March 28, 2017 from 12-1pm in PGH 216
Presenter: R. Stan Williams, Quantum Science Research Laboratory at Hewlett-Packard
With the end of Moore’s Law in sight, there is a great deal of angst in the information technology community over how computing can keep pace now that data is being generated and accumulated at an exponential rate. One solution is to perform exponentially more computation per unit of energy expended in a computer. This may very well require the exploitation of nonlinear dynamical systems to encode and process information in unconventional ways. Both nanoscale structures and neurons can display pathologically nonlinear responses such as chaos to a small stimulus, and in many ways the former can be used to emulate the latter. After a brief introduction to a couple of nonlinear electronic devices, i.e. passive or synaptic memristors and locally active or axonic memristors, I will describe the electronic and physical characterization tools and techniques that we have developed to characterize these systems. Standard electronic test and measurement systems are largely incapable of providing the appropriate time and/or frequency dependent information required to quantitatively characterize and model memristors. We have built flexible high-speed systems that enable us to watch the electronic switching in highly nonlinear systems in real-time from 10’s of picoseconds to minutes. This type of data is critical to construct compact models for both the switching and the reliability of dynamical devices. We base our models, as much as possible, on the actual physical mechanisms that occur inside the devices as they operate. For this purpose, we have worked with both the Advanced Light Source at LBNL and the Stanford Synchrotron Radiation Laboratory to utilize the technique of Scanning Transmission X-ray Microscopy to examine functioning memristors in situ and in operando under controlled temperature and electrical bias conditions. We have imaged the structure and chemical composition of different conductance states of devices in order to determine what and how atoms move inside solid state devices as they are switching electrically under an external bias, whether that switching occurs via a phase transition or through drift, diffusion and thermophoresis of atomic species like oxygen. The electrical and mechanistic information come together in the compact device models that we supply to circuit architects so that they can faithfully and predictively simulate a wide range of circuits before they commit to a design that will be fabricated.
The Center for Advanced Computing and Data Systems will be hosting a seminar that will be given by Dr. Uwe Woessner in PGH 216 from 12-1 p.m. on April 6, 2017.
Virtual environments provide an ideal environment for engineering teams or research groups to analyze and discuss complex simulation results. Not only the 3D vision and surround view but most important the intuitive interaction with the data enable an efficient analysis and communication of simulation results. Collaborative virtual environments provide similar functionality but extend the reach to remote sites and Augmented Reality allows a direct comparison of simulation results with live experiments. All these technologies will be presented by means of examples from engineering, forensics, urban planning and more.
About the Presenter:
Since 2004, Uwe Woessner is heading the visualization department at the High Performance Computing Center Stuttgart (HLRS).
He received his PhD. in Mechanical Engineering from the University of Stuttgart in 2009. Since 1996 he is working in the Collaborative Research Center “Rapid Prototyping” established at the University of Stuttgart in the field of VR based virtual and augmented prototyping. He is guest professor and guest lecturer at the IFOER and ITE, TU-Vienna, Austria and at HSR, Rapperswil, Switzerland. He is also Co-founder of VirCinity GmbH.
He received international Awards such as the 2003 HPC Challenge and 2006 HPC Bandwidth Challenge.
His current research interests include collaborative virtual environments for scientific visualization, Augmented Reality, 3D user interfaces and interaction techniques for computational steering.
He is in the committee of several VR and 3D User Interface related conferences such as IEEE VR, IEEE Vis, EuroVR, GI VRAR.
The Journal of Geophysical Research has published an article that features Center for Advanced Computing and Data Systems support and resources. The article details Remote sensing evidence of decadal changes in major tropospheric ozone precursors over East Asia. The research outlined in the article was, in part, obtained by using the Opuntia Cluster and advanced CACDS support.
The paper’s abstract explains the research that was completed:
Recent regulatory policies in East Asia reduce ozone precursors, but these changes are spatially and temporally nonuniform. This study investigates variations in the long-term trends of tropospheric NO2, HCHO, and HCHO/NO2 ratios to diagnose ozone sensitivity to changes in NOx and volatile organic compound using the Ozone Monitoring Instrument (OMI). Using an adaptive-degree polynomial filter, we identify extremums of time series of NO2 to determine when and how NO2 change. Due to the regulations in China, trends which were predominantly upward turned downward. The years undergoing these changes primarily happened in 2011 and 2012. OMI column densities, however, suggest that NOxsources in South Korea, the Pearl River Delta (PRD), Taiwan, and Japan have not consistently decreased. Specifically, as Chinese exports of NO2 started subsiding, increasing trends in NO2 columns over several Korean cities, including Seoul, become evident. To quantify the changes in NOx emissions from summertime 2010 to 2014, we conduct a 3D-Var inverse modeling using a regional model with MIX-Asia inventory and estimate NOx emissions (in 2010 and 2014) for the PRD (1.6 and 1.5 Gg/d), the Yangtze River Delta (3.9 and 3.0 Gg/d), north China (15.6 and 14.3 Gg/d), South Korea (1.6 and 1.5 Gg/d), and Japan (2.7 and 2.6 Gg/d). OMI HCHO shows upward trends in East Asia resulting from anthropogenic effects; however, the magnitudes are negative in the PRD, Japan, North Korea, and Taiwan. OMI HCHO/NO2 ratios reveal that while South Korea, Japan, and the south of China have undergone toward more NOx-sensitive regime, areas around the Bohai Sea have become more NOx saturated.
The full text can be found by visiting: http://onlinelibrary.wiley.com/doi/10.1002/2016JD025663/full
Date: March 3, 2017
Place: Agnes Arnold Hall Room 104
Time: 12:30pm – 6:00pm
RSVP: Valeria Gonzalez (firstname.lastname@example.org) by Feb. 27
The College of Liberal Arts and Social Sciences in collaboration with faculty from the Center for Advanced Computing and Data Systems is sponsoring a workshop in the Digital Humanities and Social Sciences. The workshop will explore the scope and variety of projects in the Digital Humanities and Social Sciences. There will be presentations from Dr. Claude Willan, an exciting young scholar and research associate at Princeton University’s Center for Digital Humanities and also from University of Houston faculty and librarians and from the Executive Director for Digital Scholarship Service at the Fondren Library at Rice University. Distinguished Professor Andrea Prosperetti from the Center for Advanced Computing and Data Systems will speak briefly about resources available at UH for those interested in research in Digital Humanities and Social Sciences. The workshop is open to all faculty and graduate students at the University of Houston.
There will be three sessions and we will provide a lunch. There will be a social hour following the workshop. Please see the attached schedule of the events of the day.
Digital research is an important new area of inquiry. This workshop will show the types of projects informed by digital research and will publicize what resources are available at UH for those interested in pursuing this scholarship.
We hope to see you on March 3 in Agnes Arnold 104
-The steering committee for the Digital Humanities
The Center for Advanced Computing and Data Systems is now offering free Accelerator Programming courses to UH faculty/staff during this semester!
February 21: OpenACC Programming Part 1
February 24: OpenACC Programming Part 2
March 3: GPGPU Parallel Programming with CUDA Part 1
March 7: GPGPU Parallel Programming with CUDA Part 2
The Center for Advanced Computing and Data Systems is now offering free Visualization courses at UH for all faculty and staff during the current semester!
January 24: Visualization with VISIT Part 1
January 27: Visualization with VISIT Part 2
January 31: Visualization with Paraview Part 1
February 3: Visualization with Paraview Part 2
The Center for Advanced Computing and Data Systems is offering free introductory courses for High Performance Computing to UH faculty/staff this semester!
January 20: Intro to Shell Programming
January 27: Intro to Shell Programming
January 31: Intro to Cluster Computing
April 11: Intro to Shell Programming
April 14: Intro to Cluster Computing
The Center for Advanced Computing and Data Systems is now offering free Machine Learning courses to all faculty/students at UH during the current semester!
February 13: Intro to Machine Learning
February 15: Intro to Deep Learning
March 21: Intro to Machine Learning
March 24: Intro to Deep Learning
UH’s Center for Advanced Computing and Data Systems is currently offering FREE Parallel Computing classes to all UH students, faculty, and staff this semester.
January 19: Parallel Programming with MPI Part I
January 26: Parallel Programming with MPI Part II
February 6: Parallel Programming with OpenMP Part I
February 8: Parallel Programming with OpenMP Part II
February 23: Parallel Programming with R
March 2: Parallel Programming with MPI Part I
March 7: Parallel Programming with MPI Part II
March 21: Parallel Programming with OpenMP Part I
March 24: Parallel Programming with OpenMP Part II
UH’s Center for Advanced Computing and Data Systems is currently offering FREE R Programming classes to all UH students, faculty, and staff this semester.
January 23: Intro to R Part I
January 26: Intro to R Part II
April 25: Intro to R Part I
April 28: Intro to R Part II