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The Mainstreaming of MLPerf? Nvidia Dominates Training v2.0 but Challengers Are Rising

June 29, 2022

MLCommons’ latest MLPerf Training results (v2.0) issued today are broadly similar to v1.1 released last December. Nvidia still dominates, but less so (no gran Read more…

ACES ‘Composable’ Supercomputer Gets Ready for Phase One Use

April 4, 2022

Later this spring, ACES – the new ‘composable’ supercomputer being stood up at Texas A&M University – will begin granting Phase One access to early Read more…

Graphcore Launches Wafer-on-Wafer ‘Bow’ IPU

March 3, 2022

Graphcore introduced its AI-focused, PCIe-based Intelligent Processing Units (IPUs) six years ago. Since then, the company has done anything but slow down, announcing a second generation of IPUs in 2020 and, over the years, larger and larger IPU-based “IPU-POD” systems — most recently the IPU-POD128 and the IPU-POD256, both announced just a few months... Read more…

Nvidia Dominates Latest MLPerf Results but Competitors Start Speaking Up

December 1, 2021

MLCommons today released its fifth round of MLPerf training benchmark results with Nvidia GPUs again dominating. That said, a few other AI accelerator companies Read more…

Graphcore Introduces Larger-Than-Ever IPU-Based Pods

October 22, 2021

After launching its second-generation intelligence processing units (IPUs) in 2020, four years after emerging from stealth, Graphcore is now boosting its produc Read more…

Three Universities Team for NSF-Funded ‘ACES’ Reconfigurable Supercomputer Prototype

September 23, 2021

As Moore’s law slows, HPC developers are increasingly looking for speed gains in specialized code and specialized hardware – but this specialization, in turn, can make testing and deploying code trickier than ever. Now, researchers from Texas A&M University, the University of Illinois at Urbana... Read more…

Latest MLPerf Results: Nvidia Shines but Intel, Graphcore, Google Increase Their Presence

June 30, 2021

While Nvidia (again) dominated the latest round of MLPerf training benchmark results, the range of participants expanded. Notably, Google’s forthcoming TPU v4 Read more…

AI Silicon Startup Graphcore Launches Channel Partner Program

September 23, 2020

AI compute platform vendor Graphcore has launched its first formal global channel partner program to promote and boost the sales of its AI processors and blade computing products. The formalized, all-new Graphcore Elite Partner Program follows the company’s past history of working with several... Read more…

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From Hallucination to Reality

As Federal agencies navigate an increasingly complex and data-driven world, learning how to get the most out of high-performance computing (HPC), artificial intelligence (AI), and machine learning (ML) technologies is imperative to their mission. These technologies can significantly improve efficiency and effectiveness and drive innovation to serve citizens' needs better. Implementing HPC and AI solutions in government can bring challenges and pain points like fragmented datasets, computational hurdles when training ML models, and ethical implications of AI-driven decision-making. Still, CTG Federal, Dell Technologies, and NVIDIA unite to unlock new possibilities and seamlessly integrate HPC capabilities into existing enterprise architectures. This integration empowers organizations to glean actionable insights, improve decision-making, and gain a competitive edge across various domains, from supply chain optimization to financial modeling and beyond.

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Whitepaper

Why IT Must Have an Influential Role in Strategic Decisions About Sustainability

Data centers are experiencing increasing power consumption, space constraints and cooling demands due to the unprecedented computing power required by today’s chips and servers. HVAC cooling systems consume approximately 40% of a data center’s electricity. These systems traditionally use air conditioning, air handling and fans to cool the data center facility and IT equipment, ultimately resulting in high energy consumption and high carbon emissions. Data centers are moving to direct liquid cooled (DLC) systems to improve cooling efficiency thus lowering their PUE, operating expenses (OPEX) and carbon footprint.

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