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Closing ISC Keynote by Sterling and Suarez Looks Backward and Forward
ISC’s closing keynote this year was given jointly by a pair of distinguished HPC leaders, Thomas Sterling of Indiana University and Estela Suarez of Jülich Supercomputing Centre (JSC). Ostensi …
Exascale Frontier Supercomputer Has Passed Formal Acceptance: What That Means
Fresh off their third Top500 win for Frontier – now with an 8.4% higher Linpack score – the HPC team at Oak Ridge National Laboratory had some exciting news to share today. Frontier has passe …
Intel Admits GPU Mistakes, Reveals New Supercomputing Chip Roadmap
May 22, 2023
Intel has finally provided specific details on wholesale changes it has made to its supercomputing chip roadmap after an abrupt reversal of an ambitious plan to Read more…
Nvidia Announces Hybrid Classical-Quantum Lab at Jülich SC; Touts Rolls Royce Quantum Simulation
May 21, 2023
At ISC this week, Nvidia announced plans for a new hybrid classical-quantum computing lab with partners Jülich Supercomputing Centre and ParTec. The new lab is Read more…
Eviden (Atos) Launches Qaptiva Platform for Quantum Software Development
May 11, 2023
Eviden – soon to be the independent half of European IT giant Atos which is splitting itself in two this year – today introduced a broad quantum computing p Read more…
Google’s New AI-Focused ‘A3’ Supercomputer Has 26,000 GPUs
May 10, 2023
Cloud providers are building armies of GPUs to provide more AI firepower. Google is joining the gang with a new supercomputer that has almost 2.5 times the number of GPUs than the world’s third-fastest supercomputer called LUMI. Google announced an AI supercomputer with 26,000 GPUs at its developer conference on Wednesday. Read more…
Intel’s Habana Labs Takes on Prominent Role as Generative AI Surges
May 9, 2023
Intel acquired AI chipmaker Habana Labs just four years ago; now, the division is serving – per Habana COO Eitan Medina – as “effectively the center of ex Read more…
Microsoft and ETH Take Aim at Quantum Computing’s Hype (and Promise)
May 2, 2023
A fascinating ACM paper by researchers Torsten Hoefler (ETH Zurich), Thomas Häner (Microsoft*) and Matthias Troyer (Microsoft) – "Disentangling Hype from Pra Read more…
Quantum Centers, National Labs Tackle Workforce and Public-Private Partnering
April 28, 2023
This year, the U.S. National Quantum Initiative Act (NQIA), passed in 2018, is up for re-authorization by Congress. NQIA is a complicated $2B-plus effort and on Read more…
Intel Puts a Happy Face on Its Worst Quarterly Loss Ever
April 27, 2023
Intel posted its worst quarterly loss in history on Thursday, but the chipmaker took a bold move to put a positive spin on the grim news. “We delivered solid first-quarter results, representing steady progress with our transformation,” said Pat Gelsinger, Intel's CEO, in a press release. Read more…
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Powering Up Automotive Simulation: Why Migrating to the Cloud is a Game Changer
The increasing complexity of electric vehicles result in large and complex computational models for simulations that demand enormous compute resources. On-premises high-performance computing (HPC) clusters and computer-aided engineering (CAE) tools are commonly used but some limitations occur when the models are too big or when multiple iterations need to be done in a very short term, leading to a lack of available compute resources. In this hybrid approach, cloud computing offers a flexible and cost-effective alternative, allowing engineers to utilize the latest hardware and software on-demand. Ansys Gateway powered by AWS, a cloud-based simulation software platform, drives efficiencies in automotive engineering simulations. Complete Ansys simulation and CAE/CAD developments can be managed in the cloud with access to AWS’s latest hardware instances, providing significant runtime acceleration.
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Five Recommendations to Optimize Data Pipelines
When building AI systems at scale, managing the flow of data can make or break a business. The various stages of the AI data pipeline pose unique challenges that can disrupt or misdirect the flow of data, ultimately impacting the effectiveness of AI storage and systems.
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