From the Big Bang to Massive Data Flow: Parallel Computing in High Energy Physics Experiments

Autor:	J. Berger, D. Flierl, T.M. Steinbeck, M. W. Schulz, C. Struck, A. Vestbo, Arne Wiebalck, C. Adler, Kjetil Ullaland, J. S. Lange, H. K. Sollveit, D. Schmischke, R. Stock, Volker Lindenstruth, J. Lien, Dieter Røhrich, H. Helstrup, Bernhard Skaali
Rok vydání:	2001
Předmět:	Data flow diagram Parallel processing (DSP implementation) Computer science Feature extraction Bandwidth (computing) Vector quantization Signal compression Parallel computing Data modeling Data compression
Zdroj:	Applied Parallel Computing. New Paradigms for HPC in Industry and Academia ISBN: 9783540417293 PARA
DOI:	10.1007/3-540-70734-4_39
Popis:	Tracking detectors in high-energy physics experiments produce hundreds of megabytes of data at a rate of several hundred Hz. Processing this data at a bandwidth of 10-20 Gbyte/sec requires parallel computing. Reducing the huge data rate to a manageable amount by realtime data compression and pattern recognition techniques is the prime task. Clustered SMP (Symmetric Multi-Processor) nodes, based on off-the-shelf PCs and connected by a high bandwidth, low latency network, provide the necessary computing power. Such a system can easily be interfaced to the front-end electronics of the detectors via the internal PCI-bus. Data compression techniques like vector quantization and data modeling and fast transformations like conformal mapping or the adaptive, generalized Hough-transform for feature extraction are the methods of choice.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::8f4268b54f1be05a5abb456c3a2ca5e5 https://doi.org/10.1007/3-540-70734-4_39 Zobrazit plný text záznamu