Graph theory | Page 3

hgpu.org » Graph theory

Fine-Grain Acceleration of Graph Algorithms on a Heterogeneous Chip

Cagri Eryilmaz

View

Download (PDF)

Tags: Algorithms, APU, Computer science, Graph theory, Heterogeneous systems, OpenCL, Thesis

July 19, 2017 by hgpu

Gunrock: GPU Graph Analytics

Yangzihao Wang, Yuechao Pan, Andrew Davidson, Yuduo Wu, Carl Yang, Leyuan Wang, Muhammad Osama, Chenshan Yuan, Weitang Liu, Andy T. Riffel, John D. Owens

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Graph theory, nVidia, Package, Tesla K40

January 8, 2017 by hgpu

GPU Concurrency Choices in Graph Analytics

Masab Ahmad, Omer Khan

View

Download (PDF)

Tags: Algorithms, Computer science, Graph theory, nVidia, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX 970, OpenCL

October 8, 2016 by hgpu

A Compiler for Throughput Optimization of Graph Algorithms on GPUs

Sreepathi Pai, Keshav Pingali

View

Download (PDF)

Tags: Compilers, Computer science, CUDA, Graph theory, nVidia, Tesla K40

September 20, 2016 by hgpu

Hybrid CPU-GPU Framework for Network Motifs

Ryan A. Rossi, Rong Zhou

View

Download (PDF)

Tags: Algorithms, Computer science, Graph theory, Machine learning, nVidia, nVidia GeForce GTX Titan Black

August 23, 2016 by hgpu

Study and evaluation of an Irregular Graph Algorithm on Multicore and GPU Processor Architectures

Varun Nagpal

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Performance, Tesla C1060, Thesis

March 10, 2016 by hgpu

Algorithms and Heuristics for Scalable Betweenness Centrality Computation on Multi-GPU Systems

Flavio Vella, Giancarlo Carbone, Massimo Bernaschi

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, Graph theory, nVidia, OpenMPI, Tesla K20, Tesla K80

February 3, 2016 by hgpu

MapGraph: A High Level API for Fast Development of High Performance Graph Analytics on GPUs

Zhisong Fu, Michael Personick, Bryan Thompson

View

Download (PDF)

Source codes

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

December 10, 2015 by hgpu

An Efficient Parallel Algorithm for Graph Isomorphism on GPU using CUDA

Min-Young Son, Young-Hak Kim, Byoung-Woo Oh

View

Download (PDF)

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

December 4, 2015 by hgpu

Parallel Graph Algorithms on the Xeon Phi Coprocessor

Dennis Felsing

View

Download (PDF)

Tags: Algorithms, Computer science, Graph theory, Intel Xeon Phi, OpenMP, Thesis, Visualization

October 6, 2015 by hgpu

A Parallel Algorithm to Test Chordality of Graphs

Agnieszka Lupinska

View

Download (PDF)

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

August 28, 2015 by hgpu

Falcon: A Graph Manipulation Language for Heterogeneous Systems

Unnikrishnan C, Y N Srikant, Rupesh Nasre

View

Download (PDF)

Tags: Compilers, Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, OpenMP, Tesla C2050, Tesla C2075, Tesla K20

June 16, 2015 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

* * *

high performance computing on graphics processing units: hgpu.org

Fine-Grain Acceleration of Graph Algorithms on a Heterogeneous Chip

Gunrock: GPU Graph Analytics

GPU Concurrency Choices in Graph Analytics

A Compiler for Throughput Optimization of Graph Algorithms on GPUs

Hybrid CPU-GPU Framework for Network Motifs

Study and evaluation of an Irregular Graph Algorithm on Multicore and GPU Processor Architectures

Algorithms and Heuristics for Scalable Betweenness Centrality Computation on Multi-GPU Systems

MapGraph: A High Level API for Fast Development of High Performance Graph Analytics on GPUs

An Efficient Parallel Algorithm for Graph Isomorphism on GPU using CUDA

Parallel Graph Algorithms on the Xeon Phi Coprocessor

A Parallel Algorithm to Test Chordality of Graphs

Falcon: A Graph Manipulation Language for Heterogeneous Systems

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

Most viewed papers (last 30 days)