high performance computing on graphics processing units: hgpu.org

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An Ultrafast Scalable Many-core Motif Discovery Algorithm for Multiple GPUs

Yongchao Liu, Bertil Schmidt, Douglas L. Maskell

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Tags: Algorithms, Benchmarking, Biology, CUDA, GPU cluster, MPI, nVidia, OpenMP, Package, Tesla S2050

November 15, 2011 by hgpu

GStream: A General-Purpose Data Streaming Framework on GPU Clusters

Yongpeng Zhang, Frank Mueller

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Data parallelism, GPU cluster, nVidia, Tesla C2050

November 15, 2011 by hgpu

Comprehensive Performance Monitoring for GPU Cluster Systems

K. Furlinger, N.J. Wright, D. Skinner

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Tags: Benchmarking, Computer science, CUDA, GPU cluster, MPI, nVidia, Performance, Tesla C2050

November 13, 2011 by hgpu

Run, Stencil, Run! – A Comparison of Modern Parallel Programming Paradigms

Helmar Burkhart, Matthias Christen, Max Rietmann, Madan Sathe, Olaf Schenk

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Tags: Benchmarking, Computer science, CUDA, MPI, nVidia, OpenMP, Tesla C2050

November 10, 2011 by hgpu

Generation of planar radiographs from 3D anatomical models using the GPU

Andre dos Santos Cardoso

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Tags: Algorithms, Benchmarking, CUDA, Data parallelism, Image processing, Image registration, Medicine, nVidia, nVidia GeForce GT 240, Optimization, Thesis

November 10, 2011 by hgpu

Automatic transformation and optimization of applications on GPUs and GPU clusters

Wenjing Ma

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Tags: Algorithm optimization, Algorithms, Benchmarking, Code generation, Computer science, CUDA, Data mining, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 9800 GX2, Optimization, Tesla T10, Thesis

November 9, 2011 by hgpu

Performance analysis of a hybrid MPI/CUDA implementation of the NASLU benchmark

S.J. Pennycook, S.D. Hammond, S.A. Jarvis, G.R. Mudalige

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Tags: Benchmarking, Computer science, CUDA, MPI, nVidia, nVidia GeForce 8400 GS, nVidia GeForce 9400 GT, Operating systems, Performance, Tesla C1060, Tesla C2050, Tesla T10

November 8, 2011 by hgpu

Global memory access modelling for efficient implementation of the lattice Boltzmann method on graphics processing units

Christian Obrecht, Frederic Kuznik, Bernard Tourancheau, Jean-Jacques Roux

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Tags: Benchmarking, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 295

November 6, 2011 by hgpu

Parallelization of maximum likelihood fits with OpenMP and CUDA

Sverre Jarp, Alfio Lazzaro, Julien Leduc, Andrzej Nowak, Felice Pantaleo

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Tags: Algorithms, Benchmarking, CUDA, Numerical Analysis, nVidia, nVidia GeForce GTX 470, OpenMP, Physics

November 4, 2011 by hgpu

Topology Optimization with Unstructured Meshes on Graphics Processing Units (GPUs)

Tomas Zegard Latrach

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, Optimization, Tesla T10, Thesis

November 3, 2011 by hgpu

Acceleration Methods for Bayesian Network Sampling

Haohai Yu

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Bayesian, Benchmarking, Clustering, Computer science, OpenCL, Probability, Thesis

November 2, 2011 by hgpu

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Efficient deep learning inference on end devices

Ouroboros: Virtualized Queues for dynamic memory management

Dynamic Memory Management on GPUs with SYCL

MSCCL++: A GPU-driven communication stack for scalable AI applications

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

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high performance computing on graphics processing units: hgpu.org

An Ultrafast Scalable Many-core Motif Discovery Algorithm for Multiple GPUs

GStream: A General-Purpose Data Streaming Framework on GPU Clusters

Comprehensive Performance Monitoring for GPU Cluster Systems

Run, Stencil, Run! – A Comparison of Modern Parallel Programming Paradigms

Generation of planar radiographs from 3D anatomical models using the GPU

Automatic transformation and optimization of applications on GPUs and GPU clusters

Performance analysis of a hybrid MPI/CUDA implementation of the NASLU benchmark

Global memory access modelling for efficient implementation of the lattice Boltzmann method on graphics processing units

Parallelization of maximum likelihood fits with OpenMP and CUDA

Topology Optimization with Unstructured Meshes on Graphics Processing Units (GPUs)

Acceleration Methods for Bayesian Network Sampling

Recent source codes

SYCL Container

CASS: Cuda-Amd aSSembly

Cluser of smartphones for edge computing application using TensorFlow

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

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