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OpenCL-HPX Integration

Michael Schupikov

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce RTX 3080, OpenCL, Thesis

December 26, 2021 by hgpu

Evaluation of Pseudo-Random Number Generation on GPU Cards

Tair Askar, Bekdaulet Shukirgaliyev, Martin Lukac, Ernazar Abdikamalov

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 1080 Ti, nVidia GeForce RTX 3080, nVidia GeForce RTX 3090, Pseudo-random number generators

December 19, 2021 by hgpu

A fluid simulation system based on the MPS method

André Luiz Buarque Vieira e Silva, Caio José dos Santos Brito, Francisco Paulo Magalhães Simões, Veronica Teichrieb

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Tags: cfd, CUDA, Fluid dynamics, Fluid simulation, nVidia, nVidia GeForce GTX 1080 Ti, OpenMP, Package

May 9, 2021 by hgpu

Energy-aware Task Scheduling with Deadline Constraint in DVFS-enabled Heterogeneous Clusters

Xinxin Mei, Qiang Wang, Xiaowen Chu, Hai Liu, Yiu-Wing Leung, Zongpeng Li

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Tags: Computer science, Deep learning, Energy-efficient computing, Heterogeneous systems, nVidia, nVidia GeForce GTX 1080 Ti, Package, Task scheduling

April 5, 2021 by hgpu

BASEMENT v3: a modular freeware for river process modelling over multiple computational backends

Davide Vanzo, Samuel Peter, Lukas Vonwiller, Matthias Buergler, Manuel Weberndorfer, Annunziato Siviglia, Daniel Conde, David F. Vetsch

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Tags: cfd, Computational Physics, CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 1050 Ti, nVidia GeForce GTX 1080 Ti, Package, Tesla P100

February 28, 2021 by hgpu

Text2Gestures: A Transformer-Based Network for Generating Emotive Body Gestures for Virtual Agents

Uttaran Bhattacharya, Nicholas Rewkowski, Abhishek Banerjee, Pooja Guhan, Aniket Bera, Dinesh Manocha

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Tags: Biomechanics, Computer science, Deep learning, nVidia, nVidia GeForce GTX 1080 Ti, Package, Virtual reality

January 31, 2021 by hgpu

Advances in Electron Microscopy with Deep Learning

Jeffrey M. Ede

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Tags: Deep learning, Electron microscopy, Image processing, Machine learning, Microscopy, nVidia, nVidia GeForce GTX 1080 Ti, Package, Thesis

January 10, 2021 by hgpu

I/O Lower Bounds for Auto-tuning of Convolutions in CNNs

Xiaoyang Zhang, Junmin Xiao, Guangming Tan

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Tags: Auto-Tuning, CNN, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, Tesla V100

January 3, 2021 by hgpu

Toward Accurate Platform-Aware Performance Modeling for Deep Neural Networks

Chuan-Chi Wang, Ying-Chiao Liao, Ming-Chang Kao, Wen-Yew Liang, Shih-Hao Hung

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Tags: Benchmarking, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, Performance

December 6, 2020 by hgpu

AIPerf: Automated machine learning as an AI-HPC benchmark

Zhixiang Ren, Yongheng Liu, Tianhui Shi, Lei Xie, Yue Zhou, Jidong Zhai, Youhui Zhang, Yunquan Zhang, Wenguang Chen

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Tags: Algorithms, Artificial intelligence, Benchmarking, Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 1080 Ti, Package, Tesla V100

August 23, 2020 by hgpu

UVMBench: A Comprehensive Benchmark Suite for Researching Unified Virtual Memory in GPUs

Yongbin Gu, Wenxuan Wu, Yunfan Li, Lizhong Chen

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Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 1080 Ti, Package, Performance

July 26, 2020 by hgpu

Investigating Input Representations and Representation Models of Source Code for Machine Learning

Alexander Brauckmann

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Tags: AMD Radeon HD 7970, ATI, Code generation, Computer science, LLVM, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX 970, OpenCL, Thesis

July 12, 2020 by hgpu

clRNG: an OpenCL based software library containing random number generation functions

A tool set for random number generation on GPUs in R

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

GPOEO: a micro-intrusive GPU online energy optimization framework for iterative applications

Dynamic GPU Energy Optimization for Machine Learning Training Workloads

CFU Playground: Full-Stack Open-Source Framework for Tiny Machine Learning (tinyML) Acceleration on FPGAs

From Loop Fusion to Kernel Fusion: A Domain-specific Approach to Locality Optimization

System-Level Optimization and Code Generation for Graphics Processors using a Domain-Specific Language

Faster-Mean-Shift-Euc

GPU-accelerated Faster Mean Shift with euclidean distance metrics

Turbo: A constraint solver purely on GPUs (CUDA)

A Variant of Concurrent Constraint Programming on GPU

See all packages

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high performance computing on graphics processing units: hgpu.org

OpenCL-HPX Integration

Evaluation of Pseudo-Random Number Generation on GPU Cards

A fluid simulation system based on the MPS method

Energy-aware Task Scheduling with Deadline Constraint in DVFS-enabled Heterogeneous Clusters

BASEMENT v3: a modular freeware for river process modelling over multiple computational backends

Text2Gestures: A Transformer-Based Network for Generating Emotive Body Gestures for Virtual Agents

Advances in Electron Microscopy with Deep Learning

I/O Lower Bounds for Auto-tuning of Convolutions in CNNs

Toward Accurate Platform-Aware Performance Modeling for Deep Neural Networks

AIPerf: Automated machine learning as an AI-HPC benchmark

UVMBench: A Comprehensive Benchmark Suite for Researching Unified Virtual Memory in GPUs

Investigating Input Representations and Representation Models of Source Code for Machine Learning

Recent source codes

clRNG: an OpenCL based software library containing random number generation functions

DLRM: An implementation of a deep learning recommendation model

OpenMM: A High Performance Molecular Dynamics Library

Fancier High-Performance API

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

GPOEO: a micro-intrusive GPU online energy optimization framework for iterative applications

From Loop Fusion to Kernel Fusion: A Domain-specific Approach to Locality Optimization

Faster-Mean-Shift-Euc

Turbo: A constraint solver purely on GPUs (CUDA)

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