high performance computing on graphics processing units: hgpu.org

Applications

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Best Practice Guide – GPGPU

Momme Allalen, Vali Codreanu, Nevena Ilieva-Litova, Alan Gray, Anders Sjostrom, Volker Weinberg

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Tags: Computer science, CUDA, OpenACC, OpenCL, OpenMP, Review

November 12, 2017 by hgpu

Low-power System-on-Chip Processors for Energy Efficient High Performance Computing: The Texas Instruments Keystone II

Gaurav Mitra

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Tags: ARM, Benchmarking, Computer science, DSP, Heterogeneous systems, Matrix multiplication, nVidia, nVidia Jetson TK1, nVidia Tegra TX1, OpenCL, SoC, Thesis

November 12, 2017 by hgpu

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

Leiming Yu, Fanny Nina-Paravecino, David Kaeli, Qianqian Fang

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Tags: Algorithms, AMD R9 Nano, AMD Radeon RX 480, ATI, Computational Physics, Heterogeneous systems, nVidia, nVidia GeForce GTX 1050 Ti, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX 590, nVidia GeForce GTX 980 Ti, nVidia GeForce GTX Titan X, OpenCL, Package, Physics

November 12, 2017 by hgpu

Performance Evaluation of Deep Learning Tools in Docker Containers

Pengfei Xu, Shaohuai Shi, Xiaowen Chu

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Tags: Benchmarking, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 980, nVidia GeForce GTX Titan X, Package, Performance

November 12, 2017 by hgpu

Comparison of Parallelisation Approaches, Languages, and Compilers for Unstructured Mesh Algorithms on GPUs

G. D. Balogh, I. Z. Reguly, G. R. Mudalige

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Tags: Benchmarking, Computer science, CUDA, MPI, nVidia, OpenACC, OpenMP, Performance, Tesla K40, Tesla P100

November 7, 2017 by hgpu

Radeon PRO Solid State Graphics (SSG) API User Manual

AMD

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Tags: AMD Radeon Pro SSG, ATI, Computer science, DirectX, OpenCL, OpenGL

November 7, 2017 by hgpu

Scalable Streaming Tools for Analyzing N-body Simulations: Finding Halos and Investigating Excursion Sets in One Pass

Nikita Ivkin, Zaoxing Liu, Lin F. Yang, Srinivas Suresh Kumar, Gerard Lemson, Mark Neyrinck, Alexander S. Szalay, Vladimir Braverman, Tamas Budavari

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Tags: Algorithms, Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce GTX 1080, Tesla C2050, Tesla C2070

November 7, 2017 by hgpu

Lattice QCD on new chips: a community summary

Antonio Rago

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Tags: CUDA, HEP, High Energy Physics - Lattice, Intel Xeon Phi, MPI, nVidia, OpenMP, Physics, QCD, Review, Tesla V100

November 7, 2017 by hgpu

Acceleration of tensor-product operations for high-order finite element methods

Kasia Swirydowicz, Noel Chalmers, Ali Karakus, Timothy Warburton

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Tags: Computer science, CUDA, FEM, Finite element method, Mathematical Software, Numerical Analysis, nVidia, Overview, Performance, Tesla P100

November 7, 2017 by hgpu

Dynamic Load Balancing Strategies for Graph Applications on GPUs

Ananya Raval, Rupesh Nasre, Vivek Kumar, Vasudevan R, Sathish Vadhiyar, Keshav Pingali

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Tags: Computer science, CUDA, load balancing, nVidia, Tesla K20

November 5, 2017 by hgpu

A Dynamic Hash Table for the GPU

Saman Ashkiani, Martin Farach-Colton, John D. Owens

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Tags: Computer science, CUDA, Graph theory, Hashing, nVidia, Tesla K40

November 5, 2017 by hgpu

Data Coherence Analysis and Optimization for Heterogeneous Computing

Rafael Sousa, Marcio Pereira, Fernando Magno Quintao Pereira, Guido Araujo

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Tags: ARM, Compilers, Computer science, Heterogeneous systems, OpenCL

November 5, 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

Best Practice Guide – GPGPU

Low-power System-on-Chip Processors for Energy Efficient High Performance Computing: The Texas Instruments Keystone II

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

Performance Evaluation of Deep Learning Tools in Docker Containers

Comparison of Parallelisation Approaches, Languages, and Compilers for Unstructured Mesh Algorithms on GPUs

Radeon PRO Solid State Graphics (SSG) API User Manual

Scalable Streaming Tools for Analyzing N-body Simulations: Finding Halos and Investigating Excursion Sets in One Pass

Lattice QCD on new chips: a community summary

Acceleration of tensor-product operations for high-order finite element methods

Dynamic Load Balancing Strategies for Graph Applications on GPUs

A Dynamic Hash Table for the GPU

Data Coherence Analysis and Optimization for Heterogeneous Computing

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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