high performance computing on graphics processing units: hgpu.org

hgpu.org » Graph theory

VertexAPI2 – A Vertex-Program API for Large Graph Computations on the GPU

Erich Elsen, Vishal Vaidyanathan

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 670, Package

January 16, 2014 by hgpu

A Push-Relabel-Based Maximum Cardinality Bipartite Matching Algorithm on GPUs

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

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

January 5, 2014 by hgpu

Efficient Large-Scale Graph Processing on Hybrid CPU and GPU Systems

Abdullah Gharaibeh, Elizeu Santos-Neto, Lauro Beltrao Costa, Matei Ripeanu

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Tags: Algorithms, Computer science, CUDA, Graph theory, Heterogeneous systems, Hybrid computing, nVidia, Package

December 12, 2013 by hgpu

Speeding up the small progress measures algorithm for parity games using the GPU

P.J.A. Bootsma

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GT 555 M, nVidia GeForce GTX 660 Ti, Thesis

December 6, 2013 by hgpu

A parallel search tree algorithm for vertex cover on graphical processing units

Rashad Karim Kabbara

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

November 24, 2013 by hgpu

Fast Diameter Computation of Large Sparse Graphs using GPUs

Giso H. Dal, Walter A. Kosters, Frank W. Takes

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

November 17, 2013 by hgpu

Parallel CPU and GPU computations to solve the job shop scheduling problem with blocking

Abdelhakim AitZai, Adel Dabah, Mourad Boudhar

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Tags: Computer science, CUDA, Graph theory, nVidia, nVidia Quadro 2000, Task scheduling

November 3, 2013 by hgpu

A New Approach of Performance Analysis of Certain Graph Algorithms

M. F Mridha, Mohammad Manzurul Islam, Syed Mohammad Oliur Rahman

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

October 26, 2013 by hgpu

Work Efficient Parallel Algorithms for Large Graph Exploration

Dip Sankar Banerjee, Shashank Sharma, Kishore Kothapalli

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Tags: Algorithms, Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, nVidia GeForce GTX 580

October 21, 2013 by hgpu

Large Graphs on multi-GPUs

Enrico Mastrostefano

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Tesla X2090, Thesis

September 25, 2013 by hgpu

Exploiting the Parallelism of Heterogeneous Systems using Dataflow Graphs on Top of OpenCL

Lars Schor, Andreas Tretter, Tobias Scherer, Lothar Thiele

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Tags: ATI, ATI Radeon HD 7750, Computer science, Graph theory, Heterogeneous systems, nVidia, nVidia GeForce GTX 670, nVidia Quadro K 2000 M, OpenCL, Task scheduling

August 13, 2013 by hgpu

GPU Acceleration of Graph Matching, Clustering, and Partitioning

Bastiaan Onne Fagginger Auer

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Tags: Algorithms, Clustering, Computer science, CUDA, Graph theory, nVidia, Sparse matrix, Tesla C2075, Thesis

August 6, 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

VertexAPI2 – A Vertex-Program API for Large Graph Computations on the GPU

A Push-Relabel-Based Maximum Cardinality Bipartite Matching Algorithm on GPUs

Efficient Large-Scale Graph Processing on Hybrid CPU and GPU Systems

Speeding up the small progress measures algorithm for parity games using the GPU

A parallel search tree algorithm for vertex cover on graphical processing units

Fast Diameter Computation of Large Sparse Graphs using GPUs

Parallel CPU and GPU computations to solve the job shop scheduling problem with blocking

A New Approach of Performance Analysis of Certain Graph Algorithms

Work Efficient Parallel Algorithms for Large Graph Exploration

Large Graphs on multi-GPUs

Exploiting the Parallelism of Heterogeneous Systems using Dataflow Graphs on Top of OpenCL

GPU Acceleration of Graph Matching, Clustering, and Partitioning

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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