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MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU

Qingqing Cao, Niranjan Balasubramanian, Aruna Balasubramanian

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Tags: Computer science, CUDA, Deep learning, Java, Neural networks, nVidia, Package, RNN, TensorFlow

June 10, 2017 by hgpu

SparkJNI: A Reference Design for a Heterogeneous Apache Spark Framework

Tudor Alexandru Voicu

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Tags: big data, Computer science, FPGA, Heterogeneous systems, Hybrid computing, Java, OpenCL, Spark, Thesis

June 1, 2017 by hgpu

GPUMap: A Transparently GPU-Accelerated Map Function

Ivan Pachev

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Tags: Computer science, CUDA, Distributed computing, Java, MapReduce, nVidia, nVidia GeForce GTX 980, Python, Thesis

May 22, 2017 by hgpu

liquidSVM: A Fast and Versatile SVM package

Ingo Steinwart, Philipp Thomann

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Tags: Computer science, CUDA, Java, nVidia, Package, Python, Spark

February 26, 2017 by hgpu

Development of JavaScript-based deep learning platform and application to distributed training

Masatoshi Hidaka, Ken Miura, Tatsuya Harada

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Tags: Computer science, Deep learning, Java, Neural networks, nVidia, OpenCL, Package, Tesla K80, WebCL

February 10, 2017 by hgpu

DeepDSL: A Compilation-based Domain-Specific Language for Deep Learning

Tian Zhao, Xiaobing Huang, Yu Cao

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Tags: Computer science, CUDA, Deep learning, DSL, Java, Machine learning, nVidia, Package, Programming Languages, Scala, Tesla K40

January 10, 2017 by hgpu

Fast and Energy-Efficient CNN Inference on IoT Devices

Mohammad Motamedi, Daniel Fong, Soheil Ghiasi

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Tags: CNN, Computer science, Deep learning, Java, Machine learning, Neural networks, Package, RenderScript, SoC

November 25, 2016 by hgpu

FastCollect: Offloading Generational Garbage Collection to Integrated GPUs

Abhinav, Rupesh Nasre

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Tags: Algorithms, Benchmarking, Computer science, Intel HD Graphics 4000, Java, OpenCL, Performance

September 27, 2016 by hgpu

Agent-Based Modeling on High Performance Computing Architectures

Nuno Fachada

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Tags: cpu, GPGPU, HPC, Java, OpenCL, Thesis

September 16, 2016 by fakenmc

Processing Big Data in Main Memory and on GPU

Meisam Fathi Salmi

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Tags: big data, Computer science, CUDA, Hadoop, Java, OpenCL, Scala, Spark, Thesis

June 14, 2016 by hgpu

Microbenchmarks for GPU characteristics: the occupancy roofline and the pipeline model

Jan Lemeire, Jan G. Cornelis, Laurent Segers

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Tags: Benchmarking, Computer science, Java, nVidia, nVidia GeForce GT 640, nVidia Quadro K620, OpenCL, Package

May 9, 2016 by hgpu

Automatic Parallelization: Executing Sequential Programs on a Task-Based Parallel Runtime

Alcides Fonseca, Bruno Cabral, Joao Rafael, Ivo Correia

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Tags: Computer science, Java, OpenCL, Package, Programming Languages

April 29, 2016 by hgpu

Page 1 of 812 3 4 5...»Last »

Rgtsvm: Support Vector Machines on a GPU in R

Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras

gloo: Collective communications library with various primitives for multi-machine training

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU

CELES: CUDA-accelerated electromagnetic scattering by large ensembles of spheres

CELES: CUDA-accelerated simulation of electromagnetic scattering by large ensembles of spheres

Boda: A C++ Framework for Efficient Experiments in Computer Vision [WIP]

Implementing Efficient, Portable Computations for Machine Learning

ESPRESO: Highly Parallel Solvers for Engineering Applications

Intel Xeon Phi acceleration of Hybrid Total FETI solver

Parallel and in-process compilation of individuals for genetic programming on GPU

MECCA development in accelerators - KPP Fortran to CUDA source-to-source pre-processor

MEDINA: MECCA Development in Accelerators – KPP Fortran to CUDA source-to-source Preprocessor

Internally-maintained tool for examining GPU scheduling behavior

Inferring the Scheduling Policies of an Embedded CUDA GPU

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2nd International Conference on Communication and Information Systems (ICCIS), 2017

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high performance computing on graphics processing units: hgpu.org

MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU

SparkJNI: A Reference Design for a Heterogeneous Apache Spark Framework

GPUMap: A Transparently GPU-Accelerated Map Function

liquidSVM: A Fast and Versatile SVM package

Development of JavaScript-based deep learning platform and application to distributed training

DeepDSL: A Compilation-based Domain-Specific Language for Deep Learning

Fast and Energy-Efficient CNN Inference on IoT Devices

FastCollect: Offloading Generational Garbage Collection to Integrated GPUs

Agent-Based Modeling on High Performance Computing Architectures

Processing Big Data in Main Memory and on GPU

Microbenchmarks for GPU characteristics: the occupancy roofline and the pipeline model

Automatic Parallelization: Executing Sequential Programs on a Task-Based Parallel Runtime

Recent source codes

Rgtsvm: Support Vector Machines on a GPU in R

Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras

gloo: Collective communications library with various primitives for multi-machine training

MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU

CELES: CUDA-accelerated electromagnetic scattering by large ensembles of spheres

Boda: A C++ Framework for Efficient Experiments in Computer Vision [WIP]

ESPRESO: Highly Parallel Solvers for Engineering Applications

Parallel and in-process compilation of individuals for genetic programming on GPU

MECCA development in accelerators - KPP Fortran to CUDA source-to-source pre-processor

Internally-maintained tool for examining GPU scheduling behavior

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Featured events

4th International Conference on Biomedical and Bioinformatics Engineering (ICBBE), 2017

9th International Conference on Signal Processing Systems (ICSPS), 2017

The 5th International conference on Control, Mechatronics and Automation (ICCMA), 2017

8th International Conference on Biology, Environment and Chemistry (ICBEC), 2017

2nd International Conference on Communication and Information Systems (ICCIS), 2017