high performance computing on graphics processing units: hgpu.org

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GPU-BLAST: Using graphics processors to accelerate protein sequence alignment

Panagiotis D. Vouzis, Nikolaos V. Sahinidis

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Tags: Bioinformatics, Biology, BLAST, CUDA, nVidia, Package, Sequence alignment, Tesla C2050

November 30, 2010 by hgpu

Parallel reconstruction of neighbor-joining trees for large multiple sequence alignments using CUDA

Yongchao Liu, Bertil Schmidt, Douglas L. Maskell

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

November 27, 2010 by hgpu

Performance Analysis of IBM Cell Broadband Engine on Sequence Alignment

Yang Song, Gregory M. Striemer, Ali Akoglu

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Tags: Bioinformatics, Biology, Cell processor, CUDA, nVidia, Sequence alignment, Smith-Waterman algorithm, Tesla C870

November 27, 2010 by hgpu

MSA-CUDA: Multiple Sequence Alignment on Graphics Processing Units with CUDA

Yongchao Liu, Bertil Schmidt, Douglas L. Maskell

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 280, Sequence alignment

November 21, 2010 by hgpu

Performance Analysis of General-Purpose Computation on Commodity Graphics Hardware: A Case Study Using Bioinformatics

Weiguo Liu, Bertil Schmidt, Wolfgang Muller-Wittig

Tags: Biology, Computer science, nVidia, Sequence alignment, Signal processing

November 7, 2010 by hgpu

Streaming Algorithms for Biological Sequence Alignment on GPUs

Weiguo Liu, Bertil Schmidt, Gerrit Voss, Wolfgang M. Wittig

Tags: Biology, Sequence alignment

November 3, 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

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

An efficient implementation of Smith Waterman algorithm on GPU using CUDA, for massively parallel scanning of sequence databases

Lukasz Ligowski, Witold Rudnicki

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Tags: Bioinformatics, Biology, Computational biology, Computer science, CUDA, nVidia, nVidia GeForce 9800 GX2, Sequence alignment, Smith-Waterman algorithm

October 28, 2010 by hgpu

CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignment

Svetlin Manavski, Giorgio Valle

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Tags: Bioinformatics, Biology, Computational biology, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Package, Sequence alignment, Smith-Waterman algorithm

October 28, 2010 by hgpu

Sequence alignment with GPU: Performance and design challenges

Gregory M. Striemer, Ali Akoglu

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Tags: Bioinformatics, Biology, Computational biology, Computer science, CUDA, nVidia, Package, Sequence alignment, Smith-Waterman algorithm, Tesla C870

October 27, 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

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high performance computing on graphics processing units: hgpu.org

GPU-BLAST: Using graphics processors to accelerate protein sequence alignment

Parallel reconstruction of neighbor-joining trees for large multiple sequence alignments using CUDA

Performance Analysis of IBM Cell Broadband Engine on Sequence Alignment

MSA-CUDA: Multiple Sequence Alignment on Graphics Processing Units with CUDA

Performance Analysis of General-Purpose Computation on Commodity Graphics Hardware: A Case Study Using Bioinformatics

Streaming Algorithms for Biological Sequence Alignment on GPUs

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

High-throughput sequence alignment using Graphics Processing Units

Optimizing data intensive GPGPU computations for DNA sequence alignment

An efficient implementation of Smith Waterman algorithm on GPU using CUDA, for massively parallel scanning of sequence databases

CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignment

Sequence alignment with GPU: Performance and design challenges

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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