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DeepFont: Identify Your Font from An Image

Zhangyang Wang, Jianchao Yang, Hailin Jin, Eli Shechtman, Aseem Agarwala, Jonathan Brandt, Thomas S. Huang

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Tags: CNN, Computer science, CUDA, Deep learning, Neural networks, nVidia

July 17, 2015 by hgpu

Towards Good Practices for Very Deep Two-Stream ConvNets

Limin Wang, Yuanjun Xiong, Zhe Wang, Yu Qiao

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Tags: Computer science, Computer vision, CUDA, Deep learning, Machine learning, MPI, nVidia, OpenMPI, Package

July 10, 2015 by hgpu

Experiments on Parallel Training of Deep Neural Network using Model Averaging

Hang Su, Haoyu Chen

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Tags: Computer science, CUDA, Deep learning, MPI, Neural networks, nVidia, Tesla K20

July 8, 2015 by hgpu

Heterogeneous Network Embedding via Deep Architectures

Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang

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Tags: Computer science, CUDA, Data mining, Deep learning, Machine learning, nVidia, Tesla K40

July 1, 2015 by hgpu

The Potential of the Intel Xeon Phi for Supervised Deep Learning

Andre Viebke, Sabri Pllana

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Tags: CNN, Computer science, Deep learning, Intel Xeon Phi, Neural networks, OpenMP, Performance

July 1, 2015 by hgpu

Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation

Marijn F. Stollenga, Wonmin Byeon, Marcus Liwicki, Juergen Schmidhuber

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Tags: Computer science, CUDA, Deep learning, Image processing, Medicine, Neural networks, nVidia, nVidia GeForce GTX Titan X

June 26, 2015 by hgpu

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun

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Tags: CNN, Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, Package, Tesla K40

June 7, 2015 by hgpu

Machine Learning Based Auto-tuning for Enhanced OpenCL Performance Portability

Thomas L. Falch, Anne C. Elster

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Tags: ATI, ATI Radeon HD 7970, Benchmarking, Computer science, Deep learning, Heterogeneous systems, Machine learning, Neural networks, nVidia, OpenCL, Tesla K40

June 5, 2015 by hgpu

Blocks and Fuel: Frameworks for deep learning

Bart van Merrienboer, Dzmitry Bahdanau, Vincent Dumoulin, Dmitriy Serdyuk, David Warde-Farley, Jan Chorowski, Yoshua Bengio

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Tags: Computer science, CUDA, Deep learning, Linear Algebra, Machine learning, MPI, Neural networks, nVidia, Package, Python, Symbolic Computation, Visualization

June 5, 2015 by hgpu

DjiNN and Tonic: DNN as a Service and Its Implications for Future Warehouse Scale Computers

Johann Hauswald, Yiping Kang, Michael A. Laurenzano, Quan Chen, Cheng Li, Trevor Mudge, Ronald G. Dreslinski, Jason Mars, Lingjia Tang

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Tags: CUDA, Deep learning, Image processing, Machine learning, Neural networks, nVidia, Speech recognition, Tesla K40

May 25, 2015 by hgpu

U-Net: Convolutional Networks for Biomedical Image Segmentation

Olaf Ronneberger, Philipp Fischer, Thomas Brox

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Tags: CNN, Computer science, CUDA, Deep learning, Image processing, Medicine, Microscopy, Neural networks, nVidia, nVidia GeForce GTX Titan, Package

May 20, 2015 by hgpu

Speeding up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves

Tobias Domhan, Jost Tobias Springenberg, Frank Hutter

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Tags: Benchmarking, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan

May 15, 2015 by hgpu

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

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high performance computing on graphics processing units: hgpu.org

DeepFont: Identify Your Font from An Image

Towards Good Practices for Very Deep Two-Stream ConvNets

Experiments on Parallel Training of Deep Neural Network using Model Averaging

Heterogeneous Network Embedding via Deep Architectures

The Potential of the Intel Xeon Phi for Supervised Deep Learning

Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Machine Learning Based Auto-tuning for Enhanced OpenCL Performance Portability

Blocks and Fuel: Frameworks for deep learning

DjiNN and Tonic: DNN as a Service and Its Implications for Future Warehouse Scale Computers

U-Net: Convolutional Networks for Biomedical Image Segmentation

Speeding up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves

Recent source codes

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

SUperman: Highly Efficient Permanent Computation Library

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

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