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Neon: A Domain-Specific Programming Language for Image Processing

Brian Guenter, Diego Nehab

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Tags: ATI, ATI Radeon HD 4850, ATI Radeon HD 5870, Code generation, DirectX, High-level Languages, HLSL, Image processing, nVidia, nVidia GeForce GTX 470, Pixel shaders

November 18, 2011 by hgpu

Adaboost GPU-based Classifier for Direct Volume Rendering

Oscar Amoros, Sergio Escalera, Anna Puig

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Tags: Computer science, CUDA, GLSL, Machine learning, nVidia GeForce 8800 GTX, nVidia GeForce GTX 470, OpenCL, OpenGL, Rendering, Visualization

November 17, 2011 by hgpu

A Full-Depth Amalgamated Parallel 3D Geometric Multigrid Solver for GPU Clusters

Dana A. Jacobsen

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Tags: Algorithms, CUDA, Fluid dynamics, GPU cluster, Laplace and Poisson equation, MPI, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce GTX 470, Poisson equation, Tesla S1070

November 16, 2011 by hgpu

Building a Real-Time Multi-GPU Platform: Robust Real-Time Interrupt Handling Despite Closed-Source Drivers

Glenn A. Elliott, James H. Anderson

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Source codes

Tags: Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce GTX 470, Package, Performance

November 11, 2011 by hgpu

Real-time Sliding Phase Vocoder using a Commodity GPU

Russell Bradford, John ffitch, Richard Dobson

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Tags: Algorithms, CUDA, nVidia, nVidia GeForce GTX 470, Signal processing

November 6, 2011 by hgpu

CUDA-Accelerated Geodesic Ray-Tracing for Fiber Tracking

Evert van Aart, Neda Sepasian, Andrei Jalba, Anna Vilanova

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Tags: Algorithms, Computer science, CUDA, Diffusion tensor, nVidia, nVidia GeForce GTX 470, Raytracing

November 5, 2011 by hgpu

Parallelization of maximum likelihood fits with OpenMP and CUDA

Sverre Jarp, Alfio Lazzaro, Julien Leduc, Andrzej Nowak, Felice Pantaleo

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Tags: Algorithms, Benchmarking, CUDA, Numerical Analysis, nVidia, nVidia GeForce GTX 470, OpenMP, Physics

November 4, 2011 by hgpu

Optimizing and Auto-tuning Belief Propagation on the GPU

Scott Grauer-Gray, John Cavazos

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 470, Optimization, Tesla C870

October 30, 2011 by hgpu

An Evolutionary Optimization Strategy Using Graphics Processing Units to Efficiently Investigate Gene-Gene Interactions in Genetic Association Studies

Joel B. Fontanarosa, Yang Dai

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Tags: Algorithms, Biology, CUDA, Evolutionary Computations, Genetics, nVidia, nVidia GeForce GTX 470, Optimization

October 25, 2011 by hgpu

APTCC: Auto Parallelizing Translator From C To CUDA

Takehiko Nawataa, Reiji Suda

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 580, Tesla C2050

October 24, 2011 by hgpu

Massively Parallel Algorithms for CFD Simulation and Optimization on Heterogeneous Many-Core Architectures

Austen C. Duffy

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Tags: Algorithms, CUDA, Fluid dynamics, Fortran, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 480, Optimization, Partial differential equations, PDEs, Thesis

October 23, 2011 by hgpu

Evaluating the Performance and Portability of OpenCL

Jarno van der Sanden

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Tags: Algorithms, ATI, ATI Radeon HD 5850, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, OpenCL, Performance, Thesis

October 18, 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

Neon: A Domain-Specific Programming Language for Image Processing

Adaboost GPU-based Classifier for Direct Volume Rendering

A Full-Depth Amalgamated Parallel 3D Geometric Multigrid Solver for GPU Clusters

Building a Real-Time Multi-GPU Platform: Robust Real-Time Interrupt Handling Despite Closed-Source Drivers

Real-time Sliding Phase Vocoder using a Commodity GPU

CUDA-Accelerated Geodesic Ray-Tracing for Fiber Tracking

Parallelization of maximum likelihood fits with OpenMP and CUDA

Optimizing and Auto-tuning Belief Propagation on the GPU

An Evolutionary Optimization Strategy Using Graphics Processing Units to Efficiently Investigate Gene-Gene Interactions in Genetic Association Studies

APTCC: Auto Parallelizing Translator From C To CUDA

Massively Parallel Algorithms for CFD Simulation and Optimization on Heterogeneous Many-Core Architectures

Evaluating the Performance and Portability of OpenCL

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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