high performance computing on graphics processing units: hgpu.org

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Monte Carlo randomization tests for large-scale abundance datasets on the GPU

John L. Van Hemert, Julie A. Dickerson

Tags: Bioinformatics, Biology, CUDA, Medicine, Metabolomics, Monte Carlo simulation, Next-Generation sequencing, nVidia

November 8, 2010 by hgpu

Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS

Casey S. Greene, Nicholas A. Sinnott-Armstrong, Daniel S. Himmelstein, Paul J. Park, Jason H. Moore, Brent T. Harris

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Tags: Bioinformatics, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 295, Package

November 7, 2010 by hgpu

Accelerating epistasis analysis in human genetics with consumer graphics hardware

Nicholas S. Armstrong, Casey Greene, Fabio Cancare, Jason Moore

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Tags: Bioinformatics, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 280

November 7, 2010 by hgpu

CUDASW++ 2.0: enhanced Smith-Waterman protein database search on CUDA-enabled GPUs based on SIMT and virtualized SIMD abstractions

Yongchao Liu, Bertil Schmidt, Douglas Maskell

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Tags: Bioinformatics, Biology, Computational biology, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, Package, Smith-Waterman algorithm

November 6, 2010 by hgpu

CUDASW++: optimizing Smith-Waterman sequence database searches for CUDA-enabled graphics processing units

Yongchao Liu, Douglas Maskell, Bertil Schmidt

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Tags: Bioinformatics, Biology, Computational biology, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, Package, Smith-Waterman algorithm

November 4, 2010 by hgpu

Molecular Simulation of ab Initio Protein Folding for a Millisecond Folder NTL9(1-39)

Vincent A. Voelz, Gregory R. Bowman, Kyle Beauchamp, Vijay S. Pande

Tags: Bioinformatics, Biology, Chemistry, Molecular dynamics

November 4, 2010 by hgpu

Fast and accurate protein substructure searching with simulated annealing and GPUs

Alex D. Stivala, Peter J. Stuckey, Anthony I. Wirth

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Tags: Bioinformatics, Biological Physics, Biology, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 285, Package, Tesla C1060

November 2, 2010 by hgpu

GPU-ClustalW: Using Graphics Hardware to Accelerate Multiple Sequence Alignment

Weiguo Liu, Bertil Schmidt, Gerrit Voss, Wolfgang Müller-Wittig

Tags: Bioinformatics, Biology, Computational biology, Computer science, Sequence alignment

November 1, 2010 by hgpu

GPU Accelerated Smith-Waterman

Yang Liu, Wayne Huang, John Johnson, Sheila Vaidya

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Tags: Bioinformatics, Biology, Computational biology, Computer science, GLSL, nVidia, nVidia GeForce 7800 GTX, OpenGL, Smith-Waterman algorithm

November 1, 2010 by hgpu

High-throughput sequence alignment using Graphics Processing Units

Michael Schatz, Cole Trapnell, Arthur Delcher, Amitabh Varshney

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Tags: Bioinformatics, Biology, Computational biology, CUDA, nVidia, nVidia GeForce 8800 GTX, Package, Sequence alignment

November 1, 2010 by hgpu

Optimizing data intensive GPGPU computations for DNA sequence alignment

Cole Trapnell, Michael C. Schatz

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

October 30, 2010 by hgpu

Exploiting graphics processing units for computational biology and bioinformatics

Joshua L. Payne, Nicholas A. Sinnott-Armstrong, Jason H. Moore

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Tags: All-Pairs Distance, Bioinformatics, Biology, Computational biology, CUDA, nVidia, nVidia GeForce 9600 M, Package

October 30, 2010 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

Monte Carlo randomization tests for large-scale abundance datasets on the GPU

Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS

Accelerating epistasis analysis in human genetics with consumer graphics hardware

CUDASW++ 2.0: enhanced Smith-Waterman protein database search on CUDA-enabled GPUs based on SIMT and virtualized SIMD abstractions

CUDASW++: optimizing Smith-Waterman sequence database searches for CUDA-enabled graphics processing units

Molecular Simulation of ab Initio Protein Folding for a Millisecond Folder NTL9(1-39)

Fast and accurate protein substructure searching with simulated annealing and GPUs

GPU-ClustalW: Using Graphics Hardware to Accelerate Multiple Sequence Alignment

GPU Accelerated Smith-Waterman

High-throughput sequence alignment using Graphics Processing Units

Optimizing data intensive GPGPU computations for DNA sequence alignment

Exploiting graphics processing units for computational biology and bioinformatics

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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