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Workload-aware Automatic Parallelization for Multi-GPU DNN Training

Sungho Shin, Youngmin Jo, Jungwook Choi, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wonyong Sung

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Tags: Artificial intelligence, Computer science, Deep learning, Neural networks, nVidia, nVidia DGX-1, nVidia GeForce GTX Titan XP, nVidia Tesla GP100

November 11, 2018 by hgpu

Programming Your GPU with OpenMP: A Hands-On Introduction

Evaluating the performance of HPC-style SYCL applications

sycl-bench: SYCL Benchmark Suite

SYCL-Bench: A Versatile Single-Source Benchmark Suite for Heterogeneous Computing

BlaBla: A Python package for clinical linguistic feature extraction in multiple languages

BlaBla: Linguistic Feature Extraction for Clinical Analysis in Multiple Languages

gocudnn: Go Bindings for cudnn and other cuda pacakges

Deep Learning with GO

Task-Based Parallel Strategies for CFD Application in Heterogeneous CPU/GPU Resources

Task-Based Parallel Strategies for CFD Application in Heterogeneous CPU/GPU Resources

DALI: a library containing both highly optimized building blocks and an execution engine for data pre-processing in deep learning applications

Importance of Data Loading Pipeline in Training Deep Neural Networks

AutoParBench: a benchmark framework to evaluate compilers and tools designed to automatically insert OpenMP directives

AutoParBench: A Unified Test Framework for OpenMP-based Parallelizers

DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy

cuda-kat: The CUDA Kernel Author's Toolkit

cuda-kat: The CUDA Kernel Author’s Toolkit

GEVO: GPU Code Optimization using Evolutionary Computation

GEVO: GPU Code Optimization using Evolutionary Computation

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2020

April

27-29

Munich, Germany

8th International Workshop on OpenCL, including SYCLCon, 2019

2019

May

13-15

Boston, USA

7th International Workshop on OpenCL, 2019

2019

May

13

Boston, MA, USA

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

2019

May

14

Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Neural Networks (ICFNN), 2019

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