high performance computing on graphics processing units: hgpu.org

Tommaso Biagini, Giovanni Chillemi, Gianluigi Mazzoccoli, Alessandro Grottesi, Caterina Fusilli, Daniele Capocefalo, Stefano Castellana, Angelo Luigi Vescovi, Tommaso Mazza

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Tags: Benchmarking, Bioinformatics, Biology, Chemistry, CUDA, Genomics, Molecular dynamics, nVidia, OpenCL, Physics, Tesla C2070

December 19, 2017 by hgpu

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 Hybrid-parallel Architecture for Applications in Bioinformatics

Jan Christian Kassens

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Tags: Algorithms, Bioinformatics, Biology, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 780 Ti, Thesis

December 3, 2017 by hgpu

High Performance Streaming Smith-Waterman Implementation with Implicit Synchronization on Intel FPGA using OpenCL

Ernst Joachim Houtgast, Vlad-Mihai Sima, Zaid Al-Ars

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Tags: Algorithms, Bioinformatics, Biology, FPGA, OpenCL, Smith-Waterman algorithm

November 26, 2017 by hgpu

Accelerating Genomics Research with OpenCL and FPGAs

Chris Rauer, George S. Powley, Mir Ahsan, Nicholas Finamore

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Tags: Algorithms, Biology, Computer science, FPGA, Genomics, OpenCL

October 15, 2017 by hgpu

Dynamic Parallelism in GPU Optimized Barnes Hut Trees for Molecular Dynamics Simulations

Melisa Carranza Zuniga

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Tags: Algorithms, Biology, Biomolecules, Biophysics, Chemistry, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 480, Physics, Thesis

August 26, 2017 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

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high performance computing on graphics processing units: hgpu.org

Parallel scalable simulations of biological neural networks using TensorFlow: A beginner’s guide

ASW: Accelerating Smith-Waterman Algorithm on Coupled CPU-GPU Architecture

SWIFOLD: Smith-Waterman implementation on FPGA with OpenCL for long DNA sequences

Interactive GPU active contours for segmenting inhomogeneous objects

Fast and Flexible GPU Accelerated Binding Free Energy Calculations within the AMBER Molecular Dynamics Package

pyPaSWAS: Python-based multi-core CPU and GPU sequence alignment

Molecular dynamics recipes for genome research

HCudaBLAST: an implementation of BLAST on Hadoop and Cuda

A Hybrid-parallel Architecture for Applications in Bioinformatics

High Performance Streaming Smith-Waterman Implementation with Implicit Synchronization on Intel FPGA using OpenCL

Accelerating Genomics Research with OpenCL and FPGAs

Dynamic Parallelism in GPU Optimized Barnes Hut Trees for Molecular Dynamics Simulations

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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