Abstract
This paper demonstrates the feasibility and evaluates the performance of using the SpiNNaker neuromorphic hardware to simulate traditional non-spiking multi-layer per-ceptron networks with the backpropagation learning rule. In addition to investigating the mapping of checker-boarding partitioning scheme onto SpiNNaker, we propose a new algorithm called pipelined checker-boarding partitioning which introduces a pipelined mode and captures the parallelism within each partition of the weight matrix, allowing the overlapping of communication and computation. Not only does the proposed algorithm localize communication, but it can also hide a part of or even all the communication. The performance is evaluated with SpiNNaker configurations up to 1000 nodes (20000 cores). © 2010 IEEE.
Original language | English |
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Title of host publication | 9th International Symposium on Parallel and Distributed Computing, ISPDC 2010|Int. Symp. Parallel Distrib. Comput., ISPDC |
Place of Publication | USA |
Publisher | IEEE |
Pages | 9-16 |
Number of pages | 7 |
ISBN (Print) | 9780769541204 |
DOIs | |
Publication status | Published - 2010 |
Event | 9th International Symposium on Parallel and Distributed Computing, ISPDC 2010 - Istanbul Duration: 1 Jul 2010 → … |
Conference
Conference | 9th International Symposium on Parallel and Distributed Computing, ISPDC 2010 |
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City | Istanbul |
Period | 1/07/10 → … |
Keywords
- Backpropagation
- Mapping
- Parallel
- Perceptron
- SpiNNaker