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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

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

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

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

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

Deep Voice 3: 2000-Speaker Neural Text-to-Speech

Wei Ping, Kainan Peng, Andrew Gibiansky, Sercan O. Arik, Ajay Kannan, Sharan Narang, Jonathan Raiman, John Miller

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Tags: Computer science, CUDA, Deep learning, nVidia, Speech recognition, Tesla P100

October 24, 2017 by hgpu

A Fast and Generic GPU-Based Parallel Reduction Implementation

Walid Jradi, Hugo do Nascimento, Wellington Martins

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Tags: Computer science, CUDA, nVidia, OpenCL, Performance, Tesla C2075

October 24, 2017 by hgpu

GPU acceleration and performance of the particle-beam-dynamics code Elegant

J.R. King, I.V. Pogorelov, K.M. Amyx, M. Borland, R. Soliday

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Tags: Computational Physics, CUDA, MPI, nVidia, Physics, Tesla K20

October 24, 2017 by hgpu

Revisiting the Case of ARM SoCs in High-Performance Computing Clusters

Tyler Fox

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Tags: Benchmarking, Computer science, CUDA, Deep learning, Heterogeneous systems, nVidia, nVidia GeForce GTX 960, nVidia Tegra TX1, SoC, Thesis

October 21, 2017 by hgpu

Parallel Matching and Clustering Algorithms on GPUs

Md. Naim

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, Tesla K40, Thesis

October 21, 2017 by hgpu

Computation of gray-level co-occurrence matrix based on CUDA and its optimization

Huichao Hong, Lixin Zheng, Shuwan Pan

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 1050 Ti, Performance

October 21, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Dynamic Load Balancing Strategies for Graph Applications on GPUs

ChainerMN: Scalable Distributed Deep Learning Framework

Automatic Scan Parallelization in OpenMP

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

GooFit 2.0

Deep Voice 3: 2000-Speaker Neural Text-to-Speech

A Fast and Generic GPU-Based Parallel Reduction Implementation

GPU acceleration and performance of the particle-beam-dynamics code Elegant

Revisiting the Case of ARM SoCs in High-Performance Computing Clusters

Parallel Matching and Clustering Algorithms on GPUs

Computation of gray-level co-occurrence matrix based on CUDA and its optimization

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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