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Data-parallel computing

Chas. Boyd

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Tags: Computer science, Data parallelism, Review

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

A design case study: CPU vs. GPGPU vs. FPGA

Daniel L. Rosenband, Till Rosenband

Tags: Computer science, CUDA, FPGA, nVidia

January 5, 2011 by hgpu

Revisiting sorting for GPGPU stream architectures

Duane G. Merrill, Andrew S. Grimshaw

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, nVidia GeForce 9800 GT, nVidia GeForce 9800 GTX, nVidia GeForce GTX 280, nVidia GeForce GTX 285, nVidia Quadro FX 5600, Sorting

January 5, 2011 by hgpu

A complete modular resultant algorithm targeted for realization on graphics hardware

Pavel Emeliyanenko

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280

January 5, 2011 by hgpu

Modular Resultant Algorithm for Graphics Processors

Pavel Emeliyanenko

Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280

January 5, 2011 by hgpu

Ubiquitous Parallel Computing from Berkeley, Illinois, and Stanford

Bryan Catanzaro, Armando Fox, Kurt Keutzer, David Patterson, Bor-Yiing Su, Marc Snir, Kunle Olukotun, Pat Hanrahan, Hassan Chafi

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Tags: Computer science, Programming techniques, Review

January 5, 2011 by hgpu

Nuclei: GPU-Accelerated Many-Core Network Coding

Hassan Shojania, Baochun Li, Xin Wang

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Tags: Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce 8600 M GT, nVidia GeForce 8800 GT, nVidia GeForce GTX 280

January 4, 2011 by hgpu

Practical Random Linear Network Coding on GPUs

Xiaowen Chu, Kaiyong Zhao and Mea Wang

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Programming techniques

January 4, 2011 by hgpu

Local Search Algorithms on Graphics Processing Units. A Case Study: The Permutation Perceptron Problem

The Van Luong, Nouredine Melab, El-Ghazali Talbi

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8600 M GT, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Search

January 4, 2011 by hgpu

Efficient Multiplication of Polynomials on Graphics Hardware

Pavel Emeliyanenko

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Tags: Computer science, CUDA, Linear Algebra, nVidia

January 4, 2011 by hgpu

Engineering of Computer Vision Algorithms Using Evolutionary Algorithms

Marc Ebner

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Tags: Algorithms, Computer science, Computer vision, nVidia, nVidia GeForce 9600 GT, OpenGL

January 4, 2011 by hgpu

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

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

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high performance computing on graphics processing units: hgpu.org

Data-parallel computing

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

A design case study: CPU vs. GPGPU vs. FPGA

Revisiting sorting for GPGPU stream architectures

A complete modular resultant algorithm targeted for realization on graphics hardware

Modular Resultant Algorithm for Graphics Processors

Ubiquitous Parallel Computing from Berkeley, Illinois, and Stanford

Nuclei: GPU-Accelerated Many-Core Network Coding

Practical Random Linear Network Coding on GPUs

Local Search Algorithms on Graphics Processing Units. A Case Study: The Permutation Perceptron Problem

Efficient Multiplication of Polynomials on Graphics Hardware

Engineering of Computer Vision Algorithms Using Evolutionary Algorithms

Recent source codes

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

HPX: a C++ Standard Library for Concurrency and Parallelism

TorchQC: Quantum Dynamics and Machine Learning

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

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