October 8, 2021
It is well known in the high-performance computing (HPC) community that many (perhaps most) HPC workloads exhibit dynamic performance envelopes that can stress Read more…
January 13, 2020
Typically, code’s performance on a given computer chip is estimated using performance models that test the code on a variety of architectures, after which com Read more…
September 12, 2010
Last week marked the release of ADIOS 1.2, the latest incarnation of one of computational science’s most effective I/O tools. So far ADIOS has helped researchers make huge strides in fusion, astrophysics and combustion. The new version features some interesting improvements that will doubtless aid researchers in taking full advantage of leading supercomputing platforms. Read more…
July 19, 2010
Although many HPC users are among the first to consider application performance when looking to the clouds as an alternative, enterprise users might overlook the importance of this aspect of adoption. With poor application performance, any cost benefits of moving to the cloud could be negated. Read more…
March 5, 2009
Want to improve application performance by 10x or 100x? Few HPC customers would say no. Benchmarks that focus on kernel performance can provide important information, but only total application benchmarking can give customers a true picture of how an HPC system will function back in their data center. 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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