high performance computing on graphics processing units: hgpu.org

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Parallel Smoothers for Matrix-based Multigrid Methods on Unstructured Meshes Using Multicore CPUs and GPUs

Vincent Heuveline, Dimitar Lukarski, Nico Trost, Jan-Philipp Weiss

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Tags: Algorithms, Computer science, CUDA, Differential equations, Linear Algebra, nVidia, Package, Partial differential equations, PDEs, Tesla S1070

October 31, 2011 by hgpu

High-performance software rasterization on GPUs

Samuli Laine, Tero Karras

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Rasterization

October 31, 2011 by hgpu

CPU and GPU Co-processing for Sound

Aleksander Gjermundsen

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Computer science, Filtering, Linear Algebra, nVidia, nVidia GeForce GTX 280, OpenCL, Package, Signal processing, Tesla C2050, Thesis

October 30, 2011 by hgpu

Parallel Random Numbers: As Easy as 1, 2, 3

John K. Salmon, Mark A. Moraes, Ron O. Dror, and David E. Shaw

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Tags: AES, ATI, ATI Radeon HD 6970, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Performance, Pseudo-random number generators, Security

October 28, 2011 by hgpu

Programming Massively Parallel Processors with CUDA (audio course)

David B. Kirk, Wen-Mei W. Hwu

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Tags: Book, Computer science, CUDA, nVidia, OpenCL, Package, Programming techniques, Review, Tutorial

October 28, 2011 by hgpu

Efficient Implementation and Evaluation of Methods for the Estimation of Motion in Image Sequences

Robert Hegner

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 260, Optical flow, Package, Thesis

October 27, 2011 by hgpu

Efficient Implementation of Optical Flow Algorithm Based on Directional Filters on a GPU Using CUDA

Robert Hegner, Ivar Austvoll, Tom Ryen, Guido M. Schuster

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 260, Optical flow, Package

October 27, 2011 by hgpu

Quasars spectra classification with the help of GPU computing

P. Wasiewicz, K. Hryniewicz

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Tags: Astrophysics, CUDA, Databases, Numerical Analysis, nVidia, Package

October 26, 2011 by hgpu

Extending Scala with General Purpose GPU Programming

Reidar Beck, Helge Willum Larsen, Tommy Jensen

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Tags: Benchmarking, Code generation, Compilers, Computer science, Java, nVidia, OpenCL, Package, Tesla C870

October 25, 2011 by hgpu

Democratizing General Purpose GPU Programming through OpenCL and Scala

Raider Beck, Helge Willum Larsen, Tommy Jensen

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Tags: Benchmarking, Code generation, Compilers, Computer science, nVidia, OpenCL, Package, Tesla C870

October 24, 2011 by hgpu

The MOSIX Virtual OpenCL (VCL) Cluster Platform

Amnon Barak, Amnon Shiloh

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Tags: APU, Computer science, GPU cluster, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 480, OpenCL, Operating systems, Package

October 24, 2011 by hgpu

Power and Performance Studies of the Explicit Multi-Threading (XMT) Architecture

Fuat Keceli

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Tags: Algorithms, ASIC, Benchmarking, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 280, Package, Performance, Thesis

October 23, 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

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high performance computing on graphics processing units: hgpu.org

Packages

Parallel Smoothers for Matrix-based Multigrid Methods on Unstructured Meshes Using Multicore CPUs and GPUs

High-performance software rasterization on GPUs

CPU and GPU Co-processing for Sound

Parallel Random Numbers: As Easy as 1, 2, 3

Programming Massively Parallel Processors with CUDA (audio course)

Efficient Implementation and Evaluation of Methods for the Estimation of Motion in Image Sequences

Efficient Implementation of Optical Flow Algorithm Based on Directional Filters on a GPU Using CUDA

Quasars spectra classification with the help of GPU computing

Extending Scala with General Purpose GPU Programming

Democratizing General Purpose GPU Programming through OpenCL and Scala

The MOSIX Virtual OpenCL (VCL) Cluster Platform

Power and Performance Studies of the Explicit Multi-Threading (XMT) Architecture

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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