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How FPGAs Accelerate Financial Services Workloads
While FSI companies are unlikely, for competitive reasons, to disclose their FPGA strategies, James Reinders offers insights into the case for FPGAs as accelerators for FSI by discussing performa …
Update from Gregory Kurtzer on Singularity’s Push into FS and the Enterprise
Container technology is hardly new but it has undergone rapid evolution in the HPC space in recent years to accommodate traditional science workloads and HPC systems requirements. While Docker co …
At HPC on Wall Street: AI-as-a-Service Accelerates AI Journeys
AIaaS – artificial intelligence-as-a-service – is the technology discipline that eases enterprise entry into the mysteries of the AI journey while lowering the financial risk. It’s already …
HPC on Wall Street: A Conference on Advanced Technology Strategies in the Financial Services Industry
September 6, 2018
Few industries are more avid for low latency, compute power and high performance data analytics (HPDA) than the financial services sector. The investment banks, Read more…
Weathering the Next ‘Great’ Storm in the Market
September 1, 2018
This is not an article about the joys and wonders of machine learning or big data. Instead, this article is about a pernicious, unsolved problem in investment f Read more…
Report: Financial Services Sector in $14B Analytics Binge
September 1, 2018
The phrase “big data” has come to mean different things to different people, morphing from the huge data volumes too big for traditional databases to handle Read more…
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Powering Up Automotive Simulation: Why Migrating to the Cloud is a Game Changer
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.
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How to Save 80% with TotalCAE Managed On-prem Clusters and Cloud
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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Whitepaper: QCT HPC BeeGFS Storage: A Performance Environment for I/O Intensive Workloads
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