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Fast k-NNG construction with GPU-based quick multi-select

Ivan Komarov, Ali Dashti, Roshan D'Souza

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Tags: Algorithms, Bioinformatics, Clustering, Computer science, CUDA, Machine learning, Nearest neighbour, nVidia, Tesla C2050

September 25, 2013 by hgpu

Expressed Sequence Tag Clustering using Commercial Gaming Hardware

Charl van Deventer, Willem A. Clarke, Scott Hazelhurst

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Tags: Algorithms, Bioinformatics, Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, Package, Thesis

September 15, 2013 by hgpu

GUESS-ing Polygenic Associations with Multiple Phenotypes Using a GPU-Based Evolutionary Stochastic Search Algorithm

Leonardo Bottolo, Marc Chadeau-Hyam, David I. Hastie, Tanja Zeller, Benoit Liquet, Paul Newcombe, Loic Yengo, Philipp S. Wild, Arne Schillert, Andreas Ziegler, Sune F. Nielsen, Adam S. Butterworth, Weang Kee Ho, Raphaele Castagne, Thomas Munzel, David Tregouet, Mario Falchi15, Francois Cambien, Borge G. Nordestgaard, Frederic Fumeron, Anne Tybjaerg-Hansen, Philippe Froguel, John Danesh, Enrico Petretto, Stefan Blankenberg, Laurence Tiret, Sylvia Richardson

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Tags: Algorithms, Bayesian, Bioinformatics, Biology, CUDA, nVidia, Package, Tesla C1060

August 16, 2013 by hgpu

Multi-core CPU or GPU-accelerated Multiscale Modeling for Biomolecular Complexes

Tao Liao, Yongjie Zhang, Peter M. Kekenes-Huskey, Yuhui Cheng, Anushka Michailova, Andrew D. McCulloch, Michael Holst, J. Andrew McCammon

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Tags: Algorithms, Bioinformatics, Biology, Biomolecules, CUDA, KD-tree, Molecular surface, nVidia, nVidia GeForce GTX 680

August 9, 2013 by hgpu

GPU Accelerated Pattern Matching Algorithm for DNA Sequences to Detect Cancer using CUDA

Snehal P. Adey

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Tags: Bioinformatics, Biology, CUDA, Medicine, nVidia, Tesla C2070, Thesis

August 7, 2013 by hgpu

On Benchmarking the Matrix Multiplication Algorithm using OpenMP, MPI and CUDA Programming Languages

Muhammed Al-Mulhem, Abdulah AlDhamin, Raed Al-Shaikh

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Tags: Algorithms, Benchmarking, Bioinformatics, Computer science, CUDA, Linear Algebra, Matrix multiplication, MPI, nVidia, nVidia GeForce GTX 460

July 19, 2013 by hgpu

CFMDS: CUDA-based fast multidimensional scaling for genome-scale data

Sungin Park, Soo-Yong Shin, Kyu-Baek Hwang

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

June 21, 2013 by hgpu

GPU Multiple Sequence Alignment Fourier-Space Cross-Correlation Alignment

Matthias Alexander Lee

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Tags: Bioinformatics, Biology, Computational Complexity, CUDA, nVidia, Package, Python, RNA, Sequence alignment, Signal processing

May 31, 2013 by hgpu

A Distributed CPU-GPU Framework for Pairwise Alignments on Large-Scale Sequence Datasets

Da Li, Kittisak Sajjapongse, Huan Truong, Gavin Conant, Michela Becchi

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Tags: Bioinformatics, Biology, Computational biology, CUDA, GPU cluster, Heterogeneous systems, MPI, nVidia, nVidia Quadro FX 2000, Sequence alignment, Tesla K20

May 11, 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

GPU-SD and DPD Parallelization for Gromacs tools for molecular dynamics simulations

Nicolae Goga, Siewert Marrink, Ruxandra Cioromela, Florica Moldoveanu

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Tags: Algorithms, Bioinformatics, Biology, Chemistry, CUDA, Molecular dynamics, nVidia, nVidia GeForce 9600 GT

April 21, 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

PELSI: Power-Efficient Layer-Switched Inference

Efficient deep learning inference on end devices

Ouroboros: Virtualized Queues for dynamic memory management

Dynamic Memory Management on GPUs with SYCL

MSCCL++: A GPU-driven communication stack for scalable AI applications

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

Data-efficient LLM Fine-tuning for Code Generation

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

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

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

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