A Spiking Neural Simulator Integrating Event-Driven and Time-Driven Computation Schemes Using Parallel CPU-GPU Co-Processing: A Case Study.
Francisco NaverosNiceto R. LuqueJesús Alberto GarridoRichard R. CarrilloMancia AnguitaEduardo RosPublished in: IEEE Trans. Neural Networks Learn. Syst. (2015)
Keyphrases
- event driven
- parallel computation
- graphics processing units
- real time
- parallel implementation
- hebbian learning
- fuzzy cognitive maps
- general purpose
- parallel computing
- parallel programming
- parallel processing
- bio inspired
- gpu implementation
- processing units
- test bed
- parallel algorithm
- shared memory
- graphics processors
- pc cluster
- information delivery
- parallel computers
- parallel architecture
- multithreading
- neuron model
- computation intensive
- processing elements
- evolutionary robotics
- publish subscribe
- neural network
- memory bandwidth
- spiking neural networks
- graphics hardware
- learning rules
- cpu implementation
- compute unified device architecture
- network architecture
- computing systems
- level parallelism
- massively parallel
- data transfer
- spike trains
- biologically plausible
- markup language
- high performance computing
- parallel architectures
- distributed memory
- high volume
- cluster of workstations
- event streams
- floating point
- multi core processors
- associative memory
- single instruction multiple data
- graphic processing unit