Conference proceeding
CARLsim 6: An Open Source Library for Large-Scale, Biologically Detailed Spiking Neural Network Simulation
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings
01 Jan 2022
Abstract
Conference Title: 2022 International Joint Conference on Neural Networks (IJCNN) Conference Start Date: 2022, July 18 Conference End Date: 2022, July 23 Conference Location: Padua, ItalyMature simulation systems for Spiking Neural Networks (SNNs) become more relevant than ever for understanding the brain and supporting neuromorphic computing. The CARL-sim SNN platform is one of the first Open Source simulation systems that utilized CUDA GPUs to address the tremendous parallel processing demands of natural brains. It has evolved over almost a decade in numerous scientific research projects requiring efficient biologically plausible modeling at scale. With its sixth major release, CARLsim 6 respects this legacy by supporting the latest versions of operating systems, development tool chains, multi-core computers, and of course GPUs. It runs on a range of platforms; from Notebooks up to the NVIDIA DGX-A100 supercomputer, and is used in biologically plausible simulations of the hippocampus and neocortex. The latest version has added flexibility for incorporating long-term and short-term synaptic plasticity. Neuromodulation is an important property of neurobiology that can lead to rapid few shot learning, network rewiring, and neural activity modulation. Because of this, CARLsim 6 now supports four multiple neuromodulators for simulating neural excitability and synaptic plasticity.
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Details
- Title
- CARLsim 6: An Open Source Library for Large-Scale, Biologically Detailed Spiking Neural Network Simulation
- Creators
- Lars NiedermeierKexin ChenJinwei XingAnup DasJeffrey KopsickEric ScottNate SuttonKillian WeberNikil DuttKenneth Chen - Digital Media
- Publication Details
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings
- Publisher
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Digital Media; Electrical and Computer Engineering
- Web of Science ID
- WOS:000867070906028
- Scopus ID
- 2-s2.0-85140756274
- Other Identifier
- 991019182766104721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Hardware & Architecture
- Engineering, Electrical & Electronic
- Neurosciences