Name
Title | ||
|---|---|---|
Performance evaluation and scaling of a multiprocessor architecture emulating complex SNN algorithms |
Abstract | ||
|---|---|---|
The performance analysis of an efficient multiprocessor architecture that allows accelerating the emulation of large-scale Spiking Neural Networks (SNNs) is reported. After describing the architecture and the complex SNN algorithm mapping, the performance study demonstrates that the system can emulate up to 10,000 300-synapse neurons in real time at 64 MHz with conventional FPGAs. Important improvements can be achieved by using advanced technology and increased clock rate or by means of simple architecture modifications. The architecture is flexible enough to be efficiently applied to any SNN model in general. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-15323-5_13 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
performance analysis,complex snn algorithm mapping,simple architecture modification,conventional fpgas,300-synapse neuron,advanced technology,snn model,efficient multiprocessor architecture,performance evaluation,performance study,important improvement,real time,simd,spiking neural network,fpga,spiking neural networks | Multiprocessor architecture,Computer architecture,Architecture,Computer science,Algorithm,Field-programmable gate array,SIMD,Emulation,Spiking neural network,Scaling,Clock rate | Conference |
Volume | ISSN | ISBN |
6274 | 0302-9743 | 3-642-15322-4 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Giovanny Sánchez | 1 | 33 | 5.29 |
| Jordi Madrenas | 2 | 150 | 27.87 |
| Juan Manuel Moreno | 3 | 186 | 32.74 |