high performance computing on graphics processing units: hgpu.org

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A GPU-based Framework for Real-time Free Viewpoint Television

Kyrylo Shegeda

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Tags: Computer science, CUDA, GLSL, nVidia, nVidia Quadro FX 1700, nVidia Quadro FX 5800, Rendering, Thesis

November 3, 2014 by hgpu

GPU/CPU Parallel Computation of Material Damage

Jie Shen, Diego Vela, Ankita Singh, Kexing Song, Guoshang Zhang, Bradon LaFreniere, Hao Chen

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Tags: CAD, Computed tomography, CT, CUDA, Materials Science, nVidia, nVidia Quadro FX 1700, Tesla C1060, Tomography

June 19, 2014 by hgpu

Parallel Firewalls on General-Purpose Graphics Processing Units

Kamal Chandra Reddy, Ankit Tharwani, Ch.Vamshi Krishna, Lakshminarayanan.V

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Tags: Computer science, CUDA, Databases, Network communications, nVidia, nVidia Quadro FX 1700, Security

December 17, 2013 by hgpu

Acceleration of Functional Validation Using GPGPU

Lalith Suresh, Navaneeth Rameshan, M. S. Gaur, Mark Zwolinski, Vijay Laxmi

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Tags: Algorithms, Benchmarking, Computer science, Electronic design automation, nVidia, nVidia Quadro FX 1700, Tesla C870

September 23, 2011 by hgpu

A GPU implementation for two MIMO-OFDM detectors

Teemu Nylanden, Janne Janhunen, Olli Silven, Markku J. Juntti

Tags: Algorithms, nVidia, nVidia Quadro FX 1700, Signal processing

April 25, 2011 by hgpu

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice

HeterPS: Distributed Deep Learning With Reinforcement Learning Based Scheduling in Heterogeneous Environments

BAT: A standardized benchmark suite for auto-tuners

BAT: A Benchmark suite for AutoTuners

The Darmstadt Automotive Parallel HeterogeNEous (DAPHNE) Benchmark-Suite

Programming Heterogeneous Systems with General and Domain-Specific Frameworks

General purpose lattice QCD code set Bridge++ 2.0 for high performance computing

MQBench: Towards Reproducible and Deployable Model Quantization Benchmark

Performance Evaluation of Python ParallelProgramming Models: Charm4Py and mpi4py

iGUARD: In-GPU Advanced Race Detection

TaPaSCo: The Task Parallel System Composer

Optimizing a Hardware Network Stack to Realize an In-Network ML Inference Application

Tapenade Automatic Differentiation Engine

Source-to-Source Automatic Differentiation of OpenMP Parallel Loops

Colossal-AI: an integrated large-scale model training system with efficient parallelization techniques

Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training

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high performance computing on graphics processing units: hgpu.org

A GPU-based Framework for Real-time Free Viewpoint Television

GPU/CPU Parallel Computation of Material Damage

Parallel Firewalls on General-Purpose Graphics Processing Units

Acceleration of Functional Validation Using GPGPU

A GPU implementation for two MIMO-OFDM detectors

Recent source codes

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice

BAT: A standardized benchmark suite for auto-tuners

The Darmstadt Automotive Parallel HeterogeNEous (DAPHNE) Benchmark-Suite

General purpose lattice QCD code set Bridge++ 2.0 for high performance computing

MQBench: Towards Reproducible and Deployable Model Quantization Benchmark

Performance Evaluation of Python ParallelProgramming Models: Charm4Py and mpi4py

iGUARD: In-GPU Advanced Race Detection

TaPaSCo: The Task Parallel System Composer

Tapenade Automatic Differentiation Engine

Colossal-AI: an integrated large-scale model training system with efficient parallelization techniques

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