high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

Francisco Javier Ordonez, Daniel Roggen

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Tags: Computer science, Deep learning, LSTM, Machine learning, Neural networks, Package, Python, RNN, Theano

January 26, 2016 by hgpu

Task Parallel Incomplete Cholesky Factorization using 2D Partitioned-Block Layout

Kyungjoo Kim, Sivasankaran Rajamanickam, George Stelle, H. Carter Edwards, Stephen L. Olivier

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Tags: Algorithms, Computer science, Factorization, Intel Xeon Phi, Mathematical Software, Package, Sparse matrix

January 26, 2016 by hgpu

Power Consumption Modeling and Prediction in a Hybrid CPU-GPU-MIC Supercomputer

Alina Sirbu, Ozalp Babaoglu

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Tags: Computer science, Energy-efficient computing, Intel Xeon Phi, Package, Python, Task scheduling

January 26, 2016 by hgpu

Odyssey: A Public GPU-Based Code for General-Relativistic Radiative Transfer in Kerr Spacetime

Hung-Yi Pu, Kiyun Yun, Ziri Younsi, Suk-Jin Yoon

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Tags: Astrophysics, CUDA, High Energy Astrophysical Phenomena, MPI, nVidia, nVidia GeForce GTX 780 Ti, Package, Raytracing

January 14, 2016 by hgpu

Real-Time Dedispersion for Fast Radio Transient Surveys, using Auto Tuning on Many-Core Accelerators

Alessio Sclocco, Joeri van Leeuwen, Henri E. Bal, Rob V. van Nieuwpoort

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Tags: Astrophysics, ATI, ATI Radeon HD 7970, Instrumentation and Methods for Astrophysics, Intel Xeon Phi, nVidia, nVidia GeForce GTX 680, nVidia GeForce Titan, OpenCL, OpenMP, Package, Tesla K20

January 12, 2016 by hgpu

Verifying CUDA Programs using SMT-Based Context-Bounded Model Checking

Phillipe A. Pereira, Higo F. Albuquerque, Hendrio M. Marques, Isabela S. Silva, Celso B. Carvalho, Lucas C. Cordeiro

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Tags: Computer science, CUDA, nVidia, Package

January 7, 2016 by hgpu

DeepLearningKit – an Open Source Deep Learning Framework for Apple’s iOS, OS X and tvOS developed in Metal and Swift

Amund Tvei, Torbjorn Morland, Thomas Brox Rost

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Tags: Computer science, Deep learning, Machine learning, Neural networks, OpenCL, Package, Vulkan

January 7, 2016 by hgpu

On the Development and Implementation of High-Order Flux Reconstruction Schemes for Computational Fluid Dynamics

Freddie David Witherden

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Tags: AMD FirePro W9100, ATI, CUDA, Finite difference, Fluid dynamics, Heterogeneous systems, MPI, nVidia, OpenCL, Package, Python, Tesla K40, Thesis

December 23, 2015 by hgpu

Poseidon: A System Architecture for Efficient GPU-based Deep Learning on Multiple Machines

Hao Zhang, Zhiting Hu, Jinliang Wei, Pengtao Xie, Gunhee Kim, Qirong Ho, Eric Xing

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Tags: Caffe, Computer science, Computer vision, Deep learning, GPU cluster, Machine learning, Neural networks, nVidia, Package, Tesla K20

December 23, 2015 by hgpu

OpenDwarfs: Characterization of Dwarf-Based Benchmarks on Fixed and Reconfigurable Architectures

Konstantinos Krommydas, Wu-chun Feng, Christos D. Antonopoulos, Nikolaos Bellas

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Tags: ATI, ATI Radeon HD 6550, ATI Radeon HD 7660, ATI Radeon HD 7970, Computer science, FPGA, Heterogeneous systems, Intel Xeon Phi, OpenCL, Package

December 22, 2015 by hgpu

Autotuning Stencils Codes with Algorithmic Skeletons

Chris Cummins

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 590, nVidia GeForce GTX 690, nVidia GeForce GTX Titan, OpenCL, Package

December 19, 2015 by hgpu

Efficient Query Processing in Co-Processor-accelerated Databases

Sebastian Bress

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Tags: Computer science, CUDA, Databases, Heterogeneous systems, nVidia, nVidia GeForce GT 640, Package, Tesla C1060, Tesla C2050, Thesis

December 19, 2015 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Packages

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

Task Parallel Incomplete Cholesky Factorization using 2D Partitioned-Block Layout

Power Consumption Modeling and Prediction in a Hybrid CPU-GPU-MIC Supercomputer

Odyssey: A Public GPU-Based Code for General-Relativistic Radiative Transfer in Kerr Spacetime

Real-Time Dedispersion for Fast Radio Transient Surveys, using Auto Tuning on Many-Core Accelerators

Verifying CUDA Programs using SMT-Based Context-Bounded Model Checking

DeepLearningKit – an Open Source Deep Learning Framework for Apple’s iOS, OS X and tvOS developed in Metal and Swift

On the Development and Implementation of High-Order Flux Reconstruction Schemes for Computational Fluid Dynamics

Poseidon: A System Architecture for Efficient GPU-based Deep Learning on Multiple Machines

OpenDwarfs: Characterization of Dwarf-Based Benchmarks on Fixed and Reconfigurable Architectures

Autotuning Stencils Codes with Algorithmic Skeletons

Efficient Query Processing in Co-Processor-accelerated Databases

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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