Search Results for author: Kim Hazelwood

Found 9 papers, 3 papers with code

Using Python for Model Inference in Deep Learning

no code implementations1 Apr 2021 Zachary DeVito, Jason Ansel, Will Constable, Michael Suo, Ailing Zhang, Kim Hazelwood

We evaluate our design on a suite of popular PyTorch models on Github, showing how they can be packaged in our inference format, and comparing their performance to TorchScript.

Model extraction

Understanding Training Efficiency of Deep Learning Recommendation Models at Scale

no code implementations11 Nov 2020 Bilge Acun, Matthew Murphy, Xiaodong Wang, Jade Nie, Carole-Jean Wu, Kim Hazelwood

The use of GPUs has proliferated for machine learning workflows and is now considered mainstream for many deep learning models.

Exploiting Parallelism Opportunities with Deep Learning Frameworks

1 code implementation13 Aug 2019 Yu Emma Wang, Carole-Jean Wu, Xiaodong Wang, Kim Hazelwood, David Brooks

State-of-the-art machine learning frameworks support a wide variety of design features to enable a flexible machine learning programming interface and to ease the programmability burden on machine learning developers.

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