RT Conference Proceedings
T1 Exploiting stream parallelism of MRI reconstruction using GrPPI over multiple back-ends
A1 García Blas, Francisco Javier
A1 Río Astorga, David del
A1 García Sánchez, José Daniel
A1 Carretero Pérez, Jesús
AB In recent years, on-line processing of data streams has been established as a major computing paradigm. This is due mainly to two reasons: first, more and more data are generated in near real-time that need to be processed; the second reason is given by the need of efficient parallel applications. However, the above-mentioned areas expose a tough challenge over traditional data-analysis techniques, which have been forced to evolve to a stream perspective. In this work we present an comparative study of a stream-aware multi-staged application, which has been implemented using GrPPI, a generic and reusable parallel pattern interface for C++ applications. We demonstrate the benefits of using this interface in terms of programability, performance, and scalability.
PB IEEE
SN 978-1-7281-0912-1
YR 2019
FD 2019-07-04
LK https://hdl.handle.net/10016/29675
UL https://hdl.handle.net/10016/29675
LA eng
NO Proceeding of: 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), Larnaca, Cyprus, 14-17 May 2019
NO ASPIDE: Exascale programIng models for extreme data processing
NO This work was supported by the EU project “ASPIDE: Exascale Programing Models for Extreme Data Processing” under grant 801091
DS e-Archivo
RD 18 jul. 2024