June 7, 2023
Perhaps the most interesting slide at Hyperion Research’s annual ISC breakfast HPC market update was one without numbers, presented by research director Mark Read more…
February 23, 2023
Layoffs and the threat of delisting at Rigetti and less-well-publicized cash squeezes elsewhere in the young quantum computing landscape have caused a stir. Hyp Read more…
December 7, 2022
Hyperion Research delivered its latest outlook for the quantum computing market yesterday at the Q2B22 Conference, estimating revenues for 2022 will finish arou Read more…
November 8, 2022
Return to normalcy is too strong, but the latest portrait of the HPC market presented by Hyperion Research yesterday is a positive one. Total 2022 HPC revenue ( Read more…
May 30, 2022
While echoes of the pandemic continue rippling through the HPC landscape – primarily lingering supply chain issues – the outlook for the HPC market writ large is strong, according to Hyperion Research, which delivered its ISC 2022 HPC market update today. Last year, HPC spending (on premise, cloud, and AI) neared $35 billion and is on track to reach... Read more…
May 17, 2022
That supercomputers produce impactful, lasting value is a basic tenet among the HPC community. To make the point more formally, Hyperion Research has issued a n Read more…
November 15, 2021
Hyperion Research delivered its annual HPC market update at SC21 today. Much of it echoed Hyperion’s earlier mid-year report: the 2020 HPC market (on-premise) finished around $28B slightly up (~1.1 percent), roughly what was forecast in June. The gain was mostly due to the early standing-up of Fugaku. Read more…
November 15, 2021
At SC21 today, Xilinx launched its most powerful FPGA-based accelerator card – the Alveo U55C – specifically targeting HPC workloads and the datacenter. FPGAs (field programmable gate arrays) have a long productive history as customized accelerator chips used in many embedded applications. It’s only in the last few years that FPGA suppliers have begun... 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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