DocumentCode :
3684872
Title :
Highly scalable parallel processing of extracellular recordings of Multielectrode Arrays
Author :
Tiago V. Gehring;Eleni Vasilaki;Michele Giugliano
Author_Institution :
Department of Computer Science, University of Sheffield, UK
fYear :
2015
Firstpage :
4178
Lastpage :
4181
Abstract :
Technological advances of Multielectrode Arrays (MEAs) used for multisite, parallel electrophysiological recordings, lead to an ever increasing amount of raw data being generated. Arrays with hundreds up to a few thousands of electrodes are slowly seeing widespread use and the expectation is that more sophisticated arrays will become available in the near future. In order to process the large data volumes resulting from MEA recordings there is a pressing need for new software tools able to process many data channels in parallel. Here we present a new tool for processing MEA data recordings that makes use of new programming paradigms and recent technology developments to unleash the power of modern highly parallel hardware, such as multi-core CPUs with vector instruction sets or GPGPUs. Our tool builds on and complements existing MEA data analysis packages. It shows high scalability and can be used to speed up some performance critical pre-processing steps such as data filtering and spike detection, helping to make the analysis of larger data sets tractable.
Keywords :
"Hardware","Runtime","Programming","Kernel","Arrays","Standards"
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
ISSN :
1094-687X
Electronic_ISBN :
1558-4615
Type :
conf
DOI :
10.1109/EMBC.2015.7319315
Filename :
7319315
Link To Document :
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