Efficient sparse matrix-delayed vector multiplication for discretized neural field model

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F18%3A00102136" target="_blank" >RIV/00216224:14610/18:00102136 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/s11227-017-2194-4" target="_blank" >https://doi.org/10.1007/s11227-017-2194-4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s11227-017-2194-4" target="_blank" >10.1007/s11227-017-2194-4</a>

Result language
angličtina
Original language name
Efficient sparse matrix-delayed vector multiplication for discretized neural field model
Original language description
Computational models of the human brain provide an important tool for studying the principles behind brain function and disease. To achieve whole-brain simulation, models are formulated at the level of neuronal populations as systems of delayed differential equations. In this paper, we show that the integration of large systems of sparsely connected neural masses is similar to well-studied sparse matrix-vector multiplication; however, due to delayed contributions, it differs in the data access pattern to the vectors. To improve data locality, we propose a combination of node reordering and tiled schedules derived from the connectivity matrix of the particular system, which allows performing multiple integration steps within a tile. We present two schedules: with a serial processing of the tiles and one allowing for parallel processing of the tiles. We evaluate the presented schedules showing speedup up to 2x on single-socket CPU, and 1.25x on Xeon Phi accelerator.
Czech name
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Czech description
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Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
<a href="/en/project/EF16_013%2F0001802" target="_blank" >EF16_013/0001802: CERIT Scientific Cloud</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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