high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

ChainerMN: Scalable Distributed Deep Learning Framework

Takuya Akiba, Keisuke Fukuda, Shuji Suzuki

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX Titan X, Package, Python

November 5, 2017 by hgpu

Deep and Shallow convections in Atmosphere Models on Intel Xeon Phi Coprocessor Systems

Srinivasan Ramesh, Sathish Vadhiyar, Ravi Nanjundiah, PN Vinayachandran

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Tags: Earth and Space Sciences, Intel Xeon Phi, OpenMP

November 5, 2017 by hgpu

Automatic Scan Parallelization in OpenMP

Maicol Zegarra, Marcio Pereira, Xavier Martorell, Guido Araujo

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Tags: Algorithms, ARM, Computer science, CUDA, nVidia, OpenCL, OpenMP, Sorting, Tesla K40

October 31, 2017 by hgpu

PCIeHLS: an OpenCL HLS framework

Malte Vesper, Dirk Koch, Khoa Pham

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Tags: Computer science, FPGA, OpenCL

October 31, 2017 by hgpu

On Pre-Trained Image Features and Synthetic Images for Deep Learning

Stefan Hinterstoisser, Vincent Lepetit, Paul Wohlhart, Kurt Konolige

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Tags: Computer science, Computer vision, Deep learning, OpenGL, Rendering

October 31, 2017 by hgpu

An efficient GPU algorithm for tetrahedron-based Brillouin-zone integration

Daniel Guterding, Harald O. Jeschke

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Tags: Algorithms, Computational Physics, CUDA, nVidia, nVidia GeForce GTX 970, Physics

October 31, 2017 by hgpu

Performance optimizations for scalable CFD applications on hybrid CPU+MIC heterogeneous computing system with millions of cores

Yong-Xian Wang, Li-Lun Zhang, Wei Liu, Xing-Hua Cheng, Yu Zhuang, Anthony T. Chronopoulos

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Tags: cfd, Computer science, CUDA, Fluid dynamics, Heterogeneous systems, MPI, nVidia, OpenMP, Performance, supercomputer, Tesla M2050, Xeon Phi

October 31, 2017 by hgpu

A Study of Time and Energy Efficient Algorithms for Parallel and Heterogeneous Computing

Jude-Thaddeus Ojiaku

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Tags: ATI, ATI Radeon HD 7750, ATI Radeon HD 7970, Bioinformatics, Computer science, Graph layout, Heterogeneous systems, nVidia, nVidia GefForce GTX 650, nVidia GefForce GTX 680, OpenCL, Thesis

October 29, 2017 by hgpu

Early Results of Deep Learning on the Stampede2 Supercomputer

Zhao Zhang, Weijia Xu, Niall Gaffney, Daniel Stanzione

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Tags: Caffe, Computer science, Deep learning, Intel Xeon Phi, TensorFlow

October 29, 2017 by hgpu

GooFit 2.0

Henry Schreiner, Christoph Hasse, Bradley Hittle, Himadri Pandey, Michael Sokoloff, Karen Tomko

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Tags: Computer science, CUDA, Mathematical Software, MPI, nVidia, nVidia GeForce GTX 1050 Ti, nVidia GeForce GTX 1080 Ti, Package, Probability, Tesla K40, Tesla P100

October 29, 2017 by hgpu

Strategy Preserving Compilation for Parallel Functional Code

Robert Atkey, Michel Steuwer, Sam Lindley, Christophe Dubach

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Tags: ATI, ATI Radeon 7970, Code generation, Computer science, nVidia, nVidia GeForce GTX Titan X, OpenCL, performance portability

October 29, 2017 by hgpu

Hybrid Fortran: High Productivity GPU Porting Framework Applied to Japanese Weather Prediction Model

Michel Muller, Takayuki Aoki

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Tags: Earth and Space Sciences, Fortran, nVidia, OpenACC, OpenMP, Package, Tesla K20, Tesla P100, Weather prediction, Weather Prediction Model

October 29, 2017 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

Applications

ChainerMN: Scalable Distributed Deep Learning Framework

Deep and Shallow convections in Atmosphere Models on Intel Xeon Phi Coprocessor Systems

Automatic Scan Parallelization in OpenMP

PCIeHLS: an OpenCL HLS framework

On Pre-Trained Image Features and Synthetic Images for Deep Learning

An efficient GPU algorithm for tetrahedron-based Brillouin-zone integration

Performance optimizations for scalable CFD applications on hybrid CPU+MIC heterogeneous computing system with millions of cores

A Study of Time and Energy Efficient Algorithms for Parallel and Heterogeneous Computing

Early Results of Deep Learning on the Stampede2 Supercomputer

GooFit 2.0

Strategy Preserving Compilation for Parallel Functional Code

Hybrid Fortran: High Productivity GPU Porting Framework Applied to Japanese Weather Prediction Model

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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