Sequence matching

hgpu.org » Sequence matching

High performance pattern matching and data remanence on graphics processing units

X. Bellekens

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Tags: Aho Corasick, Algorithms, amazon, BMH, CUDA, Digital Forensic, forensic, GPU, pattern matching, PFAC, remanence, Sequence matching, String matching, Suffix Tree, Tesla K20, Tesla K20c

November 22, 2016 by xhgpu

Stealing Webpages Rendered on Your Browser by Exploiting GPU Vulnerabilities

Sangho Lee, Youngsok Kim, Jangwoo Kim, Jong Kim

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Tags: AMD FirePro W9000, ATI, ATI Radeon HD 7850, Computer science, CUDA, nVidia, nVidia GeForce GT 210, nVidia GeForce GTX 780, OpenCL, Security, Sequence matching, Tesla C2050

April 13, 2014 by hgpu

Parallelization of DNA alignment algorithms using GPUs

Gustavo Encarnacao

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 580, Sequence matching, Suffix trees

March 7, 2014 by hgpu

Achieving TeraCUPS on Longest Common Subsequence Problem using GPGPUs

Adnan Ozsoy, Arun Chauhan, Martin Swany

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 690, Sequence alignment, Sequence matching, Tesla C2075, Tesla M2090

January 2, 2014 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

GPU Accelerated Multiple Deoxyribose Nucleic Acid Sequence Parallel Matching

Gang Liao, Qi Sun, Longfei Ma, Zhihui Qin

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Tags: Algorithms, Bioinformatics, Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 680, Sequence matching, Suffix trees

March 18, 2013 by hgpu

Bioinformatics Sequence Comparisons on Manycore Processors

Tuan Tu Tran

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Tags: ATI, ATI Radeon HD 5870, Bioinformatics, Biology, nVidia, nVidia GeForce GTX 480, OpenCL, Review, Sequence matching, Thesis

December 25, 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

Parallel Implementation of the Wu-Manber Algorithm Using the OpenCL Framework

Themistoklis K. Pyrgiotis, Charalampos S. Kouzinopoulos, Konstantinos G. Margaritis

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Tags: Algorithms, Biology, Computational biology, Databases, nVidia, nVidia GeForce GTX 280, OpenCL, Pattern Search, Sequence matching

June 20, 2012 by hgpu

Parallel Approach for Longest Common Subsequence problem on GPU

Raik Issaoui, Amine Draief, Abdelfettah Belghith

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GT 430, OpenCL, Sequence matching

November 16, 2011 by hgpu

High performance technique for database applications using a hybrid GPU/CPU platform

M. Affan Zidan, Talal Bonny, Khaled N. Salama

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Tags: Algorithms, Computer science, Databases, Presentation, Programming techniques, Sequence matching, Smith-Waterman algorithm

September 11, 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

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

High performance pattern matching and data remanence on graphics processing units

Stealing Webpages Rendered on Your Browser by Exploiting GPU Vulnerabilities

Parallelization of DNA alignment algorithms using GPUs

Achieving TeraCUPS on Longest Common Subsequence Problem using GPGPUs

Communication Optimization for Multi GPU Implementation of Smith-Waterman Algorithm

GPU Accelerated Multiple Deoxyribose Nucleic Acid Sequence Parallel Matching

Bioinformatics Sequence Comparisons on Manycore Processors

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

Parallel Implementation of the Wu-Manber Algorithm Using the OpenCL Framework

Parallel Approach for Longest Common Subsequence problem on GPU

High performance technique for database applications using a hybrid GPU/CPU platform

High-Throughput Sequence Translation Using CUDA

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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