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Benchmarks Based on Anti-Parallel Patterns for the Evaluation of GPUs

Jan G. Cornelis, Jan Lemeire

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Tags: ATI, ATI Radeon HD 5850, Benchmarking, Computer science, nVidia, nVidia GeForce GTX 280, OpenCL

October 10, 2011 by hgpu

Real time ultrasound image denoising

F. P. X. de Fontes, G. A. Barroso, P. Coupé, P. Hellier

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Tags: CUDA, Filtering, Image processing, Medicine, nVidia GeForce GTX 280, Ultrasound

October 9, 2011 by hgpu

Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)

W.J. Palenstijna, K.J. Batenburga, J. Sijbersa

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Tags: Biology, Image reconstruction, Medicine, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Tomography

October 8, 2011 by hgpu

Multi-core programming with OpenCL: performance and portability: OpenCL in a memory bound scenario

Olav Aanes Fagerlund

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Tags: Computer science, CUDA, FEM, Finite element method, nVidia, nVidia GeForce GTX 280, OpenCL, Thesis

October 6, 2011 by hgpu

Profiling Heterogeneous Multi-GPU Systems to Accelerate Cortically Inspired Learning Algorithms

Andrew Nere, Atif Hashmi, Mikko Lipasti

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Image recognition, Neural networks, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, Optimization, Tesla C2050

October 5, 2011 by hgpu

High-Order Discontinuous Galerkin Methods by GPU Metaprogramming

Andreas Klockner, Timothy Warburton, Jan S. Hesthaven

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Tags: CUDA, Differential equations, Mathematics, nVidia, nVidia GeForce GTX 280, Python, Tesla T10

October 5, 2011 by hgpu

Architecture-Aware Optimization on a 1600-core Graphics Processor

Mayank Daga, Thomas R.W. Scogland, Wu-chun Feng

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Tags: ATI, ATI Radeon HD 5870, Cluster computing, Computer science, CUDA, Molecular modeling, nVidia, nVidia GeForce GTX 280, OpenCL, Optimization, Tesla C2050

October 4, 2011 by hgpu

Finite element assembly strategies on multi-and many-core architectures

G. R. Markall, A. Slemmer, D. A .Ham, P. H. J. Kelly, C. D. Cantwell, S. J. Sherwin

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Tags: Algorithms, ATI, ATI Radeon HD 5870, CUDA, FEM, Finite element method, Fluid dynamics, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL, Spectral elements

October 4, 2011 by hgpu

An OpenCL Fast Fourier Transformation

Sven De Smet

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Tags: Computer science, Data Structures and Algorithms, FFT, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 9400 M, nVidia GeForce GTX 220, nVidia GeForce GTX 280, OpenCL

October 3, 2011 by hgpu

An Execution Model and Runtime For Heterogeneous Many-Core Systems

Gregory Diamos

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Source codes

Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, Optimization, Package, PTX, Tesla C1060, Tesla S870, Thesis

October 2, 2011 by hgpu

A Comprehensive Performance Comparison of CUDA and OpenCL

Jianbin Fang, Ana Lucia Varbanescu, Henk Sips

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Cell processor, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL, Optimization, Performance

October 1, 2011 by hgpu

Interactive Soft Tissue for Surgical Simulation

Gregory S. Ruthenbeck

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Tags: Algorithms, CUDA, Medicine, nVidia, nVidia GeForce GTX 280, Surgical simulation, Thesis, Virtual reality

October 1, 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

Benchmarks Based on Anti-Parallel Patterns for the Evaluation of GPUs

Real time ultrasound image denoising

Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)

Multi-core programming with OpenCL: performance and portability: OpenCL in a memory bound scenario

Profiling Heterogeneous Multi-GPU Systems to Accelerate Cortically Inspired Learning Algorithms

High-Order Discontinuous Galerkin Methods by GPU Metaprogramming

Architecture-Aware Optimization on a 1600-core Graphics Processor

Finite element assembly strategies on multi-and many-core architectures

An OpenCL Fast Fourier Transformation

An Execution Model and Runtime For Heterogeneous Many-Core Systems

A Comprehensive Performance Comparison of CUDA and OpenCL

Interactive Soft Tissue for Surgical Simulation

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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