Program for Research in Computing and Information Sciences and Engineering

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CISE Technical Lecture Series

CISE -TLS: August - December 2003

CISE Lecture I - Dr. Nayda G. Santiago Santiago August 28, 2002

Evaluating Performance Information for Mapping Algorithms to Advanced Architectures    
The development of efficient code for scientific and engineering applications on advanced computing systems is not a trivial task. To accomplish this task, a code developer has to be concerned not only about algorithmic correctness and robustness, but also about performance and implementation details. These additional factors impose a burden on the typical scientific computing expert, preventing the user from effectively leveraging the computational resources available to the application. Two major factors can be identified among those making this task particularly difficult. First, the complex interactions between the target platform and the application software tend to hide information about the existing relations between different entities in the system. Second, the high dimensionality of the performance data conceals interesting patterns in the observations which could lead to insights into the system behavior. While a multiplicity of tools have been developed to solve these problems, many obstacles still exist when characterizing the relations among high-level factors and low-level performance information. These problems not only make difficult the task of efficient coding, but also prevent the development of automated performance analysis tools to assist application programmers to tune their code.   In this presentation we will present a new methodology for obtaining information about the relations emerging when compute-intensive applications are mapped onto advanced architectures. The proposed methodology incorporates knowledge and techniques from multiple areas that include statistics, operational research, pattern recognition, data mining, and performance evaluation to enable the extraction of performance information during the mapping process. The methodology is composed of four steps: problem analysis, design of experiments, data collection, and data analysis. In the first two steps, analyses of the application itself are completed to determine the appropriate design of experiments for establishing relations between changes in high-level abstractions and performance outcomes. Feature subset selection is proposed for identifying important system metrics. An evaluation of different statistical analysis alternatives was carried out to characterize the types of data obtained in performance studies. The information obtained from this methodology can be converted into appropriate suggestions, observations, and guidelines for the scientific computing expert to tune applications to a particular computing system.

CISE Lecture II -Dr. Bienvenido Vélez

November 6, 2003

Elastically Replicated Information Services (ERIS)
Elastically Replicated Information Services (ERIS) use adaptive replication algorithms in order to sustain a desired level of data availability even in the presence of online changes to the topology of a distributed storage system. In this talk we first argue for the need to achieve a dynamic balance among data replication and data migration in order to sustain a desired level of availability while maximizing storage utilization. The talk will also illustrate the inherent trade off between utilization and availability in distributed storage systems and introduces a simple mathematical model of a distributed storage cluster (DSC). Preliminary results from simulations of different elastic replication algorithms using this DSC model suggest that ERIS are desirable even in small scale DSC's (order of ten storage nodes). Our initial empirical results provide an early indication of a practical need for elastic replication algorithms.

CISE Lecture II -Dr. Hugh B. Nicholas Jr.

November 20, 2003

Predicting the Determinants of Enzyme Specificity: Combining Biology, Mathematics, and Computer Science in Molecular Biological Research.
Present day biological organisms possess many homologous gene families (i.e., gene families that share a common evolutionary ancestor) that encode proteins that carry out similar but distinct biochemistry and participate in different physiological processes. These different proteins frequently function in the same cellular environment. Thus, the protein (and gene) sequence must encode the information that allows molecules to participate in the processes and pathways to which they are specific and to also avoid participating in "incorrect" processes and pathways. I will present analyses that identify the residues in biological macromolecules that are most likely to confer the specificity of interaction described above. The talk will first describe the analyses in terms the essential biochemical and biological properties of the molecular systems being studied and then discuss encapsulating this biological knowledge into formal mathematical models of the biological system. Finally, the mathematical model into a computer algorithm, and program, that calculates how closely specific biological sequence data conforms to this model. The talk will describe applying the analysis to macromolecular families and will look at how well these computational predictions match experimental results addressing the same biological questions. I will conclude by outlining some open mathematical and computational questions related to the analysis.


CISE Technical Lecture Series - SPECIAL EDITION September 4, 2003   Dr. John Rodriguez

Silicon Technology Development - Texas Instruments

Reliability Aspects of Ferroelectric Memories
A low cost, low power, non-volatile memory technology is required for many applications. One promising candidate utilizes the ferroelectric material PZT. Ferroelectric films can be polarized in either of two stable states and the polarization remains even when the writing voltage is removed, making ferroelectric memories non-volatile. In addition, ferroelectric memories can operate at low voltages, making them attractive candidates for integration with state of the art CMOS processes. In this talk, we will briefly review the basics relevant to ferroelectric memories, including electrical characterization. The two primary reliability concerns for FRAM are fatigue due to bipolar cycling and data retention. We will describe these effects and highlight progress achieved in improving the reliability of these films.



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