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CoreNEURON: Performance and Energy Efficiency Evaluation on Intel and Arm CPUs

Joel Criado, Marta Garcia-Gasulla, Pramod Kumbhar, Omar Awile, Ioannis Magkanaris, Filippo Mantovani
2020 2020 IEEE International Conference on Cluster Computing (CLUSTER)  
Specifically, by using newly developed NMODL source to source compiler framework [5] with ISPC backend [6], we analyzed different performance metrics to evaluate Intel  ...  Analyzing and optimizing such simulation software's performance on different hardware platforms is essential for delivering scientific results faster, and reducing the computational cost of such large  ...  In this paper, we focus on evaluating CoreNEURON on two HPC systems powered by Intel and Arm architectures.  ... 
doi:10.1109/cluster49012.2020.00077 dblp:conf/cluster/CriadoGAMM20 fatcat:yqzca6mwtje6tg6jpxputxlpni

Code Generation in Computational Neuroscience: A Review of Tools and Techniques

Inga Blundell, Romain Brette, Thomas A. Cleland, Thomas G. Close, Daniel Coca, Andrew P. Davison, Sandra Diaz-Pier, Carlos Fernandez Musoles, Padraig Gleeson, Dan F. M. Goodman, Michael Hines, Michael W. Hopkins (+17 others)
2018 Frontiers in Neuroinformatics  
Independently of the model complexity, all modeling methods crucially depend on an efficient and accurate transformation of mathematical model descriptions into efficiently executable code.  ...  The second is to allow model definitions in a high level interpreted language, although this may limit performance.  ...  The work by AM, DP, IB and JE on NESTML and the work by GT is funded by the Excellence Initiative of the German federal and state governments and the Jülich Aachen Research Alliance High-Performance Computing  ... 
doi:10.3389/fninf.2018.00068 pmid:30455637 pmcid:PMC6230720 fatcat:u2hxo6y46jcwpbkq7zbmdtgeuq