high performance computing on graphics processing units: hgpu.org

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Fast Gather-based Construction of Stereoscopic Images Using Reprojection

Marries van de Hoef, Bas Zalmstra

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Tags: ATI, ATI Radeon HD 5670, ATI Radeon HD 5850, Benchmarking, Cg, Image processing, nVidia, nVidia GeForce 9600 GT, OpenGL, Package

November 18, 2011 by hgpu

Parallel Performance Measurement of Heterogeneous Parallel Systems with GPUs

Allen D. Malony, Scott Biersdorff, Sameer Shende, Heike Jagode, Stanimire Tomov, Guido Juckeland, Robert Dietrich, Duncan Poole, Christopher Lamb

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Tesla C870

November 17, 2011 by hgpu

Prospects for scalable 3D FFTs on heterogeneous exascale systems

Chris McClanahan, Kent Czechowski, Casey Battaglino, Kartik Iyer, P.-K. Yeung, Richard Vuduc

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Tags: Analytical model, Benchmarking, Computer science, CUDA, FFT, GPU cluster, Heterogeneous systems, nVidia, OpenMPI, Package, Tesla M2070

November 16, 2011 by hgpu

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

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

Fast Gather-based Construction of Stereoscopic Images Using Reprojection

Parallel Performance Measurement of Heterogeneous Parallel Systems with GPUs

Prospects for scalable 3D FFTs on heterogeneous exascale systems

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

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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