Stanford University

ERE Seminar: Karthik Mukundakrishnan, PhD, Stone Ridge Technology — High Fidelity Numerical Simulations of Transport Processes: Perspectives and Challenges

When:
Monday, Nov 26, 2018 12:30 PM
Where:
Room 104, Green Earth Sciences Building, 367 Panama Street, Stanford
More Info:
ERE Seminar: Karthik Mukundakrishnan, PhD, Stone Ridge Technology — High Fid…
Audience:
General Public, Faculty/Staff, Students, Alumni/Friends, Members
Sponsor:
Energy Resources Engineering

Title
High Fidelity Numerical Simulations of Transport Processes: Perspectives and Challenges

Karthik Mukundakrishnan, PhD
Director of Research and Development | Stone Ridge Technology

Abstract
High performance computing (HPC) has become a critical tool for industries seeking solutions to complex engineering and physical problems. While the problems and underlying governing equations describing the transport physics have not changed in decades, higher fidelity simulations have pushed the boundaries of computational science. The machines employed for computations have undergone a radical transformation. In the previous decades, computing was dominated by single-core hardware. Each generation of silicon process technology offered greater clock speeds, and hence, scientific codes which were mostly compute bound, simply ran faster without any modifications. However, power constraints, especially heat dissipation, led to a plateauing of clock speeds around the mid 2000’s. Consequently, with the advent of modern many-core and multi-core processors such as GPUs, the primary way to achieve performance gains has been through parallelism. A large and diverse collection of scientific software applications that are widely used in academia, national labs, and industry now face enormous challenges in catching up with this paradigm shift in the hardware landscape. Today’s HPC practitioners are faced not only with complex multi-level parallelism but also massive parallelism available on architectures such as GPUs. This presents both challenges and great opportunity. In this talk, I will discuss some of the unique algorithmic, computational and engineering challenges involved in developing an engineering simulator by efficiently utilizing the parallelism offered by  GPUs. As an example, one computational challenge is to consider parallelism from the earliest stages of application design for maximal performance and not as an afterthought as is done more commonly. Performance results from high fidelity reservoir simulations of synthetic and real-field assets will also be presented.

Bio
Dr. Mukundakrishnan is currently the Director of Research and Development at Stone Ridge Technology which develops and markets ECHELON, a high performance commercial reservoir simulator built and optimized from inception for GPUs and massive fine-grained parallelism. Prior to joining Stone Ridge Technology, he was a R&D Technology Manager at Dassault Systemes Simulia (formerly ABAQUS Inc.) where he was a lead developer for Simulia CFD, a commercial finite volume multiphysics moving-mesh flow solver. Dr. Mukundakrishnan obtained his Ph.D. in Applied Mechanics from the University of Pennsylvania working on direct numerical simulations of flow and mass transfer of particulate-laden flows in rotating media using ALE finite element methods. Subsequently, he held a postdoctoral research fellowship at UPenn Medical School working on the direct numerical simulation of gas embolism in circulatory systems using immersed boundary methods. Dr. Mukundakrishnan’s experience includes high performance computing and formulating advanced numerical schemes for solving strongly coupled nonlinear PDEs. Dr. Mukundakrishnan also possess strong software development skills using objected oriented programming languages and has a keen interest in software engineering practices.

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