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Graph-Based Substructure Pattern Mining Using CUDA Dynamic Parallelism

Fei Wang, Jianqiang Dong, Bo Yuan

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Tesla K20

July 27, 2013 by hgpu

Parallel Graph Processing on Graphics Processors Made Easy

Jianlong Zhong, Bingsheng He

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Source codes

Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Package, Tesla C2050

July 12, 2013 by hgpu

GPU-accelerated protein family identification for metagenomics

Changjun Wu, Ananth Kalyanaraman

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Tags: Biology, Clustering, CUDA, Graph theory, nVidia, Tesla K20

May 25, 2013 by hgpu

A Tuned, Concurrent-Kernel Approach to Speed Up the APSP Problem

Hector Ortega-Arranz, Yuri Torres, Diego R. Llanos, Arturo Gonzalez-Escribano

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 480

May 25, 2013 by hgpu

Critical Links Detection using CUDA

Thomas Schnabl

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 560 Ti, Thesis

May 7, 2013 by hgpu

Efficient Computation of the Kleene Star in Max-Plus Algebra using a CUDA GPU

Hiroyuki Goto, Kazuhiro Toyoda

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Tags: Computer science, CUDA, Graph theory, nVidia, Tesla C2075

April 27, 2013 by hgpu

Atomic-free Irregular Computations on GPUs

Rupesh Nasre, Martin Burtscher, Keshav Pingali

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Package, Performance, Tesla K20

April 7, 2013 by hgpu

Deploying Graph Algorithms on GPUs: an Adaptive Solution

Da Li, Michela Becchi

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Tesla C2070

April 4, 2013 by hgpu

Accelerating Graph Analysis with Heterogeneous Systems

Ate Penders

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Tags: Algorithms, Computer science, Graph theory, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL, Tesla C2050, Thesis

March 29, 2013 by hgpu

Morph Algorithms on GPUs

Rupesh Nasre, Martin Burtscher, Keshav Pingali

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Performance, Programming techniques, Tesla C2070

March 12, 2013 by hgpu

GPU accelerated maximum cardinality matching algorithms for bipartite graphs

Mehmet Deveci, Kamer Kaya, Bora Ucar, Umit V. Catalyurek

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Tesla C2050

March 9, 2013 by hgpu

Betweenness Centrality on GPUs and Heterogeneous Architectures

Ahmet Erdem Sariyuce, Kamer Kaya, Erik Saule, Umit V. Catalyurek

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Tags: Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, Package, Tesla C2050, Virtualization

February 7, 2013 by hgpu

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

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

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

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high performance computing on graphics processing units: hgpu.org

Graph-Based Substructure Pattern Mining Using CUDA Dynamic Parallelism

Parallel Graph Processing on Graphics Processors Made Easy

GPU-accelerated protein family identification for metagenomics

A Tuned, Concurrent-Kernel Approach to Speed Up the APSP Problem

Critical Links Detection using CUDA

Efficient Computation of the Kleene Star in Max-Plus Algebra using a CUDA GPU

Atomic-free Irregular Computations on GPUs

Deploying Graph Algorithms on GPUs: an Adaptive Solution

Accelerating Graph Analysis with Heterogeneous Systems

Morph Algorithms on GPUs

GPU accelerated maximum cardinality matching algorithms for bipartite graphs

Betweenness Centrality on GPUs and Heterogeneous Architectures

Recent source codes

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

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

HPX: a C++ Standard Library for Concurrency and Parallelism

TorchQC: Quantum Dynamics and Machine Learning

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

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