high performance computing on graphics processing units: hgpu.org

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Enhancing the simulation of P systems for the SAT problem on GPUs

J.M. Cecilia, J.M. Garcia, G.D. Guerrero, M.A. Martinez-Amor, M.J. Perez-Jimenez, M. Ujaldon

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Tags: Biology, CUDA, nVidia, P systems, SAT, Tesla C1060

February 16, 2011 by hgpu

Accelerating the Stochastic Simulation Algorithm using Emerging Architectures

David Dewayne Jenkins

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Tags: Biology, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce 8600 M, Stochastic simulation, Tesla C1060, Tesla C870, Thesis

February 16, 2011 by hgpu

GPU Accelerated Stochastic Simulation

David D. Jenkins, Gregory D. Peterson

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Tags: Biology, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, Stochastic simulation, Tesla C1060

February 16, 2011 by hgpu

GPU-powered tools boost molecular visualization

Matthieu Chavent, Bruno Levy, Michael Krone, Katrin Bidmon, Jean-Philippe P. Nomine, Thomas Ertl, Marc Baaden

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Tags: Bioinformatics, Biology, Molecular modeling, nVidia, Review, Visualization

February 12, 2011 by hgpu

Next-generation acceleration and code optimization for light transport in turbid media using GPUs

Erik Alerstam, William C. Yip Lo, Tianyi D. Han, Jonathan Rose, Stefan Andersson-Engels, Lothar Lilge

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Tags: Biology, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, nVidia GeForce GTX 480, Optics, Package

February 9, 2011 by hgpu

Two Level Approach to Efficient Visualization of Protein Dynamics

Ove Daae Lampe, Ivan Viola, Nathalie Reuter, Helwig Hauser

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Tags: Biology, Molecular dynamics, nVidia, nVidia GeForce 8800 GTX, OpenGL, Visualization

February 4, 2011 by hgpu

Efficient Bayesian inference in stochastic chemical kinetic models using graphical processing units

Jarad Niemi, Matthew Wheeler

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Tags: Bayesian, Biology, Chemistry, CUDA, nVidia, Stochastic simulation, Tesla T10

January 26, 2011 by hgpu

Energy efficient biomolecular simulations with FPGA-based reconfigurable computing

Ananth Nallamuthu, Melissa C. Smith, Scott Hampton, Pratul K. Agarwal, Sadaf R. Alam

Tags: Bioinformatics, Biology, FPGA, Molecular dynamics

January 19, 2011 by hgpu

Towards microsecond biological molecular dynamics simulations on hybrid processors

Scott Hampton, Pratul K. Agarwal, Sadaf R. Alam, Paul S. Crozier

Tags: Bioinformatics, Biology, CUDA, Molecular dynamics, nVidia, Tesla C1060, Tesla C2050

January 19, 2011 by hgpu

Optimal Utilization of Heterogeneous Resources for Biomolecular Simulations

Scott S. Hampton, Sadaf R. Alam, Paul S. Crozier, Pratul K. Agarwal

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Tags: Bioinformatics, Biology, CUDA, Molecular dynamics, nVidia, Tesla C1060, Tesla C2050

January 19, 2011 by hgpu

Fast Genetic Programming on GPUs

Simon Harding, Wolfgang Banzhaf

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Tags: Bioinformatics, Biology, DirectX, Genetics, nVidia, nVidia GeForce 7300

January 15, 2011 by hgpu

GPU accelerated biochemical network simulation

Yanxiang Zhou, Juliane Liepe, Xia Sheng, Michael P. H. Stumpf, Chris Barnes

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Tags: Bioinformatics, Biology, CUDA, GPU cluster, nVidia, Package, Tesla C2050

January 13, 2011 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Enhancing the simulation of P systems for the SAT problem on GPUs

Accelerating the Stochastic Simulation Algorithm using Emerging Architectures

GPU Accelerated Stochastic Simulation

GPU-powered tools boost molecular visualization

Next-generation acceleration and code optimization for light transport in turbid media using GPUs

Two Level Approach to Efficient Visualization of Protein Dynamics

Efficient Bayesian inference in stochastic chemical kinetic models using graphical processing units

Energy efficient biomolecular simulations with FPGA-based reconfigurable computing

Towards microsecond biological molecular dynamics simulations on hybrid processors

Optimal Utilization of Heterogeneous Resources for Biomolecular Simulations

Fast Genetic Programming on GPUs

GPU accelerated biochemical network simulation

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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