high performance computing on graphics processing units: hgpu.org

hgpu.org » Graph theory

Parallel Breadth First Search on GPU Clusters

Zhisong Fu, Harish Kumar Dasari, Martin Berzins, Bryan Thompson

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Tags: Algorithms, Computer science, CUDA, GPU cluster, Graph theory, Network communications, nVidia, Package, Tesla K20

August 11, 2014 by hgpu

Parallel Distributed Breadth First Search on the Kepler Architecture

Mauro Bisson, Massimo Bernaschi, Enrico Mastrostefano

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Tags: Computer science, CUDA, Distributed computing, Graph theory, nVidia, Tesla K20

August 9, 2014 by hgpu

Scalable and High Performance Betweenness Centrality on the GPU

Adam McLaughlin, David A. Bader

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Tags: Algorithms, Computer science, CUDA, Graph theory, Numerical simulation, nVidia, nVidia GeForce GTX Titan, Package, Tesla M2090

August 1, 2014 by hgpu

Parallelization of BFS Graph Algorithm using CUDA

Chetan D. Pise, Shailendra W. Shende

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Tags: Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 630 M

July 11, 2014 by hgpu

Understanding the SIMD Efficiency of Graph Traversal on GPU

Yichao Cheng, Hong An, Zhitao Chen, Feng Li, Zhaohui Wang, Xia Jiang, Yi Peng

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

July 10, 2014 by hgpu

Massive Parallelism with GPUs for Centrality Ranking in Complex Networks

Frederico L. Cabral, Carla Osthoff, Rafael Nardes, Daniel Ramos

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Tags: Computer science, CUDA, GPU cluster, Graph theory, MPI, nVidia, Tesla K20

July 6, 2014 by hgpu

Exploiting parallel features of modern computer architectures in bioinformatics: applications to genetics, structure comparison and large graph analysis

Guillaume Chapuis

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Genetics, Graph theory, nVidia, Path problems, Tesla C2050, Thesis

July 3, 2014 by hgpu

Medusa: A Parallel Graph Processing System on Graphics Processors

Jianlong Zhong, Bingsheng He

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

June 19, 2014 by hgpu

Revisiting Edge and Node Parallelism for Dynamic GPU Graph Analytics

Adam McLaughlin, David A. Bader

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 560, Tesla C2075

June 3, 2014 by hgpu

Hardware/Software Vectorization for Closeness Centrality on Multi-/Many-Core Architectures

A.E. Sarıyuce, E. Saule, K. Kaya, U.V. Çatalyurek

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Tags: Algorithms, Graph theory, Intel Xeon Phi, Parallelization

March 29, 2014 by hgpu

Fast Exact Hyper-Graph Matching with Dynamic Programming for Spatio-Temporal Data

Oya Celiktutan, Christian Wolf, Bulent Sankur, Eric Lombardi

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Tags: Algorithms, Computer science, Computer vision, CUDA, Graph theory, nVidia, nVidia GeForce GTS 450, nVidia GeForce GTX 580, Sorting

March 14, 2014 by hgpu

Work-Efficient Parallel GPU Methods for Single-Source Shortest Paths

Andrew Davidson, Sean Baxter, Michael Garland, John D. Owens

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 680, Package

February 15, 2014 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

Parallel Breadth First Search on GPU Clusters

Parallel Distributed Breadth First Search on the Kepler Architecture

Scalable and High Performance Betweenness Centrality on the GPU

Parallelization of BFS Graph Algorithm using CUDA

Understanding the SIMD Efficiency of Graph Traversal on GPU

Massive Parallelism with GPUs for Centrality Ranking in Complex Networks

Exploiting parallel features of modern computer architectures in bioinformatics: applications to genetics, structure comparison and large graph analysis

Medusa: A Parallel Graph Processing System on Graphics Processors

Revisiting Edge and Node Parallelism for Dynamic GPU Graph Analytics

Hardware/Software Vectorization for Closeness Centrality on Multi-/Many-Core Architectures

Fast Exact Hyper-Graph Matching with Dynamic Programming for Spatio-Temporal Data

Work-Efficient Parallel GPU Methods for Single-Source Shortest Paths

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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