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…
October 18, 2022
Oracle is bringing Nvidia's AI Enterprise software suite alongside thousands of its latest GPUs to its cloud infrastructure, which could fuel the chipmaker’s Read more…
November 19, 2021
SC21 may have been the first major supercomputing conference to return to in-person activities, but not everything returned to the live menu: the Student Cluster Competition – held virtually at ISC 2020, SC20 and ISC 2021 – was again held virtually at SC21. Nevertheless, [email protected] Chair Jay Lofstead took the physical stage at SC21 on Thursday to announce the... Read more…
May 27, 2021
At the end of 2019, strange pneumonia cases started cropping up in Wuhan, China. As Wuhan (then China, then the world) scrambled to contain what would, of cours Read more…
May 25, 2021
Oracle Cloud Infrastructure (OCI) today launched a multi-prong Arm initiative including instances (VM and bare metal) based on Ampere’s Altra microprocessor, Read more…
April 27, 2021
Chip designer Arm Holdings is sharing details about its Neoverse V1 and N2 cores, introducing its new CMN-700 interconnect, and showcasing its partners' plans t Read more…
April 6, 2021
The wait is over. Today Intel officially launched its 10nm datacenter CPU, the third-generation Intel Xeon Scalable processor, codenamed Ice Lake. With up to 40 Read more…
March 30, 2021
The extraordinarily rapid drug development necessitated by the COVID-19 pandemic may have pulled AI- and HPC-accelerated pharmacology into the spotlight, but si 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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