Open AccessIntensive computing on a large data volume with a short‐vector single instruction multiple data processor
Author(s) -
Ungurean Ioan,
Gaitan VasileGheorghita,
Gaitan NicoletaCristina
Publication year - 2014
Publication title -
iet computers and digital techniques
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.219
H-Index - 46
eISSN - 1751-861X
pISSN - 1751-8601
DOI - 10.1049/iet-cdt.2013.0149
Subject(s) - computer science , parallel computing , powerpc , volume (thermodynamics) , speedup , computation , process (computing) , vector processor , computational science , computer hardware , computer architecture , algorithm , operating system , software , physics , quantum mechanics
In this study, the authors want to evaluate the performances of the PowerXCell 8i processor, which is based on Cell Broadband Engine architecture. For this purpose, the authors chose an algorithm for the k ‐nearest neighbour problem. The authors optimised this algorithm for efficient exploitation of the facilities provided by this architecture. The authors evaluated the PowerXCell 8i performances by algorithm execution with single‐ and double‐precision calculations. For both cases, the performances were evaluated with and without SIMDisation. For single‐precision calculations, the authors achieved a maximum speed‐up of 43.85 with SIMDisation by activating 6 synergetic processor element (SPE) processors and 39.73 without SIMDisation by activating 16 SPE processors. For double‐precision calculations, the authors achieved a maximum speed‐up of 34.79 with SIMDisation by activating 9 SPE processors and 32.71 without SIMDisation by activating 12 SPE processors. These values related to the execution on the PowerPC processor element processor and are due to the accessing way of the main memory by the SPE cores, through the DMA transfers who are performed in parallel with the computing operations. The authors conclude that this process can be efficiently used for the execution of algorithms that require intensive computations on huge data volume.