Read the Jesus parts again. Would Jesus like that?

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Cake day: August 12th, 2023

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  • Actually, power draw timing is a huge issue, destroying electrical substations huge, with AI data centers.

    https://arxiv.org/abs/2508.14318

    Large Artificial Intelligence (AI) training workloads spanning several tens of thousands of GPUs present unique power management challenges. These arise due to the high variability in power consumption during the training. Given the synchronous nature of these jobs, during every iteration there is a computation-heavy phase, where each GPU works on the local data, and a communication-heavy phase where all the GPUs synchronize on the data. Because compute-heavy phases require much more power than communication phases, large power swings occur. The amplitude of these power swings is ever increasing with the increase in the size of training jobs. An even bigger challenge arises from the frequency spectrum of these power swings which, if harmonized with critical frequencies of utilities, can cause physical damage to the power grid infrastructure. Therefore, to continue scaling AI training workloads safely, we need to stabilize the power of such workloads. This paper introduces the challenge with production data and explores innovative solutions across the stack: software, GPU hardware, and datacenter infrastructure. We present the pros and cons of each of these approaches and finally present a multi-pronged approach to solving the challenge. The proposed solutions are rigorously tested using a combination of real hardware and Microsoft’s in-house cloud power simulator, providing critical insights into the efficacy of these interventions under real-world conditions.

    By Esha Choukse, Brijesh Warrier, Scot Heath, Luz Belmont, April Zhao, Hassan Ali Khan, Brian Harry, Matthew Kappel, Russell J. Hewett, Kushal Datta, Yu Pei, Caroline Lichtenberger, John Siegler, David Lukofsky, Zaid Kahn, Gurpreet Sahota, Andy Sullivan, Charles Frederick, Hien Thai, Rebecca Naughton, Daniel Jurnove, Justin Harp, Reid Carper, Nithish Mahalingam, Srini Varkala, Alok Gautam Kumbhare, Satyajit Desai, Venkatesh Ramamurthy, Praneeth Gottumukkala, Girish Bhatia, Kelsey Wildstone, Laurentiu Olariu, Ileana Incorvaia, Alex Wetmore, Prabhat Ram, Melur Raghuraman, Mohammed Ayna, Mike Kendrick, Ricardo Bianchini, Aaron Hurst, Reza Zamani, Xin Li, Michael Petrov, Gene Oden, Rory Carmichael, Tom Li, Apoorv Gupta, Pratikkumar Patel, Nilesh Dattani, Lawrence Marwong, Rob Nertney, Hirofumi Kobayashi, Jeff Liott, Miro Enev, Divya Ramakrishnan, Ian Buck, Jonah Alben









  • Elsewhere in this thread. Anyway, here is what I had said:

    There are “electric truck” conversion books from the 1970s. (Only trucks as they used lead acid batteries, which are still extremely heavy for useful amounts of stored energy.) This indicates it is not extremely complex, though possibly still very complex. (My reason for this assessment is from reading a few of them, but never implementing any of it.)

    Anyway, here is a title to look for, from 2011, " The electric vehicle conversion handbook : how to convert cars, trucks, motorcycles, and bicycles : includes EV components, kits, and project vehicles" by Warner, Mark, ISBN: 9781557885685 1557885680.

    2021’s “Convert It!: A simple step-by-step guide for converting any classic car into an electric vehicle.” by Ron Toms, ASIN B093CH8HR7.

    Neither are from the 1970s, but both are likely more useful anyway. There are also likely others that I cannot immediately find. I have read neither, yet.