MATLAB is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks. MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.
NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. The predecessor of NumPy, Numeric, was originally created by Jim Hugunin with contributions from several other developers. In 2005, Travis Oliphant created NumPy by incorporating features of the competing Numarray into Numeric, with extensive modifications. NumPy is open-source software and has many contributors. NumPy is a NumFOCUS fiscally sponsored project.
Open64 is a free, open-source, optimizing compiler for the Itanium and x86-64 microprocessor architectures. It derives from the SGI compilers for the MIPS R10000 processor, called MIPSPro. It was initially released in 2000 as GNU GPL software under the name Pro64. The following year, University of Delaware adopted the project and renamed the compiler to Open64. It now mostly serves as a research platform for compiler and computer architecture research groups. Open64 supports Fortran 77/95 and C/C++, as well as the shared memory programming model OpenMP. It can conduct high-quality interprocedural analysis, data-flow analysis, data dependence analysis, and array region analysis. Development has ceased, although other projects can use the project's source.
LAPACK is a standard software library for numerical linear algebra. It provides routines for solving systems of linear equations and linear least squares, eigenvalue problems, and singular value decomposition. It also includes routines to implement the associated matrix factorizations such as LU, QR, Cholesky and Schur decomposition. LAPACK was originally written in FORTRAN 77, but moved to Fortran 90 in version 3.2 (2008). The routines handle both real and complex matrices in both single and double precision. LAPACK relies on an underlying BLAS implementation to provide efficient and portable computational building blocks for its routines.
General-purpose computing on graphics processing units is the use of a graphics processing unit (GPU), which typically handles computation only for computer graphics, to perform computation in applications traditionally handled by the central processing unit (CPU). The use of multiple video cards in one computer, or large numbers of graphics chips, further parallelizes the already parallel nature of graphics processing.
A physics processing unit (PPU) is a dedicated microprocessor designed to handle the calculations of physics, especially in the physics engine of video games. It is an example of hardware acceleration.
OpenCV is a library of programming functions mainly for real-time computer vision. Originally developed by Intel, it was later supported by Willow Garage, then Itseez. The library is cross-platform and licensed as free and open-source software under Apache License 2. Starting in 2011, OpenCV features GPU acceleration for real-time operations.
A free and open-source graphics device driver is a software stack which controls computer-graphics hardware and supports graphics-rendering application programming interfaces (APIs) and is released under a free and open-source software license. Graphics device drivers are written for specific hardware to work within a specific operating system kernel and to support a range of APIs used by applications to access the graphics hardware. They may also control output to the display if the display driver is part of the graphics hardware. Most free and open-source graphics device drivers are developed by the Mesa project. The driver is made up of a compiler, a rendering API, and software which manages access to the graphics hardware.
In computing, CUDA is a proprietary parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for accelerated general-purpose processing, an approach called general-purpose computing on GPUs (GPGPU). CUDA API and its runtime: The CUDA API is an extension of the C programming language that adds the ability to specify thread-level parallelism in C and also to specify GPU device specific operations. CUDA is a software layer that gives direct access to the GPU's virtual instruction set and parallel computational elements for the execution of compute kernels. In addition to drivers and runtime kernels, the CUDA platform includes compilers, libraries and developer tools to help programmers accelerate their applications.
In computing, Close To Metal is the name of a beta version of a low-level programming interface developed by ATI, now the AMD Graphics Product Group, aimed at enabling GPGPU computing. CTM was short-lived, and the first production version of AMD's GPGPU technology is now called AMD Stream SDK, or rather the current AMD APP SDK ) for Windows and Linux 32-bit and 64-bit, which also targets Heterogeneous System Architecture.
PGI was a company that produced a set of commercially available Fortran, C and C++ compilers for high-performance computing systems. On July 29, 2013, Nvidia acquired The Portland Group, Inc. As of August 5, 2020, the "PGI Compilers and Tools" technology is a part of the Nvidia HPC SDK product available as a free download from Nvidia.
AMD FireStream was AMD's brand name for their Radeon-based product line targeting stream processing and/or GPGPU in supercomputers. Originally developed by ATI Technologies around the Radeon X1900 XTX in 2006, the product line was previously branded as both ATI FireSTREAM and AMD Stream Processor. The AMD FireStream can also be used as a floating-point co-processor for offloading CPU calculations, which is part of the Torrenza initiative. The FireStream line has been discontinued since 2012, when GPGPU workloads were entirely folded into the AMD FirePro line.
OpenCL is a framework for writing programs that execute across heterogeneous platforms consisting of central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs) and other processors or hardware accelerators. OpenCL specifies programming languages for programming these devices and application programming interfaces (APIs) to control the platform and execute programs on the compute devices. OpenCL provides a standard interface for parallel computing using task- and data-based parallelism.
Nvidia CUDA Compiler (NVCC) is a compiler by Nvidia intended for use with CUDA. It is proprietary software.
GPULib is discontinued and unsupported software library developed by Tech-X Corporation for accelerating general-purpose scientific computations from within the Interactive Data Language (IDL) using Nvidia's CUDA platform for programming its graphics processing units (GPUs). GPULib provides basic arithmetic, array indexing, special functions, Fast Fourier Transforms (FFT), interpolation, BLAS matrix operations as well as LAPACK routines provided by MAGMA, and some image processing operations. All numeric data types provided by IDL are supported. GPULib is used in medical imaging, optics, astronomy, earth science, remote sensing, and other scientific areas.
Heterogeneous System Architecture (HSA) is a cross-vendor set of specifications that allow for the integration of central processing units and graphics processors on the same bus, with shared memory and tasks. The HSA is being developed by the HSA Foundation, which includes AMD and ARM. The platform's stated aim is to reduce communication latency between CPUs, GPUs and other compute devices, and make these various devices more compatible from a programmer's perspective, relieving the programmer of the task of planning the moving of data between devices' disjoint memories.
ROCm is an Advanced Micro Devices (AMD) software stack for graphics processing unit (GPU) programming. ROCm spans several domains: general-purpose computing on graphics processing units (GPGPU), high performance computing (HPC), heterogeneous computing. It offers several programming models: HIP, OpenMP, and OpenCL.
oneAPI is an open standard, adopted by Intel, for a unified application programming interface (API) intended to be used across different computing accelerator (coprocessor) architectures, including GPUs, AI accelerators and field-programmable gate arrays. It is intended to eliminate the need for developers to maintain separate code bases, multiple programming languages, tools, and workflows for each architecture.
