Cloud is key to transforming physical design
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a new survey by Rescale indicates that companies are rapidly combining high-performance computing platforms and best practices in the cloud to accelerate product development for physical things such as airplanes, cars, chips and medicines.
The big advantage is that companies are increasingly adopting automation approaches from the cloud computing world to make high-end computing more efficient. This dramatically lowers the barriers to testing new ideas, combining multiple simulation techniques and identifying and fixing problems much earlier in the development cycle.
These things have been pillars of business software development. But their adoption in engineering workflows could accelerate the adoption of techniques such as multi-physics simulation, generative design and multimodal AI for the design of physical products. These improvements could fuel the growth of the HPC market to $55 billion by 2024.
“Panoramic companies are actively rethinking the role of supercomputing in a digital age,” Chirag Dekate, VP of analytics for AI infrastructure, digital R&D and emerging technologies at Gartner, told VentureBeat.
HPC platforms or supercomputers have traditionally functioned in a kind of computing niche, outside of the workflows used for other types of business applications. Older HPC management tools were not known for their efficiency or flexibility. Leaders are redesigning HPC applications for clouds to take advantage of advanced cloud capabilities.
Chirag said the long-standing on-premises-only supercomputing delivery model is becoming increasingly untenable. He sees enterprises across all enterprises devising hybrid cloud strategies for supercomputing because of:
High demand for supercomputer skills, resulting in brain drain of the suppliers and end-user organizations. Supply chain challenges for on-premises systems vendors. Delays in maximizing the valuation of the latest technologies. Growing risk of analytics islands in which CAPEX and OPEX intensively decoupled its analysis capabilities at extreme scale from broader enterprise architectures.
Connect the dots
Cloud architectures lower the barrier to developing complex digital twins that combine multiple simulation techniques, such as finite element analysis (FEA), computational fluid dynamics (CFD), and machine learning to take advantage of best price versus time to make the trade-off for a given demand. to solve .
More efficient workflows reduce researchers’ time on non-research tasks, such as finding lost files and setting up infrastructure. It also accelerates the speed of innovation and enables organizations to address broader scientific and technical challenges. Companies that have adopted cloud processes are more than twice as likely to consistently achieve their product goals.
“Giving engineers and scientists easy access to calculations at scale has a measurable impact on the timeliness and success of projects, as well as the scope of their research,” Rescale CPO Edward Hsu told VentureBeat.
This reflects the innovation the cloud brought to software development a decade ago with tools such as CI/CD pipelines for reliably and repeatedly provisioning infrastructure as code. “If you make it harder for developers to use their code, the innovation speed drops,” Hsu said.
Enabling new business models
The real power of the cloud is in the way everything can be connected. “Just as tools like Google Docs have changed the way we collaborate in writing, running all computational engineering workloads from a cloud-based control plane is changing what’s possible,” Hsu said. Examples include automating entire computational pipelines, sharing best practices, simplifying data access and management, or continuously adding to a surrogate model that can be shared and enhanced.
Later on, this could change the way companies create value around physical products. Hsu predicts that companies that take engineering seriously could use computers to improve product designs in the short term and turn the model itself into products in the long term. These represent the definition of the process by which the product works and performs.
Traditionally, engineers only run simulations of things that companies intend to produce. Now they are starting to run simulations before making a design decision. More efficient computing workflows allow them to run simulations to satisfy their curiosity and explore the limits of what’s possible. These models of what is possible can become the intellectual property of the company and provide a source of competitive advantage.
The products shipped are copies of the latest model optimized to solve a particular purpose. A company might say to a customer, “If you change your requirements for this product that much, we can deliver significantly more value to you.”
“Digital twins will be an essential part of this journey into the model that becomes the company’s product, because it is the way we integrate what we perceive in the real world with what we model in the computer room,” Hsu said.
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