high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Biology

CUDAlign: using GPU to accelerate the comparison of megabase genomic sequences

Edans Flavius O. Sandes, Alba Cristina M.A. de Melo

Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 280, Sequence alignment, Smith-Waterman algorithm

February 27, 2011 by hgpu

Size Matters: Space/Time Tradeoffs to Improve GPGPU Applications Performance

Abdullah Gharaibeh, Matei Ripeanu

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Tags: Bioinformatics, Biology, Computational biology, CUDA, nVidia, nVidia GeForce 8800 GTX, Package, Sequence alignment, Short read mapping, Suffix trees

February 27, 2011 by hgpu

HexServer: an FFT-based protein docking server powered by graphics processors

Gary Macindoe, Lazaros Mavridis, Vishwesh Venkatraman, Marie-Dominique Devignes, David W. Ritchie

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Tags: Bioinformatics, Biology, CUDA, FFT, Molecular simulation, nVidia, Tesla C1060

February 25, 2011 by hgpu

A Resource-Efficient Computing Paradigm for Computational Protein Modeling Applications

Yaohang Li, Douglas Wardell, Vincent Freeh

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Tags: Algorithms, Biology, Molecular dynamics

February 24, 2011 by hgpu

Probing biomolecular machines with graphics processors

James C. Phillips, John E. Stone

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Tags: Biology, Biomolecules, CUDA, GPU cluster, Molecular simulation, nVidia, OpenCL, Review, Tesla S1070

February 23, 2011 by hgpu

Accelerating the Stochastic Simulation Algorithm

David Jenkins, Gregory D. Peterson

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Tags: Biology, CUDA, Monte Carlo simulation, MPI, nVidia, Stochastic simulation, Tesla C870

February 21, 2011 by hgpu

A massively parallel framework using P systems and GPUs

Jose M. Cecilia, Gines D. Guerrero, Jose M. Garcia, Miguel A. Martinez-del-Amor, Ignacio Perez-Hurtado, Mario J. Perez-Jimenez

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Tags: Biology, Computer science, CUDA, nVidia, P systems, Tesla C1060

February 21, 2011 by hgpu

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

AutoDock-GPU: AutoDock for GPUs and other accelerators

Architecting Tensor Core-Based Reductions for Irregular Molecular Docking Kernels

NCCLX: collective communication framework

Collective Communication for 100k+ GPUs

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

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high performance computing on graphics processing units: hgpu.org

Applications

CUDAlign: using GPU to accelerate the comparison of megabase genomic sequences

Size Matters: Space/Time Tradeoffs to Improve GPGPU Applications Performance

HexServer: an FFT-based protein docking server powered by graphics processors

A Resource-Efficient Computing Paradigm for Computational Protein Modeling Applications

Probing biomolecular machines with graphics processors

Accelerating the Stochastic Simulation Algorithm

A massively parallel framework using P systems and GPUs

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

Recent source codes

AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

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