MLPerf Inference 3.0 Highlights – Nvidia, Intel, Qualcomm and…ChatGPT

April 5, 2023

MLCommons today released the latest MLPerf Inferencing (v3.0) results for the datacenter and edge. While Nvidia continues to dominate the results – topping al Read more…

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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…

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…

Nvidia Dominates (Again) Latest MLPerf Inference Results

October 22, 2020

The two-year-old AI benchmarking group MLPerf.org released its second set of inferencing results yesterday and again, as in the most recent MLPerf training resu Read more…

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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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Transforming Industrial and Automotive Manufacturing

Divergent Technologies developed a digital production system that can revolutionize automotive and industrial scale manufacturing. Divergent uses new manufacturing solutions and their Divergent Adaptive Production System (DAPS™) software to make vehicle manufacturing more efficient, less costly and decrease manufacturing waste by replacing existing design and production processes.

Divergent initially used on-premises workstations to run HPC simulations but faced challenges because their workstations could not achieve fast enough simulation times. Divergent also needed to free staff from managing the HPC system, CAE integration and IT update tasks.

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