high performance computing on graphics processing units: hgpu.org

Andrey Ignatov, Kim Byeoung-su, Radu Timofte, Angeline Pouget, Fenglong Song, Cheng Li, Shuai Xiao, Zhongqian Fu, Matteo Maggioni, Yibin Huang, Shen Cheng, Xin Lu, Yifeng Zhou, Liangyu Chen, Donghao Liu, Xiangyu Zhang, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Minsu Kwon, Myungje Lee, Jaeyoon Yoo, Changbeom Kang, Shinjo Wang, Bin Huang, Tianbao Zhou, Shuai Liu, Lei Lei, Chaoyu Feng, Liguang Huang, Zhikun Lei, Feifei Chen

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Tags: AI, Deep learning, Image processing, Machine learning, Neural networks

May 23, 2021 by hgpu

Performance and Power Evaluation of AI Accelerators for Training Deep Learning Models

Yuxin Wang, Qiang Wang, Shaohuai Shi, Xin He, Zhenheng Tang, Kaiyong Zhao, Xiaowen Chu

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Tags: AI, AMD Radeon R7, ATI, Computer science, Deep learning, Neural networks, nVidia, PyTorch, TensorFlow, Tesla P100, Tesla V100, TPU

September 22, 2019 by hgpu

Block based Singular Value Decomposition approach to matrix factorization for recommender systems

Prasad Bhavana, Vikas Kumar, Vineet Padmanabhan

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Tags: AI, Algorithms, Computer science, CUDA, Factorization, Machine learning, nVidia, Package, Tesla M40

July 21, 2019 by hgpu

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high performance computing on graphics processing units: hgpu.org

APACE: AlphaFold2 and advanced computing as a service for accelerated discovery in biophysics

Fast Knowledge Graph Completion using Graphics Processing Units

Mystique: Enabling Accurate and Scalable Generation of Production AI Benchmarks

Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation

SOL: Reducing the Maintenance Overhead for Integrating Hardware Support into AI Frameworks

perf4sight: A toolflow to model CNN training performance on Edge GPUs

Face.evoLVe: A High-Performance Face Recognition Library

Fast Camera Image Denoising on Mobile GPUs with Deep Learning, Mobile AI 2021 Challenge: Report

Performance and Power Evaluation of AI Accelerators for Training Deep Learning Models

Block based Singular Value Decomposition approach to matrix factorization for recommender systems

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