high performance computing on graphics processing units: hgpu.org

hgpu.org » Biology

Accelerating calculations of RNA secondary structure partition functions using GPUs

Harry A Stern, David H Mathews

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biology, CUDA, nVidia, Package, RNA, Tesla M2050

November 11, 2013 by hgpu

Computational kinetics of a large scale biological process on GPU workstations: DNA bending

Arnold Peter Ruymgaart

View

Download (PDF)

Tags: Biology, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 480, Thesis

November 8, 2013 by hgpu

Communication Optimization for Multi GPU Implementation of Smith-Waterman Algorithm

Sampath Kumar, P. K. Baruah

View

Download (PDF)

Tags: Algorithms, Biology, Computational biology, CUDA, Databases, nVidia, Sequence matching, Smith-Waterman algorithm, Tesla M2050

November 2, 2013 by hgpu

gEMpicker: A Highly Parallel GPU-Accelerated Particle Picking Tool for Cryo-Electron Microscopy

Thai V. Hoang, Xavier Cavin, Patrick Schultz, David W. Ritchie

View

Download (PDF)

Tags: Algorithms, Biology, Cryo-EM, CUDA, Electron microscopy, FFT, Macromolecule, Microscopy, nVidia, Tesla C1060, Tesla C2075

October 24, 2013 by hgpu

cudaMap: a GPU accelerated program for gene expression connectivity mapping

Darragh G McArt, Peter Bankhead, Philip D Dunne, Manuel Salto-Tellez, Peter Hamilton, Shu-Dong Zhang

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biology, CUDA, nVidia, Package, Tesla C2050

October 17, 2013 by hgpu

High performance sequence mining using pairwise statistical significance

Yuhong Zhang, Feng Chen

View

Download (PDF)

Source codes

Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, Package, Tesla C2050

October 12, 2013 by hgpu

Regional Heritability Advanced Complex Trait Analysis for GPU and Traditional Parallel Architectures

L. Cebamanos, A. Gray, I. Stewart, A. Tenesa

View

Download (PDF)

Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, Tesla K20

October 12, 2013 by hgpu

Enabling the use of Heterogeneous Computing for Bioinformatics

Ramakrishna Bijanapalli Chakri

View

Download (PDF)

Tags: Bioinformatics, Biology, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, Smith-Waterman algorithm, Thesis

October 8, 2013 by hgpu

GPU-powered Simulation Methodologies for Biological Systems

Daniela Besozzi, Giulio Caravagna, Paolo Cazzaniga, Marco Nobile, Dario Pescini, Alessandro Re

View

Download (PDF)

Tags: Biology, Computer science, CUDA, nVidia

October 2, 2013 by hgpu

gEMfitter: A Highly Parallel FFT-Based 3D Density Fitting Tool With GPU Texture Memory Acceleration

Thai V. Hoang, Xavier Cavin, David W. Ritchie

View

Download (PDF)

Tags: Biology, Cryo-EM, CUDA, Electron microscopy, FFT, Macromolecule, Microscopy, nVidia, Tesla C2075

September 28, 2013 by hgpu

Improving Resource Utilization in Heterogeneous CPU-GPU Systems

Michael Boyer

View

Download (PDF)

Source codes

Tags: Algorithms, ATI, ATI Radeon HD 5870, ATI Radeon HD 7970, Biology, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 280, OpenCL, Package, Software Engineering, Thesis

September 23, 2013 by hgpu

A Novel CPU/GPU Simulation Environment for Large-Scale Biologically-Realistic Neural Modeling

Roger V. Hoang, Devyani Tanna, Laurence C. Jayet Bray, Sergiu M. Dascalu, Frederick C. Harris Jr.

View

Download (PDF)

Source codes

Tags: Biology, CUDA, Neural networks, Neuroscience, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Package, Tesla C2050

September 14, 2013 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

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

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

Experiences with implementing Kokkos’ SYCL backend

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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Accelerating calculations of RNA secondary structure partition functions using GPUs

Computational kinetics of a large scale biological process on GPU workstations: DNA bending

Communication Optimization for Multi GPU Implementation of Smith-Waterman Algorithm

gEMpicker: A Highly Parallel GPU-Accelerated Particle Picking Tool for Cryo-Electron Microscopy

cudaMap: a GPU accelerated program for gene expression connectivity mapping

High performance sequence mining using pairwise statistical significance

Regional Heritability Advanced Complex Trait Analysis for GPU and Traditional Parallel Architectures

Enabling the use of Heterogeneous Computing for Bioinformatics

GPU-powered Simulation Methodologies for Biological Systems

gEMfitter: A Highly Parallel FFT-Based 3D Density Fitting Tool With GPU Texture Memory Acceleration

Improving Resource Utilization in Heterogeneous CPU-GPU Systems

A Novel CPU/GPU Simulation Environment for Large-Scale Biologically-Realistic Neural Modeling

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

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

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

Most viewed papers (last 30 days)