high performance computing on graphics processing units: hgpu.org

hgpu.org » Sequence alignment

Faster sequence alignment through GPU-accelerated restriction of the seed-and-extend search space

Richard Wilton, Tamas Budavari, Ben Langmead, Sarah Wheelan, Steven L. Salzberg, Alex Szalay

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Tags: Bioinformatics, Biology, CUDA, nVidia, Sequence alignment, Tesla K20

August 10, 2014 by hgpu

Performance Efficient DNA Sequence Detection on GPU Using Parallel Pattern Matching Approach

Rahul Shirude, Valmik B. Nikam, B.B. Meshram

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX Titan, RNA, Sequence alignment, String matching, Tesla K20

July 26, 2014 by hgpu

Parallelized Hierarchical Expected Matching Probability for Multiple Sequence Alignment

Kedhar M, DR. M. Rajasekhara Babu, Mayank G, Abhinivesh M

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Tags: Bioinformatics, Biology, CUDA, nVidia, Programming techniques, RNA, Sequence alignment, Tesla C2070

July 12, 2014 by hgpu

Fast Sequence Alignment Method Using CUDA-enabled GPU

Yeim-Kuan Chang, De-Yu Chen

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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

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

June 9, 2014 by hgpu

GPU-BSM: A GPU-Based Tool to Map Bisulfite-Treated Reads

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

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Tags: Bioinformatics, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 480, Package, Python, Sequence alignment, Tesla K10, Tesla K20

May 25, 2014 by hgpu

cuBLASTP: Fine-Grained Parallelization of Protein Sequence Search on a GPU

Jing Zhang, Hao Wang, Heshan Lin, Wu-chun Feng

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Tags: Bioinformatics, Biology, CUDA, Next-Generation sequencing, nVidia, Sequence alignment, Tesla K20

May 23, 2014 by hgpu

Local Alignment Tool Based on Hadoop Framework and GPU Architecture

Che-Lun Hun, Guan-Jie Hua

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Tags: Biology, Cloud, CUDA, Hadoop, MapReduce, nVidia, nVidia GeForce GTS 480, Sequence alignment

April 19, 2014 by hgpu

Pairwise Sequence Alignment for Very Long Sequences on GPUs

J. Li, S. Ranka, S. Sahni

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

April 2, 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

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

March 6, 2014 by hgpu

QuickProbs – A Fast Multiple Sequence Alignment Algorithm Designed for Graphics Processors

Adam Gudys, Sebastian Deorowicz

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Tags: ATI, ATI Radeon HD 7970, Bioinformatics, Biology, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Package, Sequence alignment

March 4, 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

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

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high performance computing on graphics processing units: hgpu.org

Faster sequence alignment through GPU-accelerated restriction of the seed-and-extend search space

Performance Efficient DNA Sequence Detection on GPU Using Parallel Pattern Matching Approach

Parallelized Hierarchical Expected Matching Probability for Multiple Sequence Alignment

Fast Sequence Alignment Method Using CUDA-enabled GPU

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

GPU-BSM: A GPU-Based Tool to Map Bisulfite-Treated Reads

cuBLASTP: Fine-Grained Parallelization of Protein Sequence Search on a GPU

Pairwise Sequence Alignment for Very Long Sequences on GPUs

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

QuickProbs – A Fast Multiple Sequence Alignment Algorithm Designed for Graphics Processors

Achieving TeraCUPS on Longest Common Subsequence Problem using GPGPUs

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