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A Dynamic Resource Management System for Network-Attached Accelerator Clusters

Suraj Prabhakaran, Mohsin Iqbal, Sebastian Rinke, Felix Wolf

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia

October 17, 2013 by hgpu

Performance Comparison of GPU, DSP and FPGA implementations of image processing and computer vision algorithms in embedded systems

Egil Fykse

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Source codes

Tags: Benchmarking, Computer science, Computer vision, CUDA, DSP, FPGA, Image processing, nVidia, nVidia GeForce GTX 660 Ti, nVidia Quadro 1000 M, OpenCV, Performance, Thesis

October 15, 2013 by hgpu

Domain-Specific Languages for Heterogeneous Parallel Computing

HyoukJoong Lee, Kevin J. Brown, Arvind K. Sujeeth, Hassan Chafi, Tiark Rompf, Martin Odersky, Kunle Olukotun

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, Tesla C2050

October 15, 2013 by hgpu

GPU-acceleration of parallel unconditionally stable group explicit finite difference method

K. Parand, Saeed Zafarvahedian, Sayyed A. Hossayni

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Tags: Algorithms, Computer science, CUDA, Finite difference, Numerical Analysis, nVidia, nVidia GeForce GT 335 M

October 15, 2013 by hgpu

GPU-Framework for Teamwork Action Recognition

Mohamed Elhoseiny, Hossam Faheem, Taymour Nazmy, Eman Shaaban

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Tags: Computer science, Computer vision, CUDA, Machine learning, nVidia, nVidia GeForce 9500 GT, OpenCV

October 15, 2013 by hgpu

An Efficient WSN Simulator for GPU-Based Node Performance

An Na Kang, Hyun-Woo Kim, Leonard Barolli, Young-Sik Jeong

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Tags: Computer science, CUDA, nVidia, Sensing

October 15, 2013 by hgpu

High-Performance GPGPU Programming with OCaml

Mathias Bourgoin, Emmanuel Chailloux, Jean-Luc Lamotte

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Tags: ATI, ATI Radeon HD 6950, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 680, OpenCL, Tesla C2070

October 15, 2013 by hgpu

Uses of GPU Powered Interval Optimization for Parameter Identification in the Context of SO Fuel Cells

Stefan Kiel, Ekaterina Auer, Andreas Rauh

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Tags: Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GTX 580, ODEs, Ordinary differential equations

October 15, 2013 by hgpu

GPU-Specfic Kalman Filtering and Retrodiction for Large-Scale Target Tracking

Sean Tager

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Tags: Algorithms, Computer science, Filtering, Thesis

October 13, 2013 by hgpu

Power Control for GPU Clusters in processing large-scale streams

Qingkui Chen, Haifeng Wang, Bocheng Liu

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Tags: Computer science, CUDA, Energy-efficient computing, GPU cluster, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480

October 13, 2013 by hgpu

Contributions to parallel stochastic simulation: Application of good software engineering practices to the distribution of pseudorandom streams in hybrid Monte-Carlo simulations

Jonathan Passerat-Palmbach

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Tags: Algorithms, Computer science, CUDA, Java, Monte Carlo simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 590, OpenCL, Pseudo-random number generators, Software Engineering, Stochastic simulation, Tesla C2050, Tesla C2075, Tesla K20, Thesis

October 13, 2013 by hgpu

Simulating Active Membrane Systems Using GPUs

Miguel A. Martinez-del-Amor, Ignacio Perez-Hurtado, Mario J. Perez-Jimenez, Jose M. Cecilia, Gines D. Guerrero, Jose M. Garcia

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Tags: Computer science, CUDA, Membrane computing, nVidia, Tesla C1060

October 13, 2013 by hgpu

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

Unified schemes for directive-based GPU offloading

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

See all packages

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high performance computing on graphics processing units: hgpu.org

A Dynamic Resource Management System for Network-Attached Accelerator Clusters

Performance Comparison of GPU, DSP and FPGA implementations of image processing and computer vision algorithms in embedded systems

Domain-Specific Languages for Heterogeneous Parallel Computing

GPU-acceleration of parallel unconditionally stable group explicit finite difference method

GPU-Framework for Teamwork Action Recognition

An Efficient WSN Simulator for GPU-Based Node Performance

High-Performance GPGPU Programming with OCaml

Uses of GPU Powered Interval Optimization for Parameter Identification in the Context of SO Fuel Cells

GPU-Specfic Kalman Filtering and Retrodiction for Large-Scale Target Tracking

Power Control for GPU Clusters in processing large-scale streams

Contributions to parallel stochastic simulation: Application of good software engineering practices to the distribution of pseudorandom streams in hybrid Monte-Carlo simulations

Simulating Active Membrane Systems Using GPUs

Recent source codes

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

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