October 5, 2022
In June 2020, the NSF awarded the National Center for Supercomputing Applications (NCSA) $10 million for its post-Blue Waters “Delta” supercomputer. Now, th Read more…
August 9, 2022
Argonne National Laboratory has made its newest supercomputer, Polaris, available for scientific research. The system, which ranked 14th on the most recent Top500 list, is serving as a testbed for the exascale Aurora system slated for delivery in the coming months. The HPE-built Polaris system (pictured in the header) consists of 560 nodes... Read more…
February 24, 2022
Technology heavyweight Hewlett Packard Enterprise and optical IO startup Ayar Labs have embarked on a strategic collaboration to advance silicon photonics in the datacenter and integrate optical IO into a future generation of HPE’s Slingshot interconnect. Optical-based interconnects are essential to overcoming the bandwidth, latency, power and distance... Read more…
September 8, 2021
Additional details came to light on Argonne National Laboratory’s preparation for the 2022 Aurora exascale-class supercomputer, during the HPC User Forum, held virtually this week on account of pandemic. Exascale Computing Project director Doug Kothe reviewed some of the 'early exascale hardware' at Argonne, Oak Ridge and NERSC (Perlmutter), while Ti Leggett, Deputy Project Director & Deputy Director... Read more…
August 25, 2021
A new 44-petaflops (theoretical peak) supercomputer is under construction at the Department of Energy’s Argonne National Laboratory. Called Polaris, this new Read more…
March 11, 2020
Last week, the day before the El Capitan processor disclosures were made at HPE's new headquarters in San Jose, Steve Scott (CTO for HPC & AI at HPE, and former Cray CTO) was on-hand at the Rice Oil & Gas HPC conference in Houston. He was there to discuss the HPE-Cray transition and blended roadmap, as well as his favorite topic, Cray's eighth-gen networking technology, Slingshot. Read more…
May 22, 2019
More so than with most acquisitions of this kind, HPE’s purchase of Cray for $1.3 billion, announced last week, seems to have elements of that overused, often Read more…
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.
Two recent studies show how Ansys Gateway powered by AWS can balance run times and costs, making it a compelling solution for automotive development.
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.
With so many applications and diverse requirements for data types, management systems, workloads, and compliance regulations, these challenges are only amplified. Without a clear, continuous flow of data throughout the AI data lifecycle, AI models can perform poorly or even dangerously.
To ensure your AI systems are optimized, follow these five essential steps to eliminate bottlenecks and maximize efficiency.
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