Software Engineering Radio - the podcast for professional software developers

Episode 479: Luis Ceze on the Apache TVM Machine Learning Compiler

Sep 29, 2021

51:29

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Highlights

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Episode notes

How to Debug a Machine Leani Model?

02:57

Compilers and Correctness

02:34

Data Scientists Don't Have to Worry About Deployment

01:51

Introduction

2min

The Life Cycle of Machine Learning

3min

The Difference Between a Simple Machine Learning and a Complex Machine Learning Model?

3min

How to Optimize Your Models With TVM?

5min

How Complex Is That for a Linear Aggression Model?

3min

TvM: A Compiler That Takes in a Model and Gives You Talket Architecture

4min

Is the Lowest Level API Enabled in Machine Learning?

2min

Is There a Library of Model Descriptions?

2min

Is There a More Specifiable One Out There?

5min

10.

Ss Radio Listeners, We Want to Hear From You!

2min

11.

How to Estimate the Accuracy of a Machine Learning Model?

2min

12.

Data Scientists Don't Have to Worry About Deployment

2min

13.

How to Debug a Machine Leani Model?

3min

14.

How to Deploy a Model on Multiple Architectures?

4min

15.

Compilers and Correctness

3min

16.

Is There a Hardware Designer in TV M?

2min

17.

How to Package a Modo Into a Python Package

2min

18.

Machine Learning - Where Do You See It Going in the Future?

5min

Luis Ceze of OctoML discusses Apache TVM, an open source machine learning model compiler for a variety of different hardware architectures with host Akshay Manchale. Luis talks about the challenges in deploying models on specialized hardware and how TVM.