by Dennis M. Ritchie to develop the UNIX operating system at Bell Labs. It supports structured programming, lexical variable scope, and recursion, with a static type system. C also provides constructs that map efficiently to typical machine instructions, which makes it one was of the most widely used programming languages today.
- Embedded C - committee) to address issues that exist between C extensions for different [embedded systems](https://en.wikipedia.org/wiki/Embedded_system). The extensions hep enhance microprocessor features such as fixed-point arithmetic, multiple distinct memory banks, and basic I/O operations. This makes Embedded C the most popular embedded software language in the world.
- C & C++ Developer Tools from JetBrains
- Open source C++ libraries on cppreference.com
- C++ Graphics libraries
- C++ Libraries in MATLAB
- C++ Tools and Libraries Articles
- Google C++ Style Guide
- C++ style guide for Fuchsia
- Chromium C++ Style Guide
- C++ Core Guidelines
- Learn C++
- Learn C : An Interactive C Tutorial
- C++ Online Training Courses on LinkedIn Learning
- C++ Tutorials on W3Schools
- Learn C Programming Online Courses on edX
- Learn C++ with Online Courses on edX
- Learn C++ on Codecademy
- Coding for Everyone: C and C++ course on Coursera
- C++ For C Programmers on Coursera
- C++ Online Courses on Udemy
- Top C Courses on Udemy
- Basics of Embedded C Programming for Beginners on Udemy
- C++ For Programmers Course on Udacity
- C++ Fundamentals Course on Pluralsight
- C++ Style Guide for ROS
C/C++ Tools and Frameworks
- AWS SDK for C++
- Azure SDK for C++
- Azure SDK for C
- C++ Client Libraries for Google Cloud Services
- Vcpkg
- ReSharper C++
- CLion - platform IDE for C and C++ developers developed by JetBrains.
- Code::Blocks
- CppSharp
- Conan
- High Performance Computing (HPC) SDK
- Boost - edge C++. Boost has been a participant in the annual Google Summer of Code since 2007, in which students develop their skills by working on Boost Library development.
- Automake
- Cmake - source, cross-platform family of tools designed to build, test and package software. CMake is used to control the software compilation process using simple platform and compiler independent configuration files, and generate native makefiles and workspaces that can be used in the compiler environment of your choice.
- GDB
- GCC - C, Fortran, Ada, Go, and D, as well as libraries for these languages.
- GSL - squares fitting. There are over 1000 functions in total with an extensive test suite.
- Libtool
- Maven
- TAU (Tuning And Analysis Utilities) - based sampling. All C++ language features are supported including templates and namespaces.
- Clang - C, C++ and Objective-C++ compiler when targeting X86-32, X86-64, and ARM (other targets may have caveats, but are usually easy to fix). Clang is used in production to build performance-critical software like Google Chrome or Firefox.
- OpenCV - time applications. Cross-Platform C++, Python and Java interfaces support Linux, MacOS, Windows, iOS, and Android.
- ANTLR (ANother Tool for Language Recognition)
- Oat++ - efficient web application. It's zero-dependency and easy-portable.
- JavaCPP
- Cython
- Spdlog - only/compiled, C++ logging library.
- Infer - C, and C. Infer is written in [OCaml](https://ocaml.org/).
Python Learning Resources
- CheckiO
- Getting Started with Python in Visual Studio Code
- Google's Python Style Guide
- The Python Open Source Computer Science Degree by Forrest Knight
- Intro to Python for Data Science
- Intro to Python by W3schools
- Codecademy's Python 3 course
- Learn Python with Online Courses and Classes from edX
- Python Courses Online from Coursera
- MTA: Introduction to Programming Using Python Certification
- PCAP – Certified Associate in Python Programming certification
- PCPP – Certified Professional in Python Programming 1 certification
- Real Python
Python Frameworks and Tools
- Python Package Index (PyPI)
- PyCharm
- Python Tools for Visual Studio(PTVS)
- Pylance
- Pyright
- Django - level Python Web framework that encourages rapid development and clean, pragmatic design.
- AWS Chalice
- HTTPie
- Pipenv
- Python Fire
- Bottle - framework for Python. It is distributed as a single file module and has no dependencies other than the [Python Standard Library](https://docs.python.org/library/).
- Falcon - performance Python web framework for building large-scale app backends and microservices with support for MongoDB, Pluggable Applications and autogenerated Admin.
- Neural Network Intelligence(NNI)
- Luigi - in.
- Locust
- spaCy
- Pillow
- IPython
- Pandas
- PuLP
- Matplotlib - quality figures in a variety of hardcopy formats and interactive environments across platforms.
- Web2py - source web application framework written in Python allowing allows web developers to program dynamic web content. One web2py instance can run multiple web sites using different databases.
- Tornado - blocking network I/O, which can scale to tens of thousands of open connections.
- CherryPy - oriented HTTP web framework.
- Sanic
- Pyramid - world web application development and deployment more fun and more productive.
- TurboGears
- Dash
- NumPy
- GraphLab Create - scale, high-performance machine learning models.
R Learning Resources
- R
- An Introduction to R
- Google's R Style Guide
- Running R at Scale on Google Compute Engine
- Running R on AWS
- Learn R by Codecademy
- Learn R Programming with Online Courses and Lessons by edX
- Learn R For Data Science by Udacity
- R developer's guide to Azure
- RStudio Server Pro for AWS
- R Language Courses by Coursera
- Running R at Scale on Google Compute Engine
R Tools, Libraries, and Frameworks
- Code Server
- R Debugger
- Language Server Protocol (LSP)
- Rmarkdown
- R Host
- Rplugin
- Plotly
- Metaflow - life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning.
- MLR
- ML workspace - in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. ML workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (Tensorflow, PyTorch, Keras, and MXnet) and dev tools (Jupyter, VS Code, and Tensorboard) perfectly configured, optimized, and integrated.
- Plumber
- DiagrammeR
- Knitr - purpose literate programming engine in R, with lightweight API's designed to give users full control of the output without heavy coding work.
- Broom
- Shiny
- Prophet - linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data.
- LightGBM
- Drake - focused pipeline toolkit for reproducibility and high-performance computing.
- VSCode-R - project.org/), including features such as extended syntax highlighting, R language service based on code analysis, interacting with R terminals, viewing data, plots, workspace variables, help pages, managing packages, and working with [R Markdown](https://rmarkdown.rstudio.com/) documents.
Julia Learning Resources
- JuliaHub
- Julia Observer
- Julia Manual
- JuliaLang Essentials
- Julia Style Guide
- Julia By Example
- Julia Meetup groups
- Julia - level, [high-performance](https://julialang.org/benchmarks/) dynamic language for technical computing. Julia programs compile to efficient native code for [multiple platforms](https://julialang.org/downloads/#support_tiers) via LLVM.
- JuliaLang Gitter
- DataFrames Tutorial using Jupyter Notebooks
- Julia Academy
- Julia on Microsoft Azure
Julia Tools, Libraries and Frameworks
- JuliaPro
- Debugger.jl
- Profile (Stdlib)
- Revise.jl - compile.
- JuliaGPU - level syntax and flexible compiler, Julia is well positioned to productively program hardware accelerators like GPUs without sacrificing performance.
- IJulia.jl
- AWS.jl
- CUDA.jl - friendly array abstraction, a compiler for writing CUDA kernels in Julia, and wrappers for various CUDA libraries.
- Nanosoldier.jl
- JuMP.jl - specific modeling language for [mathematical optimization](https://en.wikipedia.org/wiki/Mathematical_optimization) embedded in Julia.
- Optim.jl
- RCall.jl
- PyCall.jl
- MXNet.jl - of-art deep learning to Julia.
- Distributions.jl
- Flux.jl - Julia stack, and provides lightweight abstractions on top of Julia's native GPU and AD support.
- IRTools.jl
- Juno
- XLA.jl
- Julia for VSCode
- JavaCall.jl
- Knet
- DataFrames.jl
- Cassette.jl - in-time (JIT) compilation cycle, enabling post hoc analysis and modification of "Cassette-unaware" Julia programs without requiring manual source annotation or refactoring of the target code.
Contribute
- x
Parallel Computing Learning Resources
- Top Parallel Computing Courses Online | Coursera
- Parallel Computing - level]https://en.wikipedia.org/wiki/Bit-level_parallelism), [instruction-level](https://en.wikipedia.org/wiki/Instruction-level_parallelism), [data](https://en.wikipedia.org/wiki/Data_parallelism), and [task parallelism](https://en.wikipedia.org/wiki/Task_parallelism).
- Accelerated Computing - Training | NVIDIA Developer
- Fundamentals of Accelerated Computing with CUDA Python Course | NVIDIA
- HPC Architecture and System Design | Intel
- Top Parallel Computing Courses Online | Udemy
- Scientific Computing Masterclass: Parallel and Distributed
- Learn Parallel Computing in Python | Udemy
- GPU computing in Vulkan | Udemy
- High Performance Computing Courses | Udacity
- Parallel Computing Courses | Stanford Online
- Parallel Computing with CUDA | Pluralsight
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Programming Languages

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gpu-guide

Game Engines

OpenGL Learning Resources

Augmented Reality (AR) & Virtual Reality (VR)

Parallel Computing Tools, Libraries, and Frameworks

OpenCL Learning Resources

OpenCL Tools, Libraries and Frameworks

CUDA Learning Resources

CUDA Tools Libraries, and Frameworks

Learning Resources for ML

ML Frameworks, Libraries, and Tools

Deep Learning Learning Resources

Deep Learning Tools, Libraries, and Frameworks

Computer Vision Learning Resources

Computer Vision Tools, Libraries, and Frameworks

Performance Benchmarks

Apple Arcade

Game Streaming

Game Emulators

Game Development Tools, Libraries, and Frameworks

Game Development Learning Resources

OpenGL Tools, Libraries, and Frameworks

Vulkan Learning Resources

Vulkan Tools, Libraries, and Frameworks

DirectX Learning Resources

DirectX Tools, Libraries, and Frameworks

Audio/Video Learning Resources

Audio/Video Tools and Equipment

3D Graphics and Design Learning Resources

3D Graphics and Design Tools

Core ML Learning Resources

Core ML Tools, Libraries, and Frameworks

Metal Learning Resources

Metal Tools, Libraries, and Frameworks

MATLAB Learning Resources

MATLAB Tools, Libraries, Frameworks

C/C++ Learning Resources

C/C++ Tools and Frameworks

Python Learning Resources

Python Frameworks and Tools

R Learning Resources

R Tools, Libraries, and Frameworks

Julia Learning Resources

Julia Tools, Libraries and Frameworks

Contribute

Parallel Computing Learning Resources

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