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AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles

Charles Weill, Javier Gonzalvo, Vitaly Kuznetsov, Scott Yang, Scott Yak, Hanna Mazzawi, Eugen Hotaj, Ghassen Jerfel, Vladimir Macko, Ben Adlam, Mehryar Mohri, Corinna Cortes

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Tags: Algorithms, Computer science, Machine learning, Neural networks, nVidia, Package, TensorFlow, Tesla V100

May 5, 2019 by hgpu

Chunkflow: Distributed Hybrid Cloud Processing of Large 3D Images by Convolutional Nets

Jingpeng Wu, William M. Silversmith, H. Sebastian Seung

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Tags: Cloud, CNN, Computer science, CUDA, Deep learning, Electron microscopy, Image processing, Microscopy, nVidia, nVidia GeForce GTX 970, Package, Tesla K80

April 28, 2019 by hgpu

Loop Perforation in OpenACC

Ahmad Lashgar, Ehsan Atoofian, Amirali Baniasadi

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Tags: Computer science, CUDA, OpenACC, OpenCL, Package, Performance

April 20, 2019 by hgpu

Concurrent query processing in a GPU-based database system

Hao Li, Yi-Cheng Tu, Bo Zeng

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX Titan X, Package

April 20, 2019 by hgpu

Accelerated Neural Networks on OpenCL Devices Using SYCL-DNN

Rod Burns, John Lawson, Duncan McBain, Daniel Soutar

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Tags: Computer science, Computer vision, Deep learning, Machine learning, Neural networks, nVidia, OpenCL, Package, SYCL

April 14, 2019 by hgpu

Cross-Platform Performance Portability Using Highly Parametrized SYCL Kernels

John Lawson, Mehdi Goli, Duncan McBain, Daniel Soutar, Louis Sugy

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Tags: AMD R9 Nano, ATI, BLAS, Computer science, Deep learning, Linear Algebra, Machine learning, Mathematical Software, OpenCL, Package, Performance, performance portability, SYCL

April 14, 2019 by hgpu

The Study of the OpenCL Processing Models for the FPGA Devices

Piotr Szkotak, Pawel Russek, Kazimierz Wiatr

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Tags: AMD Radeon R9 290, ATI, Computer science, FPGA, HLS, nVidia, nVidia GeForce GTX 1080, OpenCL, Package

April 7, 2019 by hgpu

TonY: An Orchestrator for Distributed Machine Learning Jobs

Anthony Hsu, Keqiu Hu, Jonathan Hung, Arun Suresh, Zhe Zhang

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Tags: Computer science, Deep learning, Hadoop, Machine learning, Package, PyTorch, TensorFlow, TPU

April 7, 2019 by hgpu

fairseq: A Fast, Extensible Toolkit for Sequence Modeling

Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, Michael Auli

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Tags: Computer science, CUDA, NLP, nVidia, Package, PyTorch, Video

April 7, 2019 by hgpu

Dynamic Application Autotuning for Self-Aware Approximate Computing

Davide Gadioli

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Tags: Auto-Tuning, Computer science, OpenCL, Package, Thesis

March 31, 2019 by hgpu

Hybrid CPU-GPU execution support in the skeleton programming framework SkePU

Tomas Oehberg, August Ernstsson, Christoph Kessler

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Tags: Computer science, CUDA, Heterogeneous systems, Hybrid computing, MapReduce, nVidia, OpenCL, Package, Tesla K20

March 31, 2019 by hgpu

HeteroMap: A Runtime Performance Predictor for Efficient Processing of Graph Analytics on Heterogeneous Multi-Accelerators

Masab Ahmad, Halit Dogan, Christopher J. Michael, Omer Khan

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Tags: Algorithms, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX 970, OpenCL, Package, Performance

March 31, 2019 by hgpu

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Efficient deep learning inference on end devices

Ouroboros: Virtualized Queues for dynamic memory management

Dynamic Memory Management on GPUs with SYCL

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high performance computing on graphics processing units: hgpu.org

Packages

AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles

Loop Perforation in OpenACC

Concurrent query processing in a GPU-based database system

Accelerated Neural Networks on OpenCL Devices Using SYCL-DNN

Cross-Platform Performance Portability Using Highly Parametrized SYCL Kernels

The Study of the OpenCL Processing Models for the FPGA Devices

TonY: An Orchestrator for Distributed Machine Learning Jobs

fairseq: A Fast, Extensible Toolkit for Sequence Modeling

Dynamic Application Autotuning for Self-Aware Approximate Computing

Hybrid CPU-GPU execution support in the skeleton programming framework SkePU

HeteroMap: A Runtime Performance Predictor for Efficient Processing of Graph Analytics on Heterogeneous Multi-Accelerators

Recent source codes

XaaS containers

microSYCL: SYCL micro-benchmarks repository

SYCL Container

CASS: Cuda-Amd aSSembly

Cluser of smartphones for edge computing application using TensorFlow

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

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