high performance computing on graphics processing units: hgpu.org

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Fine-grain Parallelism using Multi-core, Cell/BE, and GPU Systems

Frederico Pratas, Pedro Trancoso, Leonel Sousa, Alexandros Stamatakis, Guochun Shi, Volodymyr Kindratenko

Tags: Bioinformatics, Biology, Cell processor, CUDA, Molecular dynamics, nVidia

August 25, 2011 by hgpu

Network-on-Chip Hardware Accelerators for Biological Sequence Alignment

Souradip Sarkar, Gaurav Ramesh Kulkarni, Partha Pratim Pande, Ananth Kalyanaraman

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Tags: Algorithms, Bioinformatics, Biology, FPGA, Sequence alignment

August 12, 2011 by hgpu

Unifying stream based and reconfigurable computing to design application accelerators

Bruno Francisco, Frederico Pratas, Leonel Sousa

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Tags: Bioinformatics, Biology, Computer science, Data parallelism, FPGA, nVidia, nVidia GeForce GTX 285

August 2, 2011 by hgpu

High-Throughput Sequence Translation Using CUDA

Sun Wei-dong, Ma Zong-min

Tags: Bioinformatics, Biology, CUDA, nVidia, Sequence matching

July 25, 2011 by hgpu

A Coarse Grain Reconfigurable Architecture for sequence alignment problems in bio-informatics

Pei Liu, A. Hemani

Tags: Algorithms, Bioinformatics, Biology, FPGA, Sequence alignment, Smith-Waterman algorithm

July 25, 2011 by hgpu

On the Robust Mapping of Dynamic Programming onto a Graphics Processing Unit

Shucai Xiao, A.M. Aji, Wu-chun Feng

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Tags: Algorithms, Bioinformatics, Biology, Cell processor, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 280, Sequence alignment, Smith-Waterman algorithm

July 23, 2011 by hgpu

Harnessing the power of idle GPUs for acceleration of biological sequence alignment

Fumihiko Ino, Yuki Kotani, Yuma Munekawa, Kenichi Hagihara

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce 7900 GTX, nVidia GeForce 7950 GX2, nVidia GeForce 8800 GTX, OpenGL, Sequence alignment

July 12, 2011 by hgpu

An Adaptive Hybrid Multiprocessor technique for bioinformatics sequence alignment

T. Bonny, M.A. Zidan, K.N. Salama

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia Quadro FX 4800, Sequence alignment, Smith-Waterman algorithm

July 7, 2011 by hgpu

Striped Smith-Waterman speeds database searches six times over other SIMD implementations

M. Farrar

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Tags: Algorithms, Bioinformatics, Biology, Sequence alignment, Smith-Waterman algorithm

July 6, 2011 by hgpu

Six-fold speed-up of Smith-Waterman sequence database searches using parallel processing on common microprocessors

Torbjorn Rognes, Erling Seeberg

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Tags: Algorithms, Bioinformatics, Biology, Sequence alignment, Smith-Waterman algorithm

July 6, 2011 by hgpu

Graphics processing unit implementations of relative expression analysis algorithms enable dramatic computational speedup

Andrew T. Magis, John C. Earls, Youn-Hee H. Ko, James A. Eddy, Nathan D. Price

Source codes

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

July 1, 2011 by hgpu

CAMPAIGN: An open-source Library of GPU-accelerated Data Clustering Algorithms

Kai J. Kohlhoff, Marc H. Sosnick, William T. Hsu, Vijay S. Pande, Russ B. Altman

Source codes

Tags: Bioinformatics, Biology, Clustering, CUDA, nVidia, Package

July 1, 2011 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

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high performance computing on graphics processing units: hgpu.org

Fine-grain Parallelism using Multi-core, Cell/BE, and GPU Systems

Network-on-Chip Hardware Accelerators for Biological Sequence Alignment

Unifying stream based and reconfigurable computing to design application accelerators

High-Throughput Sequence Translation Using CUDA

A Coarse Grain Reconfigurable Architecture for sequence alignment problems in bio-informatics

On the Robust Mapping of Dynamic Programming onto a Graphics Processing Unit

Harnessing the power of idle GPUs for acceleration of biological sequence alignment

An Adaptive Hybrid Multiprocessor technique for bioinformatics sequence alignment

Striped Smith-Waterman speeds database searches six times over other SIMD implementations

Six-fold speed-up of Smith-Waterman sequence database searches using parallel processing on common microprocessors

Graphics processing unit implementations of relative expression analysis algorithms enable dramatic computational speedup

CAMPAIGN: An open-source Library of GPU-accelerated Data Clustering Algorithms

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)