high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

RenderAnts: Interactive REYES Rendering on GPUs

Kun Zhou, Qiming Hou, Zhong Ren, Minmin Gong, Xin Sun, Baining Guo

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Tags: Computer science, Image generation, nVidia, nVidia GeForce GTX 280, Package, Raytracing, Rendering, Shaders

November 5, 2010 by hgpu

Accelerating MATLAB Image Processing Toolbox functions on GPUs

Jingfei Kong, Martin Dimitrov, Yi Yang, Janaka Liyanage, Lin Cao, Jacob Staples, Mike Mantor, Huiyang Zhou

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Tags: ATI, ATI Radeon HD 5870, CUDA, Image processing, nVidia, nVidia GeForce GTX 280, OpenCL, RV870

November 5, 2010 by hgpu

Accelerating advanced MRI reconstructions on GPUs

Samuel S. Stone, Justin P. Haldar, Stephanie C. Tsao, Wen-Mei W. Hwu, Zhi-Pei Liang, Bradley P. Sutton

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

November 5, 2010 by hgpu

Efficient computation of sum-products on GPUs through software-managed cache

Mark Silberstein,Assaf Schuster,Dan Geiger,Anjul Patney,John D. Owens

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Programming techniques

November 5, 2010 by hgpu

Iterative induced dipoles computation for molecular mechanics on GPUs

Frederico Pratas,Ricardo A. Mata,Leonel Sousa

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Tags: Chemistry, Computational chemistry, Computer science, CUDA, Molecular dynamics, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 285

November 5, 2010 by hgpu

The Scalable Heterogeneous Computing (SHOC) benchmark suite

Anthony Danalis,Gabriel Marin,Collin McCurdy,Jeremy S. Meredith,Philip C. Roth,Kyle Spafford,Vinod Tipparaju,Jeffrey S. Vetter

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Source codes

Tags: ATI, ATI Radeon HD 5770, ATI Radeon HD 5870, ATI Stream, Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GT, nVidia GeForce 8800 GTS, nVidia GeForce 8800 GTX, nVidia GeForce 9400 M, OpenCL, Package, Performance, Tesla C1060

November 5, 2010 by hgpu

Designing efficient sorting algorithms for manycore GPUs

Nadathur Satish,Mark Harris,Michael Garland

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 Ultra, Sorting

November 5, 2010 by hgpu

Best-effort semantic document search on GPUs

Surendra Byna,Jiayuan Meng,Anand Raghunathan,Srimat Chakradhar,Srihari Cadambi

Tags: Computer science, nVidia, Programming techniques, Semantic indexing, Tesla C870

November 5, 2010 by hgpu

Sparse matrix solvers on the GPU: conjugate gradients and multigrid

Jeff Bolz,Ian Farmer,Eitan Grinspun,Peter Schrooder

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Tags: Computer science, Fluid simulation, Navier-Stokes equations, NSEs, Numerical simulation, nVidia, Sparse matrix

November 5, 2010 by hgpu

A Survey of General-Purpose Computation on Graphics Hardware

John D. Owens, David Luebke, Naga Govindaraju, Mark Harris, Jens Kruger, Aaron E. Lefohn, and Timothy J. Purcell

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Tags: Algorithms, Computer science, Review

November 5, 2010 by hgpu

NVIDIA Tesla: A Unified Graphics and Computing Architecture

Erik Lindholm, J. Nickolls, S. Oberman, J. Montrym

Tags: Computer science, Hardware, nVidia, Review, Tesla

November 5, 2010 by hgpu

Accelerator: using data parallelism to program GPUs for general-purpose uses

David Tarditi, Sidd Puri, Jose Oglesby

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Tags: ATI, ATI Radeon X1800, ATI Radeon X850 XT, Computer science, High-level Languages, nVidia, nVidia GeForce 6800 Ultra, nVidia GeForce 7800 GTX

November 5, 2010 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

Applications

RenderAnts: Interactive REYES Rendering on GPUs

Accelerating MATLAB Image Processing Toolbox functions on GPUs

Accelerating advanced MRI reconstructions on GPUs

Efficient computation of sum-products on GPUs through software-managed cache

Iterative induced dipoles computation for molecular mechanics on GPUs

The Scalable Heterogeneous Computing (SHOC) benchmark suite

Designing efficient sorting algorithms for manycore GPUs

Best-effort semantic document search on GPUs

Sparse matrix solvers on the GPU: conjugate gradients and multigrid

A Survey of General-Purpose Computation on Graphics Hardware

NVIDIA Tesla: A Unified Graphics and Computing Architecture

Accelerator: using data parallelism to program GPUs for general-purpose uses

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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