December 8, 2022
The U.S. Department of Defense wielded its JEDI powers to procure public cloud services with a diplomatic end to a feud between Amazon and Google to win the multi-billion dollar contract. The DoD broke up a $9 billion contract between the top four cloud providers – Google, Amazon, Microsoft and Oracle – for the Joint Warfighting Cloud Capability initiative, which will bring the defense branches – Air Force, Army... Read more…
September 2, 2021
With cloud computing as the de facto deployment model in large enterprises, the usage of multiple clouds within a single enterprise has become omnipresent. The Read more…
February 4, 2020
Computer scientists at the University of Michigan have come up with a faster way to schedule cloud microservices via a new algorithm running on a custom processor. The platform, called Q-Zilla, is based on a widely used scheduling algorithm... Read more…
June 28, 2018
HPC in the cloud is one of those “insanely great” ideas that, failing to fire, year after year recedes before our expectations. Until, that is, last year, a Read more…
April 5, 2017
IBM announced today that it will be adding Nvidia P100 graphics processors to its Bluemix cloud later this month, becoming the "first major global cloud vendor Read more…
February 22, 2017
Just what constitutes HPC and how best to support it is a keen topic currently. A new paper posted last week on arXiv.org – Rethinking HPC Platforms: Challeng Read more…
January 26, 2017
Earlier this month, Cray announced that tech veteran Stathis Papaefstathiou had joined the ranks of the iconic supercomputing company. As senior vice president Read more…
September 7, 2016
If bigger is better, the new IT behemoth Dell Technologies Inc. that combines the holdings of Dell and storage leader EMC Corp. fits the bill with the completion a $60 billion merger of cloud, storage, virtualization and hardware components that will seek to be all things to all enterprise IT customers. 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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