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Flexible Systems for the Next ML Revolution(s)

The environment for machine learning innovation has never been better. Modern GPUs are marvels of supercomputer engineering. And software stacks have raised the level of abstraction for ML implementations...

Adrian Sampson

Adrian Sampson

Jan 6, 2022

Collage: Automated integration of various deep learning backends results in state of the art model performance

At TVMCon this week, we will be presenting our latest research from Carnegie Mellon University and University of Michigan for generating the fastest possible executable for a given machine learning model by using Collage.

Byungsoo Jeon
Sunghyun Park

Dec 15, 2021

OctoML Raises $85M Series C to Accelerate ML Deployment for Enterprises Everywhere

OctoML has raised $85M led by Tiger Global Management, with participation from existing investors Addition, Madrona Venture Group and Amplify Partners.

Luis Ceze

Luis Ceze

Nov 1, 2021

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Adrian Sampson

Adrian Sampson

Apr 6, 2022

Adrian Sampson

Adrian Sampson

Apr 6, 2022

Beware the Tensor From Hell: How to Avert the Combinatorial Complexity Explosion in ML Engineering

In an earlier era, deploying ML systems was not exactly easy, but at least the problem was contained. Engineers could focus on a few important models, all of which built on similar libraries and tools. That era of uniformity is gone.

Sameer Farooqui

Sameer Farooqui

Feb 2, 2022

Sameer Farooqui

Sameer Farooqui

Feb 2, 2022

OctoML helps Woven Planet run ML inference for the next generation of smart technologies

OctoML is helping Woven Planet use Apache TVM as a core component of the Arene AI Platform to accelerate ML inference and simplify deployment across various targets.

Chris Hoge

Chris Hoge

Jan 13, 2022

Chris Hoge

Chris Hoge

Jan 13, 2022

TVMCon 2021 Wrapup

The Apache TVM Community and OctoML closed out 2021 with the fourth annual Apache TVM and Open Source ML Acceleration Conference. It was the TVM community’s largest event ever, with 700 attendees from 34 nations coming together for a virtual conference...

Adrian Sampson

Adrian Sampson

Jan 11, 2022

Adrian Sampson

Adrian Sampson

Jan 11, 2022

The Future of Hardware is Software

General-purpose GPU computing helped launch the deep learning era. As ML models have grown larger and more computationally intense, however, they have changed the way GPUs are designed—and they have inspired a wave of new hardware that looks radically different from GPUs.

Adrian Sampson

Adrian Sampson

Jan 6, 2022

Adrian Sampson

Adrian Sampson

Jan 6, 2022

Flexible Systems for the Next ML Revolution(s)

The environment for machine learning innovation has never been better. Modern GPUs are marvels of supercomputer engineering. And software stacks have raised the level of abstraction for ML implementations...

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Accelerate Performance and Deployment Time