Accelerating innovation and powering big compute at hundreds of leading enterprises
With the year coming to a close, I’m excited to share the progress we’ve made at Rescale—not only as the leading Big Compute and cloud HPC solution in the market, but also as one of the fastest growing enterprise software companies of 2017. It’s been a busy year as we’ve landed over 100 new enterprise customers, fueling our rapid growth in multiple key industry verticals including aerospace, automotive, life sciences, universities and with broad geographic coverage throughout the Americas, Europe, and Asia.
Our customers are deeply engaging with the ScaleX Enterprise platform and our portfolio of industry solutions. Usage of Rescale has grown by 30% month-over-month throughout the entire year, resulting in numerous Silicon Valley investors identifying Rescale as the fastest growing enterprise software company in 2017. Customers are delivering incredible results accelerating their innovation capabilities, including: Airbus accelerating development of complex aerodynamics, LSIS deploying the first cloud-based engineering environment in Korea, RWDI implementing hybrid HPC across their enterprise, Boom Supersonic building the world’s next-generation supersonic jetliner, and many more.
This article was written by Joris Poort.
This article originally appeared on ENGINEERING.com. To see the full article, click here.
The concept of the digital twin brings versatility to the engineering world. By creating a virtual representation of a product, engineers can investigate designs to further product development, in-service optimizations and quality assurance.
Digital twins help engineers predict real world behavior, optimize designs and gain new insights and understandings of use cases. (Image courtesy of Rescale.)
Now with the implementation of the Internet of Things (IoT), the potential of the digital twin grows.
Engineers can link real-time data into their digital mock-ups, allowing for better understandings of the physical world.
However, digital twins don’t just come off the shelf. Since every modeled behavior is built in different system, engineering and IT teams experience a considerable challenge linking their disparate tools into one model. Joris Poort, CEO of Rescale, explained that this is where vendor-agnostic cloud HPC, like Rescale, can really shine.
To continue reading, please read the full article on ENGINEERING.com.
This article was written by Shawn Wasserman, ENGINEERING.com.
The Fédération Internationale de l’Automobile (FIA) released the latest version of sporting and technical regulations for 2017 Formula One Grand Prix on April 29, 2016. This document is the rulebook that all Formula One racing teams must follow in the 2017 season. All of the restrictions of CFD simulations are clearly defined in Appendix 8 (Aerodynamic Testing Restrictions) – section 2 of the sporting regulations.
Computational Fluid Dynamics (CFD), a widely accepted methodology in automobile aerodynamics R&D, has been proven to speed up the turnaround time effectively. The biggest upside is that it doesn’t involve any part manufacturing and all proof of concepts (POC) can be done on computers. In the high-end auto industry, such as sports and racing vehicle makers, CFD has been used even more intensively. In this blog post, I’ll illustrate why Formula One racing teams should leverage the cloud to advance their CFD designs and why FIA, as the governing body of the sport, would also benefit from pushing it forward.
This article was written by Irwen Song.
In 1991, I joined Cray and had the opportunity to work on the machines Seymour Cray designed. I was working on the operating system and would often have to work alone on it at night, but the excitement of working on such unique systems kept me going. The Cray 1, XMP, YMP, represented a family of machines where a differentiated architecture and design allowed you to solve problems that you just couldn’t solve with a regular computer.
When I joined, Cray was considering building a new type of parallel machines we called MPPs (massively parallel processing). I worked on the design and implementation of the operating system for the Cray T3E, a system with 2048 individual nodes, with standard CPU chips, memory, and a proprietary high-speed interconnect. Ahead of its time, Cray was building what we today call HPC clusters. Besides it being a fantastic engineering project, it was the beginning of a disruption: going from proprietary Cray architectures to clusters of nodes with commodity parts.
This article was written by Gabriel Broner.