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CPLD-Guide

Complex Programmable Logic Device (CPLD) Guide
https://github.com/mikeroyal/CPLD-Guide

Last synced: 4 days ago
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Assembly Learning Resources

C/C++ Learning Resources

C/C++ Tools, Libraries and Frameworks

  • AWS SDK for C++
  • 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
  • ReSharper C++
  • 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. All code inspections are run on the fly.
  • CLion - platform IDE for C and C++ developers developed by JetBrains.
  • Code::Blocks
  • 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.
  • OpenGL Extension Wrangler Library (GLEW) - platform open-source C/C++ extension loading library. GLEW provides efficient run-time mechanisms for determining which OpenGL extensions are supported on the target platform.
  • 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.
  • Cython
  • Infer - C, and C. Infer is written in OCaml.
  • sparkfun
  • andrewpover.co.uk
  • vecteezy
  • differencebetween
  • electrical4u
  • differencebetween
  • Azure SDK for C++
  • Azure SDK for C
  • C++ Client Libraries for Google Cloud Services
  • Vcpkg
  • CppSharp
  • Thrust - level interface greatly enhances programmer productivity while enabling performance portability between GPUs and multicore CPUs. Interoperability with established technologies such as CUDA, TBB, and OpenMP integrates with existing software.
  • JavaCPP
  • Spdlog - only/compiled, C++ logging library.
  • sdsu-physics
  • sdsu-physics
  • sdsu-physics
  • andrewpover.co.uk

Firmware Learning Resources

Firmware Tools, Libraries, and Frameworks

MATLAB Learning Resources

MATLAB Tools, Libraries, Frameworks

  • MATLAB and Simulink Services & Applications List
  • MATLAB in the Cloud - cloud) including AWS and Azure.
  • Simulink - Based Design. It supports simulation, automatic code generation, and continuous testing of embedded systems.
  • Simulink Online™
  • MATLAB Drive™
  • 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.
  • 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™
  • Statistics and Machine Learning Toolbox™
  • Lidar Toolbox™ - camera cross calibration for workflows that combine computer vision and lidar processing.
  • Mapping Toolbox™
  • UAV Toolbox
  • Partial Differential Equation Toolbox™
  • ROS Toolbox
  • Robotics Toolbox™ - holonomic vehicle. The Toolbox also including a detailed Simulink model for a quadrotor flying robot.
  • 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.
  • Model Predictive Control Toolbox™ - loop simulations, you can evaluate controller performance.
  • 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.
  • 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.
  • hctsa - series analysis using Matlab.
  • YALMIP
  • hctsa - series analysis using Matlab.
  • MATLAB Schemer
  • 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.
  • 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.
  • 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.
  • 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.

OpenCL Learning Resources