high performance computing on graphics processing units: hgpu.org

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HCudaBLAST: an implementation of BLAST on Hadoop and Cuda

Nilay Khare, Alind Khare and Farhan Khan

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Tags: Algorithms, Bioinformatics, Biology, BLAST, CUDA, Hadoop, nVidia, nVidia Quadro 2000, nVidia Quadro 600, Tesla C2075

December 3, 2017 by hgpu

A Performance Model for Memory Bandwidth Constrained Applications on Graphics Engines

Lin Ma, Roger D. Chamberlain

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Tags: Biology, BLAST, Computational biology, CUDA, Hashing, nVidia, nVidia GeForce GTX 480, Performance

July 15, 2012 by hgpu

Accelerating Protein Sequence Search in a Heterogeneous Computing System

Shucai Xiao, Heshan Lin, Wu-chun Feng

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Tags: Algorithms, Bioinformatics, Biology, BLAST, Databases, Heterogeneous systems, nVidia, Optimization, Tesla C1060, Tesla C2050

November 23, 2011 by hgpu

The accelerating implementation of BLAST with stream processor

Gang Wei, Chao Ma, Songwen Pei, Baifeng Wu

Tags: ATI, ATI Radeon HD 4850, Bioinformatics, Biology, BLAST, Brook, Sequence alignment

June 15, 2011 by hgpu

GPU Based Parallel Computing on Blast Program

Huang Lican, Hu Ya

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Tags: Bioinformatics, Biology, BLAST, Sequence alignment

May 7, 2011 by hgpu

CUDA-BLASTP: Accelerating BLASTP on CUDA-Enabled Graphics Hardware

Weiguo Liu, Bertil Schmidt, Wolfgang Muller-Wittig

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Tags: Bioinformatics, Biology, BLAST, CUDA, nVidia, nVidia GeForce GTX 295, Package, Sequence alignment

April 18, 2011 by hgpu

CBESW: sequence alignment on the Playstation 3

Adrianto Wirawan, Chee Keong K. Kwoh, Nim Tri T. Hieu, Bertil Schmidt

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Tags: Algorithms, Bioinformatics, Biology, BLAST, Cell processor, CUDA, nVidia, nVidia GeForce 8800 GTX, Package, Playstation, Sequence alignment, Smith-Waterman algorithm

January 8, 2011 by hgpu

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

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

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high performance computing on graphics processing units: hgpu.org

HCudaBLAST: an implementation of BLAST on Hadoop and Cuda

A Performance Model for Memory Bandwidth Constrained Applications on Graphics Engines

Accelerating Protein Sequence Search in a Heterogeneous Computing System

The accelerating implementation of BLAST with stream processor

GPU Based Parallel Computing on Blast Program

CUDA-BLASTP: Accelerating BLASTP on CUDA-Enabled Graphics Hardware

CBESW: sequence alignment on the Playstation 3

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

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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