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Computation on GPU of Eigenvalues and Eigenvectors of a Large Number of Small Hermitian Matrices

Alain Cosnuau

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Matrix decomposition, nVidia, Tesla M2070

June 27, 2014 by hgpu

Image Noise Removal on Heterogeneous CPU-GPU Configurations

Maria G. Sanchez, Vicente Vidal, Josep Arnal, Anna Vidal

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Tags: Algorithms, CUDA, Filtering, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GT 120, OpenMP, Signal denoising

June 27, 2014 by hgpu

Speeding up a Video Summarization Approach Using GPUs and Multicore CPUs

Suellen S. de Almeida, Antonio Carlos de Nazare Junior, Arnaldo de Albuquerque Arauujo, Guillermo Camara-Chavez, David Menotti

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 650, Package

June 27, 2014 by hgpu

Fast LBP Face Detection on low-power SIMD architectures

Olexa Bilaniuk, Ehsan Fazl-Ersi, Robert Laganiere, Christina Xu, Daniel Laroche, Craig Moulder

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Tags: Algorithms, Computer science, Computer vision, FPGA, OpenCV

June 26, 2014 by hgpu

GPU accelerated Hybrid Tree Algorithm for Collision-less N-body Simulations

Tsuyoshi Watanabe, Naohito Nakasato

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Tags: Algorithms, Astrophysics, GPU cluster, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, OpenCL, Tesla M2090

June 25, 2014 by hgpu

GPU-driven Parallel Processing for Realtime Creation of Tree Animation

Sang-Min Song, Young-Min Kang, Kang-Hyuk Lee, Soo-Yol Ok

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Real-time graphics

June 24, 2014 by hgpu

Feature Generation for Quantification of Visual Similarity

Tianning Steven Han

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Tags: Algorithms, Computer science, Computer vision, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 480, Tesla K20, Thesis

June 23, 2014 by hgpu

An efficient parallel algorithm for accelerating computational protein design

Yichao Zhou, Wei Xu, Bruce R. Donald, Jianyang Zeng

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Java, nVidia, Package, Tesla K20

June 23, 2014 by hgpu

A Scala Prototype to Generate Multigrid Solver Implementations for Different Problems and Target Multi-Core Platforms

Harald Koestler, Christian Schmitt, Sebastian Kuckuk, Frank Hannig, Juergen Teich, Ulrich Ruede

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Tags: Algorithms, Computer science, CUDA, Differential equations, Mathematical Software, nVidia, nVidia GeForce GTX 680, Partial differential equations, PDEs

June 23, 2014 by hgpu

Real-Time Deformation of Subdivision Surfaces from Object Collisions

Henry Schafer, Benjamin Keinert, Matthias Niessner, Christoph Buchenau, Michael Guthe, Marc Stamminger

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Tags: 3D Graphics and Realism, Algorithms, Computer science, DirectX, HLSL, nVidia, nVidia GeForce GTX 780, Tessellation, Voxelization

June 22, 2014 by hgpu

Comparison of Random Number Generators in Particle Swarm Optimization Algorithm

Ke Ding, Ying Tan

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti, Particle swarm optimization, Pseudo-random number generators

June 22, 2014 by hgpu

Dealing With Big Data Outside Of The Cloud: GPU Accelerated Sort

John Vidler, Paul Rayson, Laurence Anthony, Andrew Scott, John Mariani

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Tags: Algorithms, Cloud, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, Sorting

June 18, 2014 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Computation on GPU of Eigenvalues and Eigenvectors of a Large Number of Small Hermitian Matrices

Image Noise Removal on Heterogeneous CPU-GPU Configurations

Speeding up a Video Summarization Approach Using GPUs and Multicore CPUs

Fast LBP Face Detection on low-power SIMD architectures

GPU accelerated Hybrid Tree Algorithm for Collision-less N-body Simulations

GPU-driven Parallel Processing for Realtime Creation of Tree Animation

Feature Generation for Quantification of Visual Similarity

An efficient parallel algorithm for accelerating computational protein design

A Scala Prototype to Generate Multigrid Solver Implementations for Different Problems and Target Multi-Core Platforms

Real-Time Deformation of Subdivision Surfaces from Object Collisions

Comparison of Random Number Generators in Particle Swarm Optimization Algorithm

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

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

Most viewed papers (last 30 days)