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Parallel algorithms to a parallel hardware: Designing vision algorithms for a GPU

Jun-Sik Kim, Myung Hwangbo, Takeo Kanade

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce 8800 GTX, Optical flow

January 8, 2011 by hgpu

A Unified Runtime System for Heterogeneous Multi-core Architectures

Cedric Augonnet, Raymond Namyst

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Tags: Computer science, CUDA, Heterogeneous systems, Memory, nVidia, nVidia Quadro FX 4600

January 7, 2011 by hgpu

JCUDA: A Programmer-Friendly Interface for Accelerating Java Programs with CUDA

Yonghong Yan, Max Grossman, Vivek Sarkar

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Tags: Computer science, CUDA, Java, nVidia, Package, Tesla C1060

January 7, 2011 by hgpu

Power Consumption of GPUs from a Software Perspective

Sylvain Collange, David Defour, Arnaud Tisserand

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce 9800 GX2, Tesla C870, Tesla D870, Tesla T10P

January 7, 2011 by hgpu

Fast BVH Construction on GPUs

C. Lauterbach, M. Garland, S. Sengupta, D. Luebke, D. Manocha

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Tags: Collision detection, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Raytracing

January 7, 2011 by hgpu

Accelerating phase unwrapping and affine transformations for optical quadrature microscopy using CUDA

Perhaad Mistry, Sherman Braganza, David Kaeli, Miriam Leeser

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Tags: Biology, CUDA, Genetics, Image processing, nVidia, nVidia GeForce 8800 GTX

January 6, 2011 by hgpu

Synthetic Aperture Radar Processing with GPGPU

Maurizio di Bisceglie, Michele Di Santo, Carmela Galdi, Riccardo Lanari, Nadia Ranaldo

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Tags: CUDA, nVidia, Signal processing, Tesla C1060

January 6, 2011 by hgpu

An asymmetric distributed shared memory model for heterogeneous parallel systems

Isaac Gelado, John E. Stone, Javier Cabezas, Sanjay Patel, Nacho Navarro, Wen-mei W. Hwu

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Tags: Computer science, CUDA, Memory, Memory model, nVidia, nVidia GeForce GTX 280

January 6, 2011 by hgpu

Efficient gather and scatter operations on graphics processors

Bingsheng He, Naga K. Govindaraju, Qiong Luo, Burton Smith

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800, Search, Sorting, Sparse matrix

January 6, 2011 by hgpu

q-state Potts model metastability study using optimized GPU-based Monte Carlo algorithms

Ezequiel E. Ferrero, Juan Pablo De Francesco, Nicolas Wolovick, Sergio A. Cannas

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Tags: Computational Physics, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 470, nVidia GeForce GTX 480, Package, Physics, Statistical Mechanics

January 6, 2011 by hgpu

Speeding Up Homomorpic Hashing Using GPUs

K. Zhao, X. Chu, M. Z. Wang, Y. Jiang

Tags: Algorithms, Computer science, CUDA, nVidia, Security

January 5, 2011 by hgpu

Significantly Improved Performances Of The Cryptographically Generated Addresses Thanks To ECC And GPGPU

Tony Cheneau, Aymen Boudguiga, Maryline Laurent

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8600 GT, nVidia GeForce 8600 GTS, Security

January 5, 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

Parallel algorithms to a parallel hardware: Designing vision algorithms for a GPU

A Unified Runtime System for Heterogeneous Multi-core Architectures

JCUDA: A Programmer-Friendly Interface for Accelerating Java Programs with CUDA

Power Consumption of GPUs from a Software Perspective

Fast BVH Construction on GPUs

Accelerating phase unwrapping and affine transformations for optical quadrature microscopy using CUDA

Synthetic Aperture Radar Processing with GPGPU

An asymmetric distributed shared memory model for heterogeneous parallel systems

Efficient gather and scatter operations on graphics processors

q-state Potts model metastability study using optimized GPU-based Monte Carlo algorithms

Speeding Up Homomorpic Hashing Using GPUs

Significantly Improved Performances Of The Cryptographically Generated Addresses Thanks To ECC And GPGPU

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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