high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Stochastic transparency

Eric Enderton, Erik Sintorn, Peter Shirley, David Luebke

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Tags: 3D Graphics and Realism, Algorithms, Computer science, DirectX, OpenGL, Rendering

February 5, 2011 by hgpu

NeMo: A Platform for Neural Modelling of Spiking Neurons Using GPUs

Andreas Fidjeland, Etienne B. Roesch, Murray P. Shanahan, Wayne Luk

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Source codes

Tags: Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 280, Package, Tesla C1060

February 5, 2011 by hgpu

Model-driven autotuning of sparse matrix-vector multiply on GPUs

Jee W. Choi, Amik Singh, Richard W. Vuduc

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, Performance, Sparse matrix, Tesla C1060, Tesla C870, Tesla T10P

February 5, 2011 by hgpu

Real-Time Face Pose Estimation from Single Range Images

Michael D. Breitenstein, Daniel Kuettel, Thibaut Weise, Luc van Gool, and Hanspeter Pfister

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce 8800 GTX

February 5, 2011 by hgpu

QR decomposition on GPUs

Andrew Kerr, Dan Campbell, Mark Richards

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Matrix decomposition, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280

February 5, 2011 by hgpu

Real-Time Prediction of Brain Shift Using Nonlinear Finite Element Algorithms

Grand Roman Joldes, Adam Wittek, Mathieu Couton, Simon K. Warfield and Karol Miller

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Tags: CUDA, Finite element method, Image processing, Image registration, Medicine, MRI, nVidia

February 5, 2011 by hgpu

GPGPU-compatible archive based stochastic ranking evolutionary algorithm (G-ASREA) for multi-objective optimization

Deepak Sharma, Pierre Collet

Tags: Algorithms, Computer science, Evolutionary Computations

February 4, 2011 by hgpu

Accelerating total variation regularization for matrix-valued images on GPUs

Maryam Moazeni, Alex A. T. Bui, Majid Sarrafzadeh

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia Quadro FX 5600

February 4, 2011 by hgpu

Lattice Based Volumetric Global Illumination

Feng Qiu, Fang Xu, Zhe Fan, Neophytou Neophytos, Arie Kaufman, Klaus Mueller

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Tags: 3D Graphics and Realism, Algorithms, Computer science, nVidia, nVidia GeForce 8800 GTX, Rendering, Visualization

February 4, 2011 by hgpu

QUDA programming for staggered quarks

Steven Gottlieb, Guochun Shi, Aaron Torok, Volodymyr Kindratenko

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Tags: CUDA, High Energy Physics - Lattice, Monte Carlo simulation, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Package, Physics, QCD, Tesla C1060, Tesla C2050, Tesla S1070

February 4, 2011 by hgpu

Phoenix: A Runtime Environment for High Performance Computing on Chip Multiprocessors

Avneesh Pant, Hassan Jafri, Volodymyr Kindratenko

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Tags: Algorithms, Computer science, MPI

February 4, 2011 by hgpu

QP: A Heterogeneous Multi-Accelerator Cluster

Michael Showerman, Jeremy Enos, Avneesh Pant, Volodymyr Kindratenko, Craig Steffen, Robert Pennington, Wen-mei Hwu

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Tags: Computer science, CUDA, FPGA, GPU cluster, nVidia, nVidia Quadro FX 5600, Review

February 4, 2011 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Stochastic transparency

NeMo: A Platform for Neural Modelling of Spiking Neurons Using GPUs

Model-driven autotuning of sparse matrix-vector multiply on GPUs

Real-Time Face Pose Estimation from Single Range Images

QR decomposition on GPUs

Real-Time Prediction of Brain Shift Using Nonlinear Finite Element Algorithms

GPGPU-compatible archive based stochastic ranking evolutionary algorithm (G-ASREA) for multi-objective optimization

Accelerating total variation regularization for matrix-valued images on GPUs

Lattice Based Volumetric Global Illumination

QUDA programming for staggered quarks

Phoenix: A Runtime Environment for High Performance Computing on Chip Multiprocessors

QP: A Heterogeneous Multi-Accelerator Cluster

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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