high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Biology

GPU-accelerated protein family identification for metagenomics

Changjun Wu, Ananth Kalyanaraman

View

Download (PDF)

Tags: Biology, Clustering, CUDA, Graph theory, nVidia, Tesla K20

May 25, 2013 by hgpu

A Distributed CPU-GPU Framework for Pairwise Alignments on Large-Scale Sequence Datasets

Da Li, Kittisak Sajjapongse, Huan Truong, Gavin Conant, Michela Becchi

View

Download (PDF)

Tags: Bioinformatics, Biology, Computational biology, CUDA, GPU cluster, Heterogeneous systems, MPI, nVidia, nVidia Quadro FX 2000, Sequence alignment, Tesla K20

May 11, 2013 by hgpu

The GPU-based High-performance Pattern-matching Algorithm for Intrusion Detection

Dongliang Xu, Hongli Zhang, Yujian Fan

View

Download (PDF)

Tags: Biology, Computer science, CUDA, Information Retrieval, nVidia, nVidia GeForce 9800 GTS, nVidia GeForce GTX 570, Security, String matching

May 11, 2013 by hgpu

Simulation of Biological Tissue using Mass-Spring-Damper Models

Emil Eriksson

View

Download (PDF)

Tags: ATI, ATI Radeon HD 7970, Biology, OpenCL, Surgical simulation, Thesis, Visualization

May 6, 2013 by hgpu

GPU-based Steady-State Solution of the Chemical Master Equation

Marco Maggioni, Tanya Berger-Wolf, Jie Liang

View

Download (PDF)

Tags: Biology, CUDA, Macromolecule, nVidia, nVidia GeForce GTX 580, Probability, Sparse matrix

May 1, 2013 by hgpu

SW# – GPU enabled exact alignments on genome scale

Matija Korpar, Mile Sikic

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biology, Computer science, CUDA, nVidia, nVidia GeForce GTX 560, nVidia GeForce GTX 570, nVidia GeForce GTX 690, Package, Sequence alignment, Smith-Waterman algorithm

April 23, 2013 by hgpu

GPU-SD and DPD Parallelization for Gromacs tools for molecular dynamics simulations

Nicolae Goga, Siewert Marrink, Ruxandra Cioromela, Florica Moldoveanu

View

Download (PDF)

Tags: Algorithms, Bioinformatics, Biology, Chemistry, CUDA, Molecular dynamics, nVidia, nVidia GeForce 9600 GT

April 21, 2013 by hgpu

CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions

Yongchao Liu, Adrianto Wirawan, Bertil Schmidt

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 690, Package, PTX, Sequence alignment, Smith-Waterman algorithm

April 10, 2013 by hgpu

Parallel Implementation of Dynamic Programming Algorithm Using Graphics Processing Unit

M. Khurram Rehman, M. Umer Sarwar, M. Ramzan Talib, M. Salman Mansoor, M. Bilal Sarwar

View

Download (PDF)

Tags: Algorithms, Bioinformatics, Biology, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GT 525 M, nVidia GeForce GT 610 M, Sequence alignment

April 6, 2013 by hgpu

CMCpy: Genetic Code-Message Coevolution Models in Python

Peter J. Becich, Brian P. Stark, Harish S. Bhat, David H. Ardell

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 460, Package, Python

March 31, 2013 by hgpu

GPU-Based Cloud Service for Smith-Waterman algorithm Using Frequency Distance Filtration Scheme

Sheng-Ta Lee, Chun-Yuan Lin, Che Lun Hung

View

Download (PDF)

Tags: Bioinformatics, Biology, Cloud, CUDA, nVidia, Sequence alignment, Smith-Waterman algorithm, Tesla C2050

March 18, 2013 by hgpu

GPU based Eulerian Assembly of Genomes

Syed Faraz Mahmood

View

Download (PDF)

Tags: Bioinformatics, Biology, CUDA, Genetics, nVidia, nVidia Quadro FX 5800, Thesis

March 7, 2013 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Applications

GPU-accelerated protein family identification for metagenomics

A Distributed CPU-GPU Framework for Pairwise Alignments on Large-Scale Sequence Datasets

The GPU-based High-performance Pattern-matching Algorithm for Intrusion Detection

Simulation of Biological Tissue using Mass-Spring-Damper Models

GPU-based Steady-State Solution of the Chemical Master Equation

SW# – GPU enabled exact alignments on genome scale

GPU-SD and DPD Parallelization for Gromacs tools for molecular dynamics simulations

CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions

Parallel Implementation of Dynamic Programming Algorithm Using Graphics Processing Unit

CMCpy: Genetic Code-Message Coevolution Models in Python

GPU based Eulerian Assembly of Genomes

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

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

Most viewed papers (last 30 days)