Exploiting graphic processing units parallelism to improve intelligent data acquisition system performance in JET's correlation reflectometer

Julián Nieto, G. De Arcas, J. Vega, M. Ruiz, J.M. López, E. Barrera, A. Murari, A. Fonseca

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The performance of intelligent data acquisition systems relies heavily on their processing capabilities and local bus bandwidth, especially in applications with high sample rates or high number of channels. This is the case of the self adaptive sampling rate data acquisition system installed as a pilot experiment in KG8 B correlation reflectometer at JET. The system, which is based on the ITMS platform, continuously adapts the sample rate during the acquisition depending on the signal bandwidth. In order to do so it must transfer acquired data to a memory buffer in the host processor and run heavy computational algorithms for each data block. The processing capabilities of the host CPU and the bandwidth of the PXI bus limit the maximum sample rate that can be achieved, therefore limiting the maximum bandwidth of the phenomena that can be studied. Graphic processing units (GPU) are becoming an alternative for speeding up compute intensive kernels of scientific, imaging and simulation applications. However, integrating this technology into data acquisition systems is not a straight forward step, not to mention exploiting their parallelism efficiently. This paper discusses the use of GPUs with new high speed data bus interfaces to improve the performance of the self adaptive sampling rate data acquisition system installed on JET. Integration issues are discussed and performance evaluations are presented. © 2006 IEEE.
Original languageEnglish
Article number5873178
Pages (from-to)1714 - 1718
Number of pages5
JournalIEEE Transactions on Nuclear Science
Volume58
Issue number4 PART 1
DOIs
Publication statusPublished - Aug 2011
Externally publishedYes

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All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Nuclear Energy and Engineering
  • Nuclear and High Energy Physics

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