Please click here for upcoming seminar information as well as other events going on in ICME.
MONDAY, JANUARY 30, 2017 CME 500: Departmental Seminar Speaker: Paul Ulrich, Assistant Professor of Regional and Global Climate Modeling, Department of Land, Air and Water Resources, UC Davis
Title: Tempest: Software Tools for Addressing the Needs of Next-Generation Climate Science
Abstract: Tempest is a comprehensive simulation-to-science infrastructure that tackles the needs of next-generation, high-resolution, data intensive climate modeling activities. This project incorporates three key components: TempestDynamics, a global modeling framework for experimental numerical methods and high-performance computing; TempestRemap, a toolset for arbitrary-order conservative and consistent remapping between unstructured grids; and TempestExtremes, a suite of detection and characterization tools for objective identification of features in large climate datasets. This work is the foundation for two larger software efforts, namely the development of a global cloud resolving atmospheric model for use on exascale architectures, and the development of a regional climate data evaluation system to meet stakeholder data needs. This presentation will describe the key features of our framework, and discuss a few of the applications where our software is now being used.
Time: 4:30-5:20 p.m.
Location: Hewlett 102
TUESDAY, JANUARY 31, 2017 CME 300: First Year Seminar Series Speaker: Mathhias Ihme, Assistant Professor of Mechanical Engineering, Stanford University
Background: Large-eddy simulation and modeling of turbulent reacting flows, non-premixed flame, aeroacoustics and combustion generated noise, turbulence and fluid dynamics, numerical methods and high-order schemes
Research activities of the Ihme Group focus on the computational modeling of turbulent and chemically reacting flows; particular emphasis is directed towards improving the fundamental understanding of underlying physical processes involving the coupling between turbulence, combustion-chemistry, pollutant formation and noise emission. Our research approach combines classical theoretical analysis tools (including linear stability analysis, rapid distortion theory, and stochastic models), numerical models (such as Reynolds-averaged Navier-Stokes (RANS) formulations and large-eddy simulations (LES)), and the utilization of direct numerical simulation (DNS) results for the development, analysis, and validation of computational models. Current research interests include:
Heat-transfer and boundary layers in internal combustion engines and rocket propulsion systems
Combustion-generated noise and supersonic jet noise
High-order numerical techniques for chemically reacting flows
Development of LES-models for application to kinetics-controlled combustion, including auto-ignition, low-temperature combustion, and combustion-dynamic processes
Characterization of facility-induced non-idealities in rapid-compression engines, shock-tubes, and flow reactors
Time: 12:30-1:20 p.m.
Location: Y2E2-101
THURSDAY, FEBRUARY 2, 2017 CME 510: Linear Algebra and Optimization Seminar Speaker: Dr. Freddie Witherden, Postdoctoral Scholar, Aeronautics and Astronautics, Stanford University
Title: PyFR: A high-order flux reconstruction solver
Abstract: High-order numerical methods for unstructured grids combine the superior accuracy of high-order spectral or finite difference methods with the geometrical flexibility of low-order finite volume or finite element schemes. The Flux Reconstruction (FR) approach unifies various high-order schemes for unstructured grids within a single framework. Additionally, the FR approach exhibits a significant degree of element locality, and is thus able to run efficiently on modern many-core hardware platforms such as GPUs. The aforementioned properties of FR mean it offers a promising route to performing affordable, and hence industrially relevant, scale-resolving simulations of hitherto intractable unsteady flows within the vicinity of real-world engineering geometries.
We will present PyFR an open-source, Python-based framework for solving advection-diffusion type problems using the FR approach. The framework is designed to target a range of hardware platforms via use of a domain-specific language. With this, PyFR is able to solve the compressible Euler and Navier-Stokes equations on grids of quadrilateral and triangular elements in 2D, and hexahedral, tetrahedral, prismatic, and pyramidal elements in 3D, targeting clusters of multi-core CPUs, NVIDIA GPUs, AMD GPUs, Intel Xeon Phis, and heterogeneous mixtures thereof. Results will be presented for various benchmark and real-world flow problems, and scalability/performance of PyFR will be demonstrated on clusters with thousands of NVIDIA GPUs. The importance of algorithm- software-hardware co-design, in the context of next-generation computational fluid dynamics, will be highlighted throughout.
Bio: Freddie Witherden studied Physics with Theoretical Physics at Imperial College London between 2008-2012, earning an MSci degree with first class honours. In September 2012 Freddie started a PhD in computational fluid dynamics in the Department of Aeronautics at Imperial College London under the supervision of Dr. Peter Vincent and graduated in December 2015. Early in 2016 Freddie started a postdoctoral appointment in the Department of Aeronautics and Astronautics at Stanford University under the supervision of Prof. Antony Jameson. Freddie's main research interests are in the development of novel approaches to the simulation of hitherto intractable flow problems at extreme scale.
Time: 4:30-5:30 p.m.
Location: Y2E2-101
OTHER ICME RELATED SEMINARS: Applied Math Seminar Tuesday, January 31, 2017 Speaker: Pablo Parrilo, MIT
Title: Graph Structure in Polynomial Systems: Chordal Networks
Abstract: The sparsity structure of a system of polynomial equations or an optimization problem can be naturally described by a graph summarizing the interactions among the decision variables. It is natural to wonder whether the structure of this graph might help in computational algebraic geometry tasks (e.g., in solving the system). In this talk we will provide an introduction to this area, focused on the key notions of chordality and treewidth, which are of great importance in related areas such as numerical linear algebra, database theory, constraint satisfaction, and graphical models. In particular, we will discuss “chordal networks”, a novel representation of structured polynomial systems that provides a computationally convenient decomposition of a polynomial ideal into simpler (triangular) polynomial sets, while maintaining its underlying graphical structure. As we will illustrate through examples from different application domains, algorithms based on chordal networks can significantly outperform existing techniques. Based on joint work with Diego Cifuentes (MIT).
Time: 3:00 p.m.
Location: 380-380C
Wednesday, February 1, 2017 Speaker: David Stork, Rambus Labs
Title: Ultra-miniature lensless computational imagers and sensors: Using optics for computing and computing for optics
Abstract: We describe a new class of computational optical sensors and imagers that do not rely on traditional refractive or reflective focusing but instead on special diffractive optical elements integrated with CMOS photodiode arrays. The diffractive elements have provably optimal optical properties essential for imaging, and act as a visual chirp and preserve full Fourier image information on the photodiode arrays. Images are not captured, as in traditional imaging systems, but rather computed from raw photodiode signals. Because such imagers forgo the use of lenses, they can be made unprecedentedly small—as small as the cross-section of a human hair. Such imagers have extended depth of field, from roughly 1mm to infinity, and should find use in numerous applications, from endoscopy to infra-red and surveillance imaging and more. Furthermore, the gratings and signal processing can be tailored to specific applications from visual motion estimation to barcode reading and others.
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