AI-ML Articles
- November 13, 2022
- Author: David Strom
AMD’s announcement of its fourth generation EPYC 9004 Series processors includes major advances in how these chipsets are designed and produced. Part 2 of 4.
- November 11, 2022
- Author: David Strom
AMD announces its fourth-generation EPYC™ CPUs. The new EPYC 9004 Series processors demonstrate advances in hybrid, multi-die architecture by decoupling core and I/O processes. Part 1 of 4.
- October 28, 2022
- Author:
Join Supermicro online Nov. 10th to watch the unveiling of the company’s new A+ systems -- featuring next-generation AMD EPYC™ processors. They can't tell us any more right now. But you can register for a link to the event by scrolling down and signing-up on this page.
- October 20, 2022
- Author: David Strom
Weka’s file system, WekaFS, unifies your entire data lake into a shared global namespace where you can more easily access and manage trillions of files stored in multiple locations from one directory.
- October 6, 2022
- Author: David Strom
Running heavy AI/ML workloads can be a challenge for any server, but the SuperBlade has extremely fast networking options, upgradability, the ability to run two AMD EPYC™ 7000-series 64-core processors and the Horovod open-source framework for scaling deep-learning training across multiple GPUs.
- September 22, 2022
- Author: David Strom
The Budapest Institute for Computer Science and Control (known as SZTAKI)
- September 21, 2022
- Author: David Strom
Lodestar is a complete management suite for developing artificial intelligence-based computer vision models from video data. It can handle the navigation and curation of a native video stream without any preparation. Lodestar annotates and labels video, and using artificial intelligence, creates searchable, structured data.
- August 18, 2022
- Author: David Strom
The Lawrence Livermore National Lababoratory chose to use a cluster of 120 servers running AMD EPYC™ processors with nearly 1,000 AMD Instinct™ GPU accelerators. The hardware, facilitated by Supermicro, was an excellent match for the molecular dynamics simulations required for the Lab's cutting-edge research, which combines machine learning with structural biology concepts.
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