We explore two different threading approaches on a graphics processing unit (GPU) exploiting two different characteristics of the current GPU architecture. The fat thread approach tries to minimize data access time by relying on shared memory and registers potentially sacrificing parallelism. The thin thread approach maximizes parallelism and tries to hide access latencies. We apply these two approaches to the parallel stochastic simulation of chemical reaction systems using the stochastic simulation algorithm (SSA) by Gillespie [14]. In these cases, the proposed thin thread approach shows comparable performance while eliminating the limitation of the reaction system's size. © 2006 IEEE
Many applications with regular parallelism have been shown to benefit from using Graphics Processing...
Best paper awardInternational audienceStochastic simulations need multiple replications in order to ...
Abstract—Through computational methods, biologists are able learn more about molecular biology by bu...
We explore two different threading approaches on a graphics processing unit (GPU) exploiting two dif...
We explore two different threading approaches on a graphics processing unit (GPU) exploiting two dif...
We explore two different threading approaches on a graphics processing unit (GPU) exploiting two dif...
vs. thin threading approach on GPUs: application to stochastic simulation of chemical reaction
The Gillespie Stochastic Simulation Algorithm (GSSA) and its variants are cornerstone techniques to ...
<div><p>The Gillespie Stochastic Simulation Algorithm (GSSA) and its variants are cornerstone techni...
Stochastic simulations of biochemical reaction networks can be computationally expensive on Central ...
For systems made up of a small number of molecules, such as a biochemical network in a single cell, ...
The small number of some reactant molecules in biological systems formed by living cells can result ...
The small number of some reactant molecules in biological systems formed by living cells can result ...
The most commonly used approach for solving reaction–diffusion systems relies upon stencil computati...
Graphical processing units (GPUs) have recently attracted attention for scientific applications such...
Many applications with regular parallelism have been shown to benefit from using Graphics Processing...
Best paper awardInternational audienceStochastic simulations need multiple replications in order to ...
Abstract—Through computational methods, biologists are able learn more about molecular biology by bu...
We explore two different threading approaches on a graphics processing unit (GPU) exploiting two dif...
We explore two different threading approaches on a graphics processing unit (GPU) exploiting two dif...
We explore two different threading approaches on a graphics processing unit (GPU) exploiting two dif...
vs. thin threading approach on GPUs: application to stochastic simulation of chemical reaction
The Gillespie Stochastic Simulation Algorithm (GSSA) and its variants are cornerstone techniques to ...
<div><p>The Gillespie Stochastic Simulation Algorithm (GSSA) and its variants are cornerstone techni...
Stochastic simulations of biochemical reaction networks can be computationally expensive on Central ...
For systems made up of a small number of molecules, such as a biochemical network in a single cell, ...
The small number of some reactant molecules in biological systems formed by living cells can result ...
The small number of some reactant molecules in biological systems formed by living cells can result ...
The most commonly used approach for solving reaction–diffusion systems relies upon stencil computati...
Graphical processing units (GPUs) have recently attracted attention for scientific applications such...
Many applications with regular parallelism have been shown to benefit from using Graphics Processing...
Best paper awardInternational audienceStochastic simulations need multiple replications in order to ...
Abstract—Through computational methods, biologists are able learn more about molecular biology by bu...