Smith-Waterman algorithm | Page 2

hgpu.org » Smith-Waterman algorithm

Comparative Study of the Parallelization of the Smith-Waterman Algorithm on OpenMP and Cuda C

Amadou Chaibou, Oumarou Sie

View

Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 670, OpenMP, Sequence alignment, Smith-Waterman algorithm

June 22, 2015 by hgpu

Flexible, Fast and Accurate Sequence Alignment Profiling on GPGPU with PaSWAS

Sven Warris, Feyruz Yalcin, Katherine J. L. Jackson, Jan Peter Nap

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 295, Package, Sequence alignment, Smith-Waterman algorithm, Tesla C1060

April 7, 2015 by hgpu

Implementation of Smith-Waterman algorithm in OpenCL for GPUs

Dzmitry Razmyslovich, Guillermo Marcus, Markus Gipp, Marc Zapatka, Andreas Szillus

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biology, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sequence alignment, Smith-Waterman algorithm

February 27, 2015 by azhar ali

SW#db: GPU-accelerated exact sequence similarity database search

Matija Korpar, Martin Sosic, Dino Blazeka, Mile Sikic

View

Download (PDF)

Source codes

Tags: Algorithms, Biology, CUDA, Databases, Next-Generation sequencing, nVidia, nVidia GeForce GTX 690, nVidia GeForce GTX 780, Package, Smith-Waterman algorithm

January 16, 2015 by hgpu

Fast Sequence Alignment Method Using CUDA-enabled GPU

Yeim-Kuan Chang, De-Yu Chen

View

Download (PDF)

Tags: Bioinformatics, Biology, CUDA, nVidia, Sequence alignment, Smith-Waterman algorithm, Tesla C1060

June 19, 2014 by hgpu

Efficient all-against-all protein similarity matrix computation using OpenCL

U. Köhler, A. Smirnov

View

Download (PDF)

Tags: AMD Radeon HD 580, Bioinformatics, nVidia, OpenCL, Sequence alignment, Smith-Waterman algorithm

June 9, 2014 by hgpu

GAMUT: GPU accelerated microRNA analysis to uncover target genes through CUDA-miRanda

Shuang Wang, Jihoon Kim, Xiaoqian Jiang, Stefan F Brunner, Lucila Ohno-Machado

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biology, CUDA, nVidia, Package, RNA, Smith-Waterman algorithm, Tesla M2090

May 10, 2014 by hgpu

SWAPHI: Smith-Waterman Protein Database Search on Xeon Phi Coprocessors

Yongchao Liu, Bertil Schmidt

View

Download (PDF)

Source codes

Tags: Computer science, Intel Xeon Phi, Package, Smith-Waterman algorithm

April 21, 2014 by hgpu

A Study on Efficient Application Mapping on Parallel Computing Accelerators

Keisuke Dohi

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, FDTD, Finite-difference time-domain, FPGA, MPI, nVidia, nVidia GeForce GTX 295, Smith-Waterman algorithm, Thesis

April 7, 2014 by hgpu

Pairwise Sequence Alignment for Very Long Sequences on GPUs

J. Li, S. Ranka, S. Sahni

View

Download (PDF)

Tags: CUDA, Genetics, nVidia, nVidia Tesla C2050, Sequence alignment, Smith-Waterman algorithm

April 2, 2014 by hgpu

MaxSSmap: A GPU program for short read mapping with the maximum scoring subsequence

Usman Roshan

View

Download (PDF)

Tags: Bioinformatics, Biology, CUDA, nVidia, Short read mapping, Smith-Waterman algorithm, Tesla M2050

March 12, 2014 by hgpu

Hybrid Framework for pairwise DNA Sequence Alignment Using the CUDA compatible GPU

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

View

Download (PDF)

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

March 6, 2014 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

* * *

high performance computing on graphics processing units: hgpu.org

Comparative Study of the Parallelization of the Smith-Waterman Algorithm on OpenMP and Cuda C

Flexible, Fast and Accurate Sequence Alignment Profiling on GPGPU with PaSWAS

Implementation of Smith-Waterman algorithm in OpenCL for GPUs

SW#db: GPU-accelerated exact sequence similarity database search

Fast Sequence Alignment Method Using CUDA-enabled GPU

Efficient all-against-all protein similarity matrix computation using OpenCL

GAMUT: GPU accelerated microRNA analysis to uncover target genes through CUDA-miRanda

SWAPHI: Smith-Waterman Protein Database Search on Xeon Phi Coprocessors

A Study on Efficient Application Mapping on Parallel Computing Accelerators

Pairwise Sequence Alignment for Very Long Sequences on GPUs

MaxSSmap: A GPU program for short read mapping with the maximum scoring subsequence

Hybrid Framework for pairwise DNA Sequence Alignment Using the CUDA compatible 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

Most viewed papers (last 30 days)