high performance computing on graphics processing units: hgpu.org

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Improving Communication Performance in GPU-Accelerated HPC Clusters

Iman Faraji

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Tags: Computer science, CUDA, GPU cluster, MPI, nVidia, Package, Performance, Thesis

January 28, 2018 by hgpu

Scheduling Parallel Tasks under Multiple Resources: List Scheduling vs. Pack Scheduling

Hongyang Sun, Redouane Elghazi, Ana Gainaru, Guillaume Aupy, Padma Raghavan

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Tags: Computer science, Intel Xeon Phi, Performance, Task scheduling

January 20, 2018 by hgpu

Comprehensive Optimization of Parametric Kernels for Graphics Processing Units

Xiaohui Chen, Marc Moreno-Maza, Jeeva Paudel, Ning Xie

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Tags: Code generation, Computer science, CUDA, LLVM, nVidia, Package, Performance, PTX, Symbolic Computation, Tesla M2050

January 20, 2018 by hgpu

Evaluation of Machine Learning Fameworks on Finis Terrae II

Andres Gomez Tato

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Deep learning, Machine learning, nVidia, Performance, Tesla K80

January 20, 2018 by hgpu

Analysing the Performance of GPU Hash Tables for State Space Exploration

Nathan Cassee, Anton Wijs

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Tags: Computer science, CUDA, Design space exploration, Hashing, nVidia, nVidia GeForce GT 750 M, Performance

January 6, 2018 by hgpu

Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer

Amrita Mathuriya, Thorsten Kurth, Vivek Rane, Mustafa Mustafa, Lei Shao, Debbie Bard, Prabhat, Victor W Lee

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Tags: Benchmarking, Computer science, Deep learning, Intel Xeon Phi, Neural networks, Performance, TensorFlow

January 6, 2018 by hgpu

Protecting Real-Time GPU Applications on Integrated CPU-GPU SoC Platforms

Waqar Ali, Heechul Yun

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Tags: Computer science, CUDA, nVidia, nVidia Jetson TK1, Operating systems, Performance, Security, SoC

December 28, 2017 by hgpu

MILC Code Performance on High End CPU and GPU Supercomputer Clusters

Ruizi Li, Carleton DeTar, Steven Gottlieb, Doug Toussaint

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Tags: Computational Physics, CUDA, High Energy Physics - Lattice, Intel Xeon Phi, nVidia, Performance, Physics, QCD, Tesla K20, Tesla P100

December 7, 2017 by hgpu

Study of Bandwidth Partitioning for Co-executing GPU Kernels

Erik Melander

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Tags: Computer science, CUDA, nVidia, Performance, Tesla K20, Thesis

December 7, 2017 by hgpu

Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs

Shaohuai Shi, Xiaowen Chu

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Tags: Algorithms, Benchmarking, Caffe, Computer science, CUDA, Deep learning, MPI, Neural networks, nVidia, Package, Performance, TensorFlow, Tesla P40, Torch

November 26, 2017 by hgpu

Launch-time Optimization of OpenCL Kernels

Andrew Siu Doug Lee

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Tags: Computer science, LLVM, nVidia, nVidia GeForce GTX 780, OpenCL, Performance, Thesis

November 16, 2017 by hgpu

Accelerating HPC codes on Intel(R) Omni-Path Architecture networks: From particle physics to Machine Learning

Peter Boyle, Michael Chuvelev, Guido Cossu, Christopher Kelly, Christoph Lehner, Lawrence Meadows

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Tags: Benchmarking, Computer science, Intel Xeon Phi, Machine learning, MPI, OpenMP, Package, Performance, Physics

November 16, 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

Improving Communication Performance in GPU-Accelerated HPC Clusters

Scheduling Parallel Tasks under Multiple Resources: List Scheduling vs. Pack Scheduling

Comprehensive Optimization of Parametric Kernels for Graphics Processing Units

Evaluation of Machine Learning Fameworks on Finis Terrae II

Analysing the Performance of GPU Hash Tables for State Space Exploration

Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer

Protecting Real-Time GPU Applications on Integrated CPU-GPU SoC Platforms

MILC Code Performance on High End CPU and GPU Supercomputer Clusters

Study of Bandwidth Partitioning for Co-executing GPU Kernels

Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs

Launch-time Optimization of OpenCL Kernels

Accelerating HPC codes on Intel(R) Omni-Path Architecture networks: From particle physics to Machine Learning

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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