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USENIX LISA2021 Computing Performance: On the Horizon

Brendan Gregg

AWS Graviton2); for memory with the arrival of DDR5 and High Bandwidth Memory (HBM) on-processor; for storage including new uses for 3D Xpoint as a 3D NAND accelerator; for networking with the rise of QUIC and eXpress Data Path (XDP); and so on. I also wrote about these topics in detail for my recent [Systems Performance 2nd Edition] book.

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USENIX SREcon APAC 2022: Computing Performance: What's on the Horizon

Brendan Gregg

Google and Amazon’s latest AI chips have arrived," [link] Oct 2022 - [Intel 22] Intel, "Intel® Developer Cloud," [link] accessed Dec 2022 I've taken care to cite the author names along with the talk titles and dates, including for Internet sources, instead of the common practice of just listing URLs.

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Platform Engineering Teams Done Right…

Adrian Cockcroft

We used this model effectively at Netflix when I was their cloud architect from 2010 through 2013. The layers of platforms start at the bottom with hardware choices such as which CPU architectures and vendors you want to use. There are three current underlying reasons for the platform engineering meme today.

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USENIX SREcon APAC 2022: Computing Performance: What's on the Horizon

Brendan Gregg

As for attending USENIX conferences: I finally started attending and speaking at them in 2010 when a community manager encouraged me to (thanks Deirdre Straughan), and since then I've met many friends and connections, including Amy who is now USENIX President, and Rikki with whom I co-chaired the USENIX LISA18 conference.

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USENIX LISA2021 Computing Performance: On the Horizon

Brendan Gregg

AWS Graviton2); for memory with the arrival of DDR5 and High Bandwidth Memory (HBM) on-processor; for storage including new uses for 3D Xpoint as a 3D NAND accelerator; for networking with the rise of QUIC and eXpress Data Path (XDP); and so on. I also wrote about these topics in detail for my recent [Systems Performance 2nd Edition] book.

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Structural Evolutions in Data

O'Reilly

Doubly so as hardware improved, eating away at the lower end of Hadoop-worthy work. And that brings our story to the present day: Stage 3: Neural networks High-end video games required high-end video cards. ” There’s as much Keras, TensorFlow, and Torch today as there was Hadoop back in 2010-2012.

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The Performance Inequality Gap, 2024

Alex Russell

It's time once again to update our priors regarding the global device and network situation. HTML, CSS, images, and fonts can all be parsed and run at near wire speeds on low-end hardware, but JavaScript is at least three times more expensive, byte-for-byte. What's changed since last year? and 75KiB of JavaScript.