Pellegrini, A.; Montañola-Sales, C.; Quaglia, F.; Casanovas, J. Lecture notes in computer science (Online) Vol. 10104, p. 334-346 DOI: 10.1007/978-3-319-58943-5_27 Data de publicació: 2017 Article en revista
Execution parallelism in agent-Based Simulation (ABS) allows to deal with complex/large-scale models. This raises the need for runtime environments able to fully exploit hardware parallelism, while jointly offering ABS-suited programming abstractions. In this paper, we target last-generation Parallel Discrete Event Simulation (PDES) platforms for multicore systems. We discuss a programming model to support both implicit (in-place access) and explicit (message passing) interactions across concurrent Logical Processes (LPs). We discuss different load-sharing policies combining event rate and implicit/explicit LPs’ interactions. We present a performance study conducted on a synthetic test case, representative of a class of agent-based models.
Sanchez, G.; Madrenas, J.; Moreno, J. Lecture notes in computer science (Online) Vol. Special ICES 2010, num. 6274, p. 145-156 DOI: 10.1007/978-3-642-15323-5_13 Data de publicació: 2010-09 Article en revista
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.