Biologically accurate neuron simulations are increasingly important in research related to brain activity. They are computationally intensive and feature data and task parallelism. In this paper, we present a case study for the mapping of a biologically accurate inferior-olive (InfOli), neural cell simulator on an many-core research platform. The Single-Chip Cloud Computer (SCC) is an experimental processor created by Intel Labs. The target neurons provide a major input to the cerebellum and are involved in motor skills and space perception. We exploit task-and data-partitioning, scaling the simulation over more than 40,000 neurons. The voltage-and frequency-scaling capabilities of the chip are explored, achieving more than 20% energy savings with negligible performance degradation. Four platform configurations are evaluated and a mapping with balanced workload and constant voltage and frequency is formally derived as optimal.
|Title of host publication||Proceedings - International Conference on Embedded Computer Systems|
|Subtitle of host publication||Architectures, Modeling and Simulation, SAMOS 2014|
|Editors||Alexander V. Veidenbaum, Carlo Galuzzi|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||8|
|Publication status||Published - 2014|
|Event||14th International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation, SAMOS 2014 - Samos, Greece|
Duration: 14 Jul 2014 → 17 Jul 2014
|Series||Proceedings - International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation, SAMOS 2014|
|Conference||14th International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation, SAMOS 2014|
|Period||14/07/14 → 17/07/14|
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