Phil Brown — How IPUs are Advancing Machine Intelligence
Phil shares some of the approaches, like sparsity and low precision, behind the breakthrough performance of Graphcore's Intelligence Processing Units (IPUs).
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Phil Brown leads the Applications team at Graphcore, where they're building high-performance machine learning applications for their Intelligence Processing Units (IPUs), new processors specifically designed for AI compute.
Connect with Phil:
LinkedIn: https://www.linkedin.com/in/philipsbrown/
Twitter: https://twitter.com/phil_s_brown
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0:00 Sneak peek, intro
1:44 From computational chemistry to Graphcore
5:16 The simulations b…
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Chapters (11)
Sneak peek, intro
1:44
From computational chemistry to Graphcore
5:16
The simulations behind weather prediction
10:54
Measuring improvement in weather prediction systems
15:35
How high performance computing and ML have different needs
19:00
The potential of sparse training
31:08
IPUs and computer architecture for machine learning
39:10
On performance improvements
44:43
The impacts of increasing computing capability
50:24
The ML chicken and egg problem
52:00
The challenges of converging at scale and bringing hardware to market
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