Title |
Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers
|
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Published in |
Frontiers in Neuroinformatics, February 2018
|
DOI | 10.3389/fninf.2018.00002 |
Pubmed ID | |
Authors |
Jakob Jordan, Tammo Ippen, Moritz Helias, Itaru Kitayama, Mitsuhisa Sato, Jun Igarashi, Markus Diesmann, Susanne Kunkel |
Abstract |
State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 12 | 24% |
Spain | 2 | 4% |
India | 1 | 2% |
Germany | 1 | 2% |
Austria | 1 | 2% |
Netherlands | 1 | 2% |
Israel | 1 | 2% |
Japan | 1 | 2% |
Chile | 1 | 2% |
Other | 3 | 6% |
Unknown | 27 | 53% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 37 | 73% |
Scientists | 12 | 24% |
Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 169 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 38 | 22% |
Researcher | 25 | 15% |
Student > Master | 19 | 11% |
Student > Bachelor | 13 | 8% |
Other | 12 | 7% |
Other | 32 | 19% |
Unknown | 30 | 18% |
Readers by discipline | Count | As % |
---|---|---|
Neuroscience | 37 | 22% |
Computer Science | 32 | 19% |
Engineering | 17 | 10% |
Agricultural and Biological Sciences | 11 | 7% |
Physics and Astronomy | 8 | 5% |
Other | 33 | 20% |
Unknown | 31 | 18% |