Multidimensional DSP with GPU acceleration: Difference between revisions

Revision as of 22:29, 19 December 2023

Revision as of 07:19, 5 March 2024

Line 25:

==GPGPU computations==

[[File:SIMD GPGPU.jpg|alt= Figure illustrating a SIMD/vector computation unit in GPGPUs..|thumb|GPGPU/SIMD computation model.]]

Modern GPU designs are mainly based on the [[Single instruction, multiple data|SIMD]] (Single Instruction Multiple Data) computation paradigm.<ref>{{cite journal|title=NVIDIA Tesla: A Unified Graphics and Computing Architecture|journal=IEEE Micro|date=2008-03-01|issn=0272-1732|pages=39–55|volume=28|issue=2|doi=10.1109/MM.2008.31|first1=E.|last1=Lindholm|first2=J.|last2=Nickolls|first3=S.|last3=Oberman|first4=J.|last4=Montrym|s2cid=2793450|url=https://ieeexplore.ieee.org/document/4523358|url-access=registration|language=en}}</ref><ref>{{cite book|title=Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)|last1=Kim|first1=Hyesoon|author1-link=Hyesoon Kim|publisher=Morgan & Claypool Publishers|year=2012|isbn=978-1-60845-954-4|last2=Vuduc|first2=Richard|last3=Baghsorkhi|first3=Sara|last4=Choi|first4=Jee|last5=Hwu|first5=Wen-Mei W.|editor-last=Hill|editor-first=Mark D.|doi=10.2200/S00451ED1V01Y201209CAC020|language=en}}</ref> This type of GPU devices is so-called [[General-purpose computing on graphics processing units|general-purpose GPUs (GPGPUs)]].