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BLAS was originally developed as a linear algebra library using Fortran, and was later ported to C/C++. As a core component of modern high-performance computing, it has formed a set of standards. There are open source implementations such as Netlib BLAS, GotoBLAS and its successor OpenBLAS. Commercially, each manufacturer has corresponding implementations for its own platform, such as Intel’s MKL, NVIDIA’s CUDA, AMD’s AOCL and ROCm. Some of them are optimized for CPU platforms, and some use GPU parallel acceleration. This article uses different BLAS libraries to implement matrix operations and analyzes the performance differences between different implementations.

Speaking of matrices, anyone who studies science and engineering will think of the fear of being dominated by linear algebra classes. Matrix multiplication operations are indispensable for various industrial and scientific research numerical calculations, and are also used in various benchmarking software. The time consumption of matrix multiplication operations is also an important indicator for judging the floating-point operation performance of computers. The purpose of this article is to verify the performance differences of various implementation methods through matrix multiplication operations, and compare the performance differences of different computing platforms to provide a reference for high-performance computing development.

STAR-CCM+ user program (user library)¹ is a dynamic link library compiled and constructed according to certain rules by an external compiler (usually C/C++, but also supports Fortran in Linux). By registering the constructed dynamic link library in the sim file, certain custom functions can be implemented. A user library usually contains one or more user-defined functions, which are generally used to implement special configuration or field functions.

Uer library need to register dynamic link libraries before they can be called, and the format of dynamic link libraries is often closely related to the operating system, hardware platform, etc. Therefore, user library are usually compiled for specific platforms and cannot run across platforms.