high performance computing on graphics processing units: hgpu.org

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Accelerating Smith-Waterman Local Sequence Alignment on GPU Cluster

Thuy T. Nguyen, Duc H. Nguyen, Phong H. Pham, Ngoc M. Ta, Tan N. Duong, Hung D. Le

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Tags: Bioinformatics, Biology, CUDA, GPU cluster, MPI, nVidia, nVidia GeForce GTX 295, Sequence alignment, Smith-Waterman algorithm, Tesla C1060

June 27, 2011 by hgpu

Accelerating Smith-Waterman on Heterogeneous CPU-GPU Systems

Jaideep Singh, Ipseeta Aruni

Tags: Bioinformatics, Biology, CUDA, Heterogeneous systems, nVidia, Smith-Waterman algorithm

June 24, 2011 by hgpu

Protein alignment algorithms with an efficient backtracking routine on multiple GPUs

Jacek Blazewicz, Wojciech Frohmberg, Michal Kierzynka, Erwin Pesch, Pawel Wojciechowski

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Package, Sequence alignment, Tesla S1070

June 21, 2011 by hgpu

Accelerating Genome-Wide Association Studies Using CUDA Compatible Graphics Processing Units

Rui Jiang, Feng Zeng, Wangshu Zhang, Xuebing Wu, Zhihong Yu

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Tags: Bioinformatics, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 280

June 15, 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

The scoring sequences on profile Hidden Markov Models with delete states elimination by GPUs

Jun Li, Yanhui Li, Shuangping Chen

Tags: Bioinformatics, Computer science, nVidia, nVidia GeForce 9800 GTX, Sequence alignment

June 10, 2011 by hgpu

cuGWAM: Genome-wide association multifactor dimensionality reduction using CUDA-enabled high-performance graphics processing unit

Min-Seok Kwon, Kyunga Kim, Sungyoung Lee, Taesung Park

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

June 9, 2011 by hgpu

Parallel accelerators for GlimmerHMM bioinformatics algorithm

Nafsika Chrysanthou, Grigorios Chrysos, Euripides Sotiriades, Ioannis Papaefstathiou

Tags: Algorithms, Bioinformatics, Biology, FPGA, Genetics

June 8, 2011 by hgpu

Highly efficient mapping of the Smith-Waterman algorithm on CUDA-compatible GPUs

K. Dohi, K. Benkridt, C. Ling, T. Hamada, Y. Shibata

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

May 31, 2011 by hgpu

Fast Parallel Markov Clustering in Bioinformatics Using Massively Parallel Graphics Processing Unit Computing

Alhadi Bustamam, Kevin Burrage, Nicholas A. Hamilton

Tags: Bioinformatics, Biology, CUDA, MPI, nVidia, Sparse matrix

May 30, 2011 by hgpu

Fast network centrality analysis using GPUs

Zhiao Shi, Bing Zhang

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Tags: All-Pairs Distance, Bioinformatics, Biology, CUDA, nVidia, Package, Tesla C2050

May 13, 2011 by hgpu

Exact and complete short-read alignment to microbial genomes using Graphics Processing Unit programming

Jochen Blom, Tobias Jakobi, Daniel Doppmeier, Sebastian Jaenicke, Jorn Kalinowski, Jens Stoye, Alexander Goesmann

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Next-Generation sequencing, nVidia, Package

May 10, 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

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high performance computing on graphics processing units: hgpu.org

Accelerating Smith-Waterman Local Sequence Alignment on GPU Cluster

Accelerating Smith-Waterman on Heterogeneous CPU-GPU Systems

Protein alignment algorithms with an efficient backtracking routine on multiple GPUs

Accelerating Genome-Wide Association Studies Using CUDA Compatible Graphics Processing Units

The accelerating implementation of BLAST with stream processor

The scoring sequences on profile Hidden Markov Models with delete states elimination by GPUs

cuGWAM: Genome-wide association multifactor dimensionality reduction using CUDA-enabled high-performance graphics processing unit

Parallel accelerators for GlimmerHMM bioinformatics algorithm

Highly efficient mapping of the Smith-Waterman algorithm on CUDA-compatible GPUs

Fast Parallel Markov Clustering in Bioinformatics Using Massively Parallel Graphics Processing Unit Computing

Fast network centrality analysis using GPUs

Exact and complete short-read alignment to microbial genomes using Graphics Processing Unit programming

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)