High Performance Computing and Bioinformatics
Dr. Reneta P. Barneva, State University of New York, Fredonia.
The significant increase of biological data observed in recent years made it possible to attack a broad spectrum of problems, from evolution of species to invention of new medicines. Most of the biological applications require high-performance computing to handle the huge run-time and memory requirements arising from the inherent complexity of biological problems, the large size of biological data sets, and the need to handle error-prone data. The goal of this talk is to introduce some of the computational problems in biology and to discuss how they can be solved with high-performance computing.
Sequence Alignment in Molecular Biology
Dr. Valentin Brimkov, State University of New York College at Buffalo
In recent decades molecular biology is appearing as one of the major sources for challenging computational problems of significant scientific and practical importance. In this regard, it is becoming increasingly crucial to develop relevant computational tools for manipulating and analyzing large sets of biosequences. In particular, for the sake of inferring common ancestry, detecting functional equivalence, or for the purposes of discovering similar elements in a database, biosequences are compared or aligned in various fashions. In this talk we will briefly consider some basic sequence alignment and comparison problems and will discuss the corresponding methods for their solution.
Practical Issues in Implementing High Performance Computing in Chemistry
Dr. Clyde Metz, College of Charleston
Dr. Shawn Sendlinger, North Carolina Central University
In the recent past, computational chemistry was performed by experts using supercomputers. The combination of new software and powerful hardware has now made computation available to all chemists. A variety of choices now confront chemists who wish to expand their use of computation in educational and research endeavors. Individual or site-licensed copies of computational chemistry software can be placed on faculty machines and in student computer labs. The performance of such software will depend on the processor speed and available memory of the machines. Someone must also be responsible for maintaining the license and loading program updates. Software and hardware costs can also present a barrier. While free software is available, it can be difficult to load and maintain and sometimes has ease-of-use concerns.
An attractive alternative is to use server-based software. Products such as WebMO provide a front-end for a variety of computational chemistry programs, and the simple user interface often makes the programs more user-friendly. If a server is available, free software can be downloaded to make this approach a cost-effective option for chemists to begin using computation in education and research.
Examples of site-licensed versus server-based software will be discussed along with basic hardware requirements. A “live” demonstration of server-based software will also be presented.
High Performance Computing and Theoretical Models in Chemistry
Dr. Shawn Sendlinger, North Carolina Central University
Dr. Clyde Metz, College of Charleston
The availability of high performance computing hardware and software has made computational chemistry an important tool in chemical education. For the student, the use of this tool in lectures, laboratories, recitation periods, POGIL sessions, or in homework assignments aids in improved visualization of concepts, the inclusion of new topics, additional individual study, or the ability to perform interactive “what if” experiments.
Computational Chemistry Education may be considered in two different ways. The simplest approach–Computational (Chemistry Education)–is the use of technology to teach chemical concepts. Typically, readily available software is used for interactive sessions, simulation of instruments or data, modeling a concept, or for demonstrations. The second approach–(Computational Chemistry) Education–involves teaching computational tools such as spreadsheet or other mathematical software, molecular and mathematical modeling software, and programming to learn chemistry.
Several examples of Computational Chemistry Education software and their suggested use in the curriculum will be illustrated.
Computational Physics, Accuracy and Efficiency
Dr. Matt Jones, Center for Computational Research, University at Buffalo
Physicists like to think in terms of scales - differing length, time, and energy scales divide physics as a discipline into its
various subfields and specialties. Similarly, the approximations used in both theoretical and computational methodologies
often trade accuracy for speed and efficiency of solution. Ever-increasing amounts of computational power have been
applied to the solution of various problems in the physical sciences, to the point where researchers now routinely harness
together hundreds or thousands of individual computers to solve larger systems with greater accuracy than ever before.
Given such computational tools, what can we hope to achieve in modeling real physical systems?
In this talk I will present results ranging from fast, interpolative tight-binding methods to highly accurate,
much more computationally demanding quantum Monte Carlo methods, and use them as case studies for some of the
computational challenges posed by atomic, molecular, and solid-state modeling.
Materials properties from first-principles
Dr. Peihong Zhang, University at Buffalo
The past few decades have witnessed dramatic progress in our ability to explain and predict various properties of materials knowing only the identities of their constituent atoms. This progress has been driven mainly by two important factors, namely, the availability of ever-increasing computer speed and advances in theoretical/computational methods, which have made computer simulation another branch of scientific research, in addition to the traditional theoretical and experimental approaches to doing science. In this talk, I will give an overview of modern electronic structure techniques and their application to the understanding of materials properties.
