Benchmarking of Neuromorphic Hardware Systems

Autor:	Christian Klarhorst, Ulrich Rückert, Michael Thies, Christoph Ostrau
Jazyk:	angličtina
Předmět:	Spiking neural network Emulation Quantitative Biology::Neurons and Cognition Performance estimation Computer science Computer Science::Neural and Evolutionary Computation 02 engineering and technology Benchmarking neuromorphic computing 020202 computer hardware & architecture Acceleration benchmark Computer Science::Emerging Technologies Computer architecture Neuromorphic engineering spiking neural networks 0202 electrical engineering electronic engineering information engineering Benchmark (computing) 020201 artificial intelligence & image processing Computer Science::Operating Systems Neuromorphic hardware
Zdroj:	Proceedings of the Neuro-inspired Computational Elements Workshop NICE
DOI:	10.1145/3381755.3381772
Popis:	With more and more neuromorphic hardware systems for the accel- eration of spiking neural networks available in science and industry, there is a demand for platform comparison and performance esti- mation of such systems. This work describes selected benchmarks implemented in a framework with exactly this target: independent black-box benchmarking and comparison of platforms suitable for the simulation/emulation of spiking neural networks.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3008140b19dee7412a021b6ad2df61a8 Zobrazit plný text záznamu