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A tool for mapping Single Nucleotide Polymorphisms using Graphics Processing Units

Andrea Manconi, Alessandro Orro, Emanuele Manca, Giuliano Armano, Luciano Milanesi

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 480, Package, Smith-Waterman algorithm, Tesla K20

January 12, 2014 by hgpu

Accelerating Pairwise DNA Sequence Alignment using the CUDA Compatible GPU

H. Khaled, R. El Gohary, N. L. Badr, H. M. Faheem

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GT 540 M, Sequence alignment, Smith-Waterman algorithm

December 22, 2013 by hgpu

DynaProg for Scala: A Scala DSL for Dynamic Programming on CPU and GPU

Thierry Coppey

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Source codes

Tags: Computer science, CUDA, Heterogeneous systems, High-level Languages, nVidia, nVidia GeForce GT 650 M, Package, RNA, Smith-Waterman algorithm

November 4, 2013 by hgpu

Communication Optimization for Multi GPU Implementation of Smith-Waterman Algorithm

Sampath Kumar, P. K. Baruah

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

November 2, 2013 by hgpu

High-performance Dynamic Programming on FPGAs with OpenCL

Sean O. Settle

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Tags: Bioinformatics, Computer science, FPGA, Heterogeneous systems, OpenCL, RNA, Smith-Waterman algorithm

October 29, 2013 by hgpu

Enabling the use of Heterogeneous Computing for Bioinformatics

Ramakrishna Bijanapalli Chakri

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

October 8, 2013 by hgpu

SW# – GPU enabled exact alignments on genome scale

Matija Korpar, Mile Sikic

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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

Computing Privacy-Preserving Edit Distance and Smith-Waterman Problems on the GPU Architecture

Shi Pu, Jyh-Charn Liu

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Security, Smith-Waterman algorithm

April 18, 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

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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

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

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

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

March 18, 2013 by hgpu

G-SNPM – A GPU-based SNP mapping tool

Alessandro Orro, Andrea Manconi, Emanuele Manca, Giuliano Armano, Luciano Milanesi

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Next-Generation sequencing, nVidia, nVidia GeForce GTX 480, Package, Python, Smith-Waterman algorithm

November 14, 2012 by hgpu

Accelerating the Smith-Waterman Algorithm for Bio-sequence Matching on GPU

Qianghua Zhu, Fei Xia, Guoqing Jin

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Databases, nVidia, nVidia GeForce GTX 470, Sequence alignment, Sequence matching, Smith-Waterman algorithm

September 16, 2012 by hgpu

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

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

A tool for mapping Single Nucleotide Polymorphisms using Graphics Processing Units

Accelerating Pairwise DNA Sequence Alignment using the CUDA Compatible GPU

DynaProg for Scala: A Scala DSL for Dynamic Programming on CPU and GPU

Communication Optimization for Multi GPU Implementation of Smith-Waterman Algorithm

High-performance Dynamic Programming on FPGAs with OpenCL

Enabling the use of Heterogeneous Computing for Bioinformatics

SW# – GPU enabled exact alignments on genome scale

Computing Privacy-Preserving Edit Distance and Smith-Waterman Problems on the GPU Architecture

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

G-SNPM – A GPU-based SNP mapping tool

Accelerating the Smith-Waterman Algorithm for Bio-sequence Matching on GPU

Recent source codes

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

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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