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SUNMONTUEWEDTHUFRISAT
Conferences, Lectures, & Seminars
Events for June
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An Introduction to the PowerPro(TM) Tool
Wed, Jun 06, 2007 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Aiguo Xie, Calypto Design Systems, Santa Clara, CAAbstract: PowerPro is our latest CAD product. It helps build better system and RTL designs by lowering their power consumption. In this talk, we will review its key technology, including reliable prototyping, sequential transformation, and verification. We will also discuss its future challenges.Brief Bio: Aiguo is a former EE-Systems Ph.D. student of Prof. Peter A. Beerel. He is an architect of Calypto Design Systems (2003-), responsible for the technology of the PowerPro product in all area. He was a chip architecture designer of Fulcrum Microsystems (2001-2003), and a synthesis tool developer of Cadence Design Systems (1999-2001).Hosted by Prof. Peter Beerel
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
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Charting the Dynamics of Neurocognitive Networks
Wed, Jun 06, 2007 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Steven L. Bressler, Ph.D.
Professor, Center for Complex Systems & Brain Sciences, Florida Atlantic UniversityAbstract:
There has long been a dichotomy in understanding higher-order functions of the cerebral cortex. The localizationist tradition has sought to identify such functions with specific cortical areas, whereas the globalist tradition has viewed all higher-order functions as emerging from the cerebral cortex as a whole. A reconciliation of these opposing viewpoints has come with the growing realization that neurocognitive networks are of central importance to cortical function. Neurocognitive networks are composed of distributed neuronal assemblies in the cortex and sub cortical structures that dynamically engage in cooperative interactions to accomplish specific cognitive operations. A major challenge for cognitive neuroscience is to develop analytic tools for the precise characterization of the dynamics of neurocognitive networks. I will describe an approach to this characterization based on the construction of network graphs derived from autoregressive time series analysis of cortical population activity. I will also present experimental evidence from non-human primates and humans that this approach provides useful insights into the neural basis of cognitive function.Location: Olin Hall of Engineering (OHE) - 100C (Studio C)
Audiences: Everyone Is Invited
Contact: Talyia Veal
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Application of Functional Genomics to Improve Chlorinated Ethane ....
Mon, Jun 11, 2007 @ 02:00 PM - 03:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Application of Functional Genomics to Improve Chlorinated Ethene Bioremediation ProcessesSpeaker:David R. Johnson,
Department of Civil and Environmental Engineering,
University of California, BerkeleyAbstractChlorinated ethenes are among the most prevalent contaminants of groundwater resources and pose a significant threat to human and ecological health. Remediating these resources with traditional pump-and-treat strategies is both technically challenging and costly. Fortunately, strategies that utilize natural microorganisms to degrade these pollutants in situ have now been developed and applied with success. Of particular interest is to utilize members of the Dehalococcoides group of bacteria because they are the only known organisms that can completely degrade fully chlorinated ethenes to non-toxic end products. Although significant progress has been made, there is now a need for effective methods to both optimize and monitor the performance of Dehalococcoides-based bioremediation systems.
To begin to address these needs, this research applied functional genomics tools to improve our understanding of Dehalococcoides ethenogenes strain 195. Specifically, transcriptomics were analyzed by whole-genome microarrays while proteomics were analyzed by liquid chromatography coupled with tandem mass spectrometry. These tools were applied during periods of maximal and repressed activity in order to identify factors that can potentially limit dechlorination. This approach successfully identified cobalamin (vitamin B12) as a key factor controlling dechlorination activity and revealed novel strategies for minimizing cobalamin deficiencies within bioremediation systems. In addition, these studies identified mRNA and peptide biomarkers that could be used to quantitatively assess the physiological state of strain 195 within uncharacterized systems.
The results of this research demonstrate that functional genomics can dramatically accelerate our understanding of reductive dechlorinating bacteria important for bioremediation applications. There is now a need for more collaborative efforts between the fields of genome sciences and environmental problems.
Location: Kaprielian Hall (KAP) - rielian Hall, 203
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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A Methodology for Creating Application Specific Processor Architectures
Mon, Jun 11, 2007 @ 02:30 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
*Professor Kumar will be available 4-5pm in EEB-248 to talk to PhD students from any engineering department interested in faculty positions at IIT Delhi.Abstract:
Performance improvement through datapath extensions with Application Specific Functional Units has been a subject of research for more than a decade now. However, we feel that full potential of this approach has not been exploited due to several obstacles. This talk presents techniques to get past some of these obstacles.Usually a cluster of operations identified from the application defines a new custom instruction and forms the behavior of an Application Specific Functional Unit that implements this instruction. In the techniques available for identifying such clusters, the number of register file ports constrains the number of inputs and outputs for a legal operation cluster, thus limiting the overall achievable speedup. We present a technique that circumvents the constraints imposed by register file ports and results in a significantly higher speed up. In addition, our identification algorithm runs 2 to 3 orders faster than a typical I/O constrained identification approach.The second issue we take up here is estimation of the speedup achievable for the clusters identified. In order to select the right clusters, we need to correctly estimate the speedup taking into account what we call as temporal and spatial reuse of the clusters. In absence of efficient techniques to do so, researchers compromise either on the quality of estimates or on the number of clusters examined. We propose a novel method by which each cluster’s reuse information can be derived very efficiently, making it possible to generate high quality custom instructions.Bio:
Anshul Kumar is currently a Professor of Computer Science and Engineering at IIT Delhi. He obtained his B.Tech. and Ph.D. degrees from IIT Delhi in the years 1974 and 1980 respectively and was awarded the President's Gold Medal in 1974. He has been involved in teaching and research at IIT Delhi for more than 20 years in the areas of VLSI synthesis, embedded systems and high performance computer architectures and has published or presented nearly hundred papers. He has held visiting appointments at Univ of Southern California Los Angeles, University of Edinburgh, KTH Stockholm and EPFL Laussane. Along with some colleagues and graduating students of his department, he recently founded a company called Kritikal Solutions under the Technology Business Incubation Program of IIT Delhi.Host: Prof. Sandeep Gupta, Ext. 02251Location: Hughes Aircraft Electrical Engineering Center (EEB) - -248
Audiences: Everyone Is Invited
Contact: Aimee Barnard
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Electro-Thermal Interaction in Nanoscale Devices: Carbon Nanotubes and Phase-Change Memory
Fri, Jun 15, 2007 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Nanotechnology Seminar:Electro-Thermal Interaction in Nanoscale Devices:Carbon Nanotubes and Phase-Change MemoryEric PopAssistant Professor
Department of Electrical Engineering
University of Illinois at Urbana-Champaign (UIUC)AbstractRising power densities are often considered the ultimate roadblock in the evolution of nanoelectronics. From a device perspective, high power densities in small volumes are complicated by reduced thermal conductance, and the thermal impedance of material interfaces. This talk will focus on two relatively novel devices, carbon nanotubes and phase-change memory, where the electro-thermal interaction is particularly strong. Singlewall carbon nanotubes exhibit significant self-heating, showing negative differential conductance, light emission and ultimately burning in air at high bias. Phase-change memory must, by design, have high and localized power density during operation, since the state of the bit is altered thermally. Simple experiments are used to gain new insight into the Fundamental behavior of both device types. This work suggests much room for the optimization of nanoscale devices through geometry, interface and materials design. Location: Olin Hall (OHE) 122
Time: 11am - noon, Friday, June 15, 2007
Hosted by Professor Chongwu Zhou (213 740 04708)Location: Olin Hall (OHE) 122
Audiences: Everyone Is Invited
Contact: Ericka Lieberknecht
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Inversion of probabilistic models of structures using measured transfer functions
Fri, Jun 22, 2007 @ 12:30 PM - 02:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker:
Maarten Arnst
Department of Civil and Environmental Engineering,
University of Southern California,
3620SVermontAvenue, KAP130,
phone: (213) 740-9165,
mail: arnst@usc.eduAbstract:
Predictive models for the dynamical behavior of complex structures are inevitably confronted to data uncertainties and modeling errors. Uncertain data include material properties, geometric parameters and boundary conditions. Modeling errors are introduced by the assumptions and approximations made in the modeling process. The data uncertainties and modeling errors may sometimes result in significant uncertainties in the model predictions. Probabilistic models then are desirable, since theyprovide a way to quantify the impact of the data uncertainties and modeling errors on the predictions.
Probabilistic mechanics is nowadays a rich and well-developed domain of research, in which a wide variety of methods for constructing probabilistic structural models has been proposed, see e.g. [1, 2, 3, 4]. Compared to deterministic structural models, an important difficulty is that probabilistic models introduce supplementary parameters, e.g. dispersion levels, spatial correlations lengths, or coefficients of chaos decompositions.An active areaof researchis thereforethedevelopmentof methodologies guidingthe choice of these parameters.
This presentation concerns the experimental identification of probabilistic structural models from measured transfer functions. The classical methods of estimation from the theory of mathematical statistics, such as the method of maximum likelihood, see e.g. [5], are not well-adapted to formulate and solve this inverse problem. In particular,numerical difficulties and conceptual problems due to model misspecification prohibit the application of the classical methods. In this talk, we propose to formulate the inversion alternatively as the minimization, with respect to the parameters to be identified, of an objective function measuring a distance between the experimental data and the probabilistic model. Two principles of construction for the definition of this distance are proposed, based on either the loglikelihood function, or the relative entropy, see e.g. [6]. The limitation of the distance to low-order marginal laws is shown to allow circumventing the aforementioned difficulties. The methodology is applied to simple illustrative examples featuring simulated data and to a civil and environmental engineering case history featuring real experimental data.
This work has been performed in the frame of a PhD thesis at Ecole Centrale Paris in France, under the supervision of Dr. Didier Clouteau and Dr. Marc Bonnet. The manuscript can be downloaded from www.mssmat.ecp.fr/rubrique.php3?id rubrique=354.
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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Transition Matrix Methods
Mon, Jun 25, 2007 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
SPEAKER: Professor David Yevick, Department of Physics, University of WaterlooABSTRACT: The transition matrix contains the probabilities that a system will
evolve between any two sets of states in a given time interval. In this
presentation, we demonstrate that techniques similar to the
multicanonical method can be employed to find the elements of the
transition matrix between pairs of rarely occurring states in an optical
communication system. This result is then applied to determine the
probability distribution of outage times resulting from polarization
mode delay (PMD).BIO: David Yevick was born in New York City on May 3, 1954. He received the A B. degree in physics from Harvard University, Cambridge, MA, in 1974,
the M A. and Ph D degrees in physics from Princeton University,
Princeton, NJ, in 1975 and 1977, respectively.Dr. Yevick is a professor at the University of Waterloo, Waterloo, ON,
Canada. He has written more than 160 papers involving the application of
numerical and analytic procedures to optical fibers, integrated optics,
and semiconductor laser modeling and, more recently, optical
communication system analysis. Dr. Yevick is a Fellow of the Optical Society of America (OSA), the IEEE and the American Physical Society (APS).Host: Alan Willner, willner@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 539
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
