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Graph-based representations underlie a wide range of scientific problems. Graph connectivity is typically represented as a sparse matrix in the Compressed Sparse Row format. Large-scale graphs rely on distributed storage, allocating distinct subsets of row ...
Exposing parallelism in scientific applications has become a core requirement for efficiently running on modern distributed multicore SIMD compute architectures. The granularity of parallelism that can be attained is a key determinant for the achievable ac ...
IEEE2019
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State-of-the-art simulations of detailed neurons follow the Bulk Synchronous Parallel execution model. Execution is divided in equidistant communication intervals, with parallel neurons interpolation and collective communication guiding synchronization. Su ...
2020
Simulations of the electrical activity of networks of morphologically-detailed neuron models allow for a better understanding of the brain.
Short time to solution is critical in order to study long biological processes such as synaptic plasticity and learn ...
