GPU-Based High-Performance Computing in Science and Economics
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Keywords

graphics processing unit (GPU), general purpose GPU (GPGPU), high-performance computing (HPC), data parallelism, SIMD and SPMD models, CUDA programming model, GPU acceleration of matrix multiplication, green computer, flops per watt

How to Cite

Plander, I. (2023). GPU-Based High-Performance Computing in Science and Economics. Information Technology Applications, 1(1), 48–54. Retrieved from https://www.itajournal.com/index.php/ita/article/view/218

Abstract

In the past few years, a new class of high-performance computing (HPC) systems has emerged. These systems employ unconventional processor architectures – such as cell accelerator and graphics processing units (GPUs) – for heavy computations and use conventional central processing units (CPUs) mostly for non-compute-intensive tasks, such as I/O and communication. General Purpose GPUs (GPGPUs) appear for scientific computing. A new concept is to use a GPGPU as a modified form of stream processor. This paper gives an overview of the state-of-the-art of the developments and applications in GPU-based high-performance computing for all platforms: applications, hardware and software technologies, languages and development environments.

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