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• W893126783 abstract "This short note regards a comparison of instantaneous power, total energy consumption, execution time and energetic cost per synaptic event of a spiking neural network simulator (DPSNN-STDP) distributed on MPI processes when executed either on an (based on a dual socket quad-core ARM platform) or a (INTEL-based quad-core dual socket platform). We also compare the measure with those reported by leading custom and semi-custom designs: TrueNorth and SpiNNaker. In summary, we observed that: 1- we spent 2.2 micro-Joule per simulated event on the embedded platform, approx. 4.4 times lower than what was spent by the platform; 2- the instantaneous power consumption of the embedded platform was 14.4 times better than the server one; 3- the is a factor 3.3 faster. The embedded platform is made of NVIDIA Jetson TK1 boards, interconnected by Ethernet, each mounting a Tegra K1 chip including a quad-core ARM Cortex-A15 at 2.3GHz. The platform is based on dual-socket quad-core Intel Xeon CPUs (E5620 at 2.4GHz). The measures were obtained with the DPSNN-STDP simulator (Distributed Simulator of Polychronous Spiking Neural Network with synaptic Spike Timing Dependent Plasticity) developed by INFN, that already proved its efficient scalability and execution speed-up on hundreds of similar server cores and MPI processes, applied to neural nets composed of several billions of synapses." @default.
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• W893126783 date "2015-05-12" @default.
• W893126783 modified "2023-09-23" @default.
• W893126783 title "Power, Energy and Speed of Embedded and Server Multi-Cores applied to Distributed Simulation of Spiking Neural Networks: ARM in NVIDIA Tegra vs Intel Xeon quad-cores" @default.
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