214 citations · 222 across the 6 of their papers we have counts for
10 papers
Efficient Distributed Transposition Of Large-Scale Multigraphs And High-Cardinality Sparse Matrices
Bruno Magalhaes, Felix Schürmann
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-…
Fully-Asynchronous Fully-Implicit Variable-Order Variable-Timestep Simulation of Neural Networks
Bruno Magalhães, Michael Hines, Thomas Sterling +1
State-of-the-art simulations of detailed neural models follow the Bulk Synchronous Parallel execution model. Execution is divided in equidistant communication intervals, equivalent…
The scientific case for brain simulations
Gaute T. Einevoll, Alain Destexhe, Markus Diesmann +7
A key element of the European Union's Human Brain Project (HBP) and other large-scale brain research projects is simulation of large-scale model networks of neurons. Here we argue…
An optimizing multi-platform source-to-source compiler framework for the NEURON MODeling Language
Pramod Kumbhar, Omar Awile, Liam Keegan +4
Domain-specific languages (DSLs) play an increasingly important role in the generation of high performing software. They allow the user to exploit specific knowledge encoded in the…
CoreNEURON : An Optimized Compute Engine for the NEURON Simulator
Pramod Kumbhar, Michael Hines, Jeremy Fouriaux +4
The NEURON simulator has been developed over the past three decades and is widely used by neuroscientists to model the electrical activity of neuronal networks. Large network simul…
Analytic Performance Modeling and Analysis of Detailed Neuron Simulations
Francesco Cremonesi, Georg Hager, Gerhard Wellein +1
Big science initiatives are trying to reconstruct and model the brain by attempting to simulate brain tissue at larger scales and with increasingly more biological detail than prev…