TY - GEN
T1 - Towards an optimized multi FPGA architecture with STDM network
T2 - 14th International Symposium on Applied Reconfigurable Computing, ARC 2018
AU - Hironaka, Kazuei
AU - Doan, Ng Anh Vu
AU - Amano, Hideharu
N1 - Funding Information:
Acknowledgments. This paper is based on results obtained from a project commissioned by the New Energy and Industrial Technology Development Organization (NEDO).
Publisher Copyright:
© Springer International Publishing AG, part of Springer Nature 2018.
PY - 2018
Y1 - 2018
N2 - In this work, we propose a multi FPGA architecture with STDM network that aims to tackle compute-intensive applications such as neural networks training or pattern recognition in artificial intelligence while realizing high cost-performance and energy efficiency. To achieve this goal, optimizing different aspects of the system communication is a key challenge. In order to do this, a preliminary study on the application mapping for both the execution time and the number of slots for the STDM is carried out. An optimization based on a multi-criteria paradigm is implemented and the preliminary results show the possibility to optimize several parameters of the communication simultaneously alongside quantitative analyses of different architecture choices.
AB - In this work, we propose a multi FPGA architecture with STDM network that aims to tackle compute-intensive applications such as neural networks training or pattern recognition in artificial intelligence while realizing high cost-performance and energy efficiency. To achieve this goal, optimizing different aspects of the system communication is a key challenge. In order to do this, a preliminary study on the application mapping for both the execution time and the number of slots for the STDM is carried out. An optimization based on a multi-criteria paradigm is implemented and the preliminary results show the possibility to optimize several parameters of the communication simultaneously alongside quantitative analyses of different architecture choices.
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U2 - 10.1007/978-3-319-78890-6_12
DO - 10.1007/978-3-319-78890-6_12
M3 - Conference contribution
AN - SCOPUS:85046261161
SN - 9783319788890
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 142
EP - 150
BT - Applied Reconfigurable Computing
A2 - Voros, Nikolaos
A2 - Keramidas, Georgios
A2 - Antonopoulos, Christos
A2 - Huebner, Michael
A2 - Diniz, Pedro C.
A2 - Goehringer, Diana
PB - Springer Verlag
Y2 - 2 May 2018 through 4 May 2018
ER -
