2020 Rice Oil & Gas HPC Conference

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While foundries bravely drive forward to overcome the technical and economic challenges posed by scaling to 5nm and beyond, Moore’s law alone can provide only a fraction of the performance / watt and performance / dollar gains needed to satisfy the demands of today’s high performance computing and artificial intelligence applications. To close the gap, multiple strategies are required. First, new levels of innovation and design efficiency will supplement technology gains to continue to deliver meaningful improvements in SoC performance. Second, heterogenous compute architectures will create x-factor increases of performance efficiency for the most critical applications. Finally, open software frameworks, APIs, and toolsets will enable broad ecosystems of application level innovation.

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Numerical methods and high-performance computing have rapidly advanced in the past few decades, enabling accurate simulations of complex thermo-fluid systems in many engineering problems. However, faster and higher resolution simulations, particularly for design, optimization, and online control, are of increasing demand, requiring novel approaches to simulating multi-scale, multi-physics, thermo-fluid systems. In the past few years, a number of studies have explored how deep learning might accelerate computational fluid dynamics (CFD). In this talk, I will discuss some of the recent advances in this area, and in particular will present our group’s work on 1) using recurrent neural networks for data-driven integration of some of the computationally demanding equations in a CFD solver, and 2) using transfer learning to improve generalization (i.e., extrapolation) of a deep learning-based CFD solver. Examples from a multi-scale Lorenz system and plans for future applications to pipe flows and Rayleigh-Benard convection will be discussed.

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Collaboration is key to accelerating the growth of Houston’s technology economy. The Ion (4201 Main Street) will anchor the 16-acre South Main Innovation District and is destined to become an epicenter for Houston’s innovation ecosystem as an inclusive, dynamic, vibrant and highly dense hub focusing on quality collaborations between entrepreneurs, incubators, accelerators, corporations and the academic community when it opens in early 2021. In this talk we will outline how the Ion will play an important role, serving the entire ecosystem as a place where those collaborations occur. Houston’s incubators and accelerators, universities, corporations and venture capitalists will have a hub to leverage the innovation taking place all across the Houston region. The 270,000-square-foot building will accommodate multiple uses, including shared workspace, prototyping and maker resources, event space, classrooms, food and beverage offerings as well as indoor/outdoor communal areas with shared amenities.

Intel Capital has invested in technology startups for nearly 30 years, fostering an ecosystem of innovation. Since 1991, Intel Capital has invested US$12.6 billion in more than 1,560 companies worldwide, and 677 portfolio companies have gone public or participated in a merger. This talk will share insights on how Intel helps its portfolio companies succeed.

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Discontinuous Galerkin (DG) methods enable high order accurate time-explicit simulations on domains with complex geometric and interior interfaces. However, DG methods face several challenges: they can lose stability or high order accuracy in the presence of heterogeneous media or complex physics, and they become significantly more expensive as the order of approximation increases. In this talk, we review developments which enable provably stable, high order accurate, and efficient time-explicit simulations for acoustic, acoustic-elastic, and poro-elastic wave propagation in complex geometries and heterogeneous media.

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