Vector

CUDA, short for Compute Unified Device Architecture, was created by NVIDIA in 2006. CUDA is a parallel computing platform and programming model that enables developers to harness the power of NVIDIA GPUs for general-purpose computing (GPGPU). Developers can access CUDA through the official site: CUDA Toolkit Downloads, which provides compilers, libraries, SDKs, and documentation for Windows, macOS, and Linux platforms.

R, short for R Programming Language, is a high-level language and environment designed for statistical computing, data analysis, and graphical representation. It is widely used in academic research, data science, machine learning, and business analytics.

NumPy, short for Numerical Python, is a powerful library for the Python programming language that provides support for large, multi-dimensional arrays and matrices, along with a collection of high-level mathematical functions to operate on them. Developed initially by Travis Oliphant in 2005, NumPy is widely used in scientific computing, data analysis, machine learning, and engineering applications.

BLAS, short for Basic Linear Algebra Subprograms, is a specification for low-level routines that perform common linear algebra operations such as vector and matrix multiplication, dot products, and vector scaling. Originally developed in the 1970s, BLAS provides a standardized interface for high-performance numerical computing across a wide variety of programming languages and hardware architectures.