Fast and accurate GPU-based CAE software is possible, according to M-Star and the pharmaceutical industry.The CAE industry has had a lot of overarching goals over the last decade. Though not an exhaustive list, two that often come up are:
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Notes on Computational Fluid Dynamics (CFD) was written for people who use CFD in their work, research or study, providing essential knowledge to perform CFD analysis with confidence. It offers a modern perspective on CFD with the finite volume method, as implemented in OpenFOAM and other popular general-purpose CFD software.
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A new solver algorithm for the MPAS-Ocean model significantly enhances climate research by reducing computational time and improving accuracy. This breakthrough, integrating Fortran and C++ programming, is a step forward in efficient and reliable climate modeling.
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Working as part of a multi-disciplinary team, you will support the Principal Investigator in delivery of research activity on the implementation of Artificial Intelligence and Machine Learning techniques to develop ground-breaking computational tools for modelling coastal flooding.
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The new Simcenter FLOEFD 2312 software release from Siemens enhances CAD-embedded computational fluid dynamics to shorten preprocessing activities, accelerate electronics thermal design workflows, while adding new capabilities for structural analysis, and an improved Application Programming Interface (API) for simulation automation, the company reports.
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Classiq, the leader in quantum software, today announced that it is working with Rolls-Royce to implement novel computational fluid dynamics algorithms. Computational fluid dynamics (CFD) deals with heavy, and complex numerical simulations of fluid and gas phenomena.
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There are certain workloads where the M1 Ultra truly excels. Hit one, and it’s game over for current x86 platforms. It’s surprisingly hard to pin down exactly how Apple’s M1 compares to Intel’s x86 processors. While the chip family has been widely reviewed in a number of common consumer applications, inevitable differences between macOS and Windows, the impact of emulation, and varying degrees of optimization between x86 and M1 all make precise measurement more difficult.
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A decade ago, waferscale architectures were dismissed as impractical. Five years ago, they were touted as a fringe possibility for AI/ML. But the next decade might demonstrate waferscale as one of only a few bridges across the post-Moore’s Law divide, at least for some applications. Luckily for the only maker of such a system, Cerebras, those areas are among the most high-value workloads in large industry.
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