||free peer-reviewed portable C++ source libraries
||GNU Scientific Library (GSL) is a numerical library for C and C++ programmers. The library provides a wide range of mathematical routines such as random number generators, special functions and least-squares fitting. There are over 1000 functions in total with an extensive test suite.
||In scientific computing, OpenBLAS is an open source implementation of the BLAS (Basic Linear Algebra Subprograms) API with many hand-crafted optimizations for specific processor types
||GNU C Library, commonly known as glibc, is the GNU Project's implementation of the C standard library.
||CUDA is a parallel computing platform and application programming interface model created by Nvidia. It allows software developers and software engineers to use a CUDA-enabled graphics processing unit for general purpose processing – an approach termed GPGPU
||OpenMP is an application programming interface that supports multi-platform shared memory multiprocessing programming in C, C++, and Fortran, on many platforms, instruction set architectures and operating systems
||MPICH, is a portable implementation of MPI, a standard for message-passing for distributed-memory applications used in parallel computing
||OpenACC is a programming standard for parallel computing developed by Cray, CAPS, Nvidia and PGI. The standard is designed to simplify parallel programming of heterogeneous CPU/GPU systems
||INTEL Math Library
||Intel Math Kernel Library is a library of optimized math routines for science, engineering, and financial applications. Core math functions include BLAS, LAPACK, ScaLAPACK, sparse solvers, fast Fourier transforms, and vector math. The routines in MKL are hand-optimized specifically for Intel processors. The library supports Intel processors and is available for Windows, Linux and macOS operating systems
||MATLAB is a multi-paradigm numerical computing environment and proprietary programming language developed by MathWork
||TensorFlow is a free and open-source software library for dataflow and differentiable programming across a range of tasks. It is a symbolic math library, and is also used for machine learning applications such as neural networks
||CAFFE is a deep learning framework, originally developed at University of California, Berkeley. It is open source, under a BSD license. It is written in C++, with a Python interface
||Python is an interpreted, high-level, general-purpose programming language
||JupyterLab enables you to work with documents and activities such as Jupyter notebooks, text editors, terminals, and custom components in a flexible, integrated, and extensible manner