high performance computing on graphics processing units: hgpu.org

Yao-Yuan Yang, Moto Hira, Zhaoheng Ni, Anjali Chourdia, Artyom Astafurov, Caroline Chen, Ching-Feng Yeh, Christian Puhrsch, David Pollack, Dmitriy Genzel, Donny Greenberg, Edward Z. Yang, Jason Lian, Jay Mahadeokar, Jeff Hwang, Ji Chen, Peter Goldsborough, Prabhat Roy, Sean Narenthiran, Shinji Watanabe, Soumith Chintala, Vincent Quenneville-Bélair, Yangyang Shi

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Tags: Computer science, Deep learning, Machine learning, nVidia, nVidia A100, Package, Python, PyTorch, Speech recognition

October 31, 2021 by hgpu

OMB-Py: Python Micro-Benchmarks for Evaluating Performance of MPI Libraries on HPC Systems

Nawras Alnaasan, Arpan Jain, Aamir Shafi, Hari Subramoni, Dhabaleswar K Panda

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Tags: Benchmarking, Computer science, CUDA, Deep learning, HPC, Machine learning, MPI, nVidia, Python, Tesla V100

October 24, 2021 by hgpu

Taskflow: A Lightweight Parallel and Heterogeneous Task Graph Computing System

Tsung-Wei Huang, Dian-Lun Lin, Chun-Xun Lin, Yibo Lin

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Tags: Computer science, CUDA, Heterogeneous systems, HPC, Machine learning, nVidia, nVidia GeForce GTX 2080, Package

September 26, 2021 by hgpu

IgNet. A Super-precise Convolutional Neural Network

Igor Mackarov

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Tags: Computer science, Machine learning, Neural networks, OpenCL

September 26, 2021 by hgpu

An Experimental Study of SYCL Task Graph Parallelism for Large-Scale Machine Learning Workloads

Cheng-Hsiang Chiu, Dian-Lun Lin, Tsung-Wei Huang

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 2080, SYCL

September 26, 2021 by hgpu

CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research

Chris Cummins, Bram Wasti, Jiadong Guo, Brandon Cui, Jason Ansel, Sahir Gomez, Somya Jain, Jia Liu, Olivier Teytaud, Benoit Steiner, Yuandong Tian, Hugh Leather

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Tags: Artificial intelligence, Benchmarking, Compilers, Computer science, CUDA, Machine learning, nVidia, Package, Performance

September 26, 2021 by hgpu

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high performance computing on graphics processing units: hgpu.org

Programming Heterogeneous Systems with General and Domain-Specific Frameworks

Performance Evaluation of Python ParallelProgramming Models: Charm4Py and mpi4py

Collage: Automated Integration of Deep Learning Backends

Optimizing a Hardware Network Stack to Realize an In-Network ML Inference Application

Source-to-Source Automatic Differentiation of OpenMP Parallel Loops

Mixed precision in Graphics Processing Unit

TorchAudio: Building Blocks for Audio and Speech Processing

OMB-Py: Python Micro-Benchmarks for Evaluating Performance of MPI Libraries on HPC Systems

Taskflow: A Lightweight Parallel and Heterogeneous Task Graph Computing System

IgNet. A Super-precise Convolutional Neural Network

An Experimental Study of SYCL Task Graph Parallelism for Large-Scale Machine Learning Workloads

CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research

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