high performance computing on graphics processing units: hgpu.org

Amrita Mathuriya, Deborah Bard, Peter Mendygral, Lawrence Meadows, James Arnemann, Lei Shao, Siyu He, Tuomas Karna, Daina Moise, Simon J. Pennycook, Kristyn Maschoff, Jason Sewall, Nalini Kumar, Shirley Ho, Mike Ringenburg, Prabhat, Victor Lee

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Tags: Astrophysics, Cosmology, CUDA, Deep learning, Intel Xeon Phi, Machine learning, nVidia, Package, TensorFlow, Tesla P100

August 19, 2018 by hgpu

GPU parallelization of a hybrid pseudospectral fluid turbulence framework using CUDA

Duane Rosenberg, Pablo D. Mininni, Raghu Reddy, Annick Pouquet

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Tags: cfd, CUDA, FFT, Fluid dynamics, MPI, Numerical simulation, nVidia, OpenMP, Tesla K20, Tesla P100

August 11, 2018 by hgpu

CRUM: Checkpoint-Restart Support for CUDA’s Unified Memory

Rohan Garg, Apoore Mohan, Michael Sullivan, Gene Cooperman

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Tags: Computer science, CUDA, Heterogeneous systems, MPI, nVidia, Tesla P100

August 5, 2018 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

ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers

Delivering Performance-Portable Stencil Computations on CPUs and GPUs Using Bricks

SIMD-X: Programming and Processing of Graph Algorithms on GPUs

Performance Portability Challenges for Fortran Applications

SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks

Spatter: A Benchmark Suite for Evaluating Sparse Access Patterns

Towards Efficient Large-Scale Graph Neural Network Computing

Scalability Analysis of Synchronous Data-Parallel Artificial Neural Network (ANN) Learners

Performance Evaluation of OpenMP’s Target Construct on GPUs – Exploring Compiler Optimizations

CosmoFlow: Using Deep Learning to Learn the Universe at Scale

GPU parallelization of a hybrid pseudospectral fluid turbulence framework using CUDA

CRUM: Checkpoint-Restart Support for CUDA’s Unified Memory

Recent source codes

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

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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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