high performance computing on graphics processing units: hgpu.org

hgpu.org » Graph theory

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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Source codes

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

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

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

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

Graph-Based Substructure Pattern Mining Using CUDA Dynamic Parallelism

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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