Sep 2 – 9, 2007
Victoria, Canada
Europe/Zurich timezone
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Data access performance through parallelization and vectored access. Some results.

Sep 6, 2007, 3:40 PM
20m
Saanich (Victoria, Canada)

Saanich

Victoria, Canada

oral presentation Distributed data analysis and information management Distributed data analysis and information management

Speaker

Mr Fabrizio Furano (INFN sez. di Padova)

Description

HEP data processing and analysis applications typically deal with the problem of accessing and processing data at high speed. Recent study, development and test work has shown that the latencies due to data access can often be hidden by parallelizing them with the data processing, thus giving the ability to have applications which process remote data with a high level of efficiency. Techniques and algorithms able to reach this result have been implemented in the client side of the Scalla/xrootd system, and in this contribution we also describe the results of some tests done in order to compare their performance and characteristics. These techniques, if used together with multiple streams data access, can also be effective in making possible to efficiently and transparently deal with data repositories accessible via a Wide Area Network.

Primary author

Mr Fabrizio Furano (INFN sez. di Padova)

Co-author

Mr Andrew Hanushevsky (SLAC - Stanford Linear Accelerator Center)

Presentation materials