March 1, 2022
Singapore has worked hard to make its mark in the supercomputing world, predominantly through its National Supercomputing Center (NSCC). Now, at the SupercomputingAsia 2022 (SCA22) conference—itself hosted in Singapore—the NSCC, Nvidia and Singaporean Health Services (SingHealth) announced that they have partnered to expand the nation’s healthcare and medical research through advanced computing. Read more…
November 6, 2014
The University of Washington Computer Science and Engineering Distinguished Lecture series recently welcomed Calit2 luminary Larry Smarr to speak on a very inte Read more…
August 28, 2014
The HPC community has been following IBM's Watson technology since a semi-personified version of the analytics machine became a winning Jeopardy contestant in 2 Read more…
May 19, 2014
Based on the number of prominent research projects currently in the works, 2014 could be a tipping point for the field of personalized medicine and in silico re Read more…
September 30, 2013
Computing and simulation methods have had a transformative effect on science and research. At a recent conference, prominent experts in biomedicine gathered to discuss HPC's role in transforming the field. Read more…
September 25, 2013
A group of researchers from UC Berkeley and UCSD used NERSC supercomputing resources to model the efficacy of microbubbles and high-intensity ultrasound for breaking up stroke-causing clots. Read more…
September 5, 2013
When it comes to employing physics in medicine, there are two major fields in terms of their relevance in clinical practice: medical imaging and radiation therapy. An Argentinian research duo addresses how these domains can benefit from high-performance computing techniques... Read more…
August 21, 2013
San Diego Supercomputer Center (SDSC) is announcing a bold new cloud and analytics-based initiative, called Sherlock. Established by SDSC with the assistance of SD Technology and Chickasaw Nation Industries, the Sherlock-branded project represents an "extensive portfolio of information technology services for healthcare and government." 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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