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

AutoDock-GPU: AutoDock for GPUs and other accelerators

Architecting Tensor Core-Based Reductions for Irregular Molecular Docking Kernels

NCCLX: collective communication framework

Collective Communication for 100k+ GPUs

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

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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

AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

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