Theory of Scanning Tunneling Microscopy

This lecture has been given at the 45th Spring School: Computing Solids: Models, Ab-initio Methods and Supercomputing organized at the Forschungszentrum J\"ulich. The goal of this manuscript is to review the basics behind the theory accompanying Scanning Tunneling Microscopy.Comment: 38 pages, 45th IFF Spring School: Computing Solids: Models, Ab-initio Methods and Supercomputing organized at the research center of Juelic

NASA's supercomputing experience

A brief overview of NASA's recent experience in supercomputing is presented from two perspectives: early systems development and advanced supercomputing applications. NASA's role in supercomputing systems development is illustrated by discussion of activities carried out by the Numerical Aerodynamical Simulation Program. Current capabilities in advanced technology applications are illustrated with examples in turbulence physics, aerodynamics, aerothermodynamics, chemistry, and structural mechanics. Capabilities in science applications are illustrated by examples in astrophysics and atmospheric modeling. Future directions and NASA's new High Performance Computing Program are briefly discussed

Cellular automaton supercomputing

Many of the models now used in science and engineering are over a century old. And most of them can be implemented on modern digital computers only with considerable difficulty. Some new basic models are discussed which are much more directly suitable for digital computer simulation. The fundamental principle is that the models considered herein are as suitable as possible for implementation on digital computers. It is then a matter of scientific analysis to determine whether such models can reproduce the behavior seen in physical and other systems. Such analysis was carried out in several cases, and the results are very encouraging

Enhancing Research

UNLV’s National Supercomputing Center provides research support

The Green500 List: Escapades to Exascale

Energy efficiency is now a top priority. The first four years of the Green500 have seen the importance of en- ergy efficiency in supercomputing grow from an afterthought to the forefront of innovation as we near a point where sys- tems will be forced to stop drawing more power. Even so, the landscape of efficiency in supercomputing continues to shift, with new trends emerging, and unexpected shifts in previous predictions. This paper offers an in-depth analysis of the new and shifting trends in the Green500. In addition, the analysis of- fers early indications of the track we are taking toward exas- cale, and what an exascale machine in 2018 is likely to look like. Lastly, we discuss the new efforts and collaborations toward designing and establishing better metrics, method- ologies and workloads for the measurement and analysis of energy-efficient supercomputing

Advanced Architectures for Astrophysical Supercomputing

Astronomers have come to rely on the increasing performance of computers to reduce, analyze, simulate and visualize their data. In this environment, faster computation can mean more science outcomes or the opening up of new parameter spaces for investigation. If we are to avoid major issues when implementing codes on advanced architectures, it is important that we have a solid understanding of our algorithms. A recent addition to the high-performance computing scene that highlights this point is the graphics processing unit (GPU). The hardware originally designed for speeding-up graphics rendering in video games is now achieving speed-ups of $O(100\times)$ in general-purpose computation -- performance that cannot be ignored. We are using a generalized approach, based on the analysis of astronomy algorithms, to identify the optimal problem-types and techniques for taking advantage of both current GPU hardware and future developments in computing architectures.Comment: 4 pages, 1 figure, to appear in the proceedings of ADASS XIX, Oct 4-8 2009, Sapporo, Japan (ASP Conf. Series

A Survey of Fault-Tolerance and Fault-Recovery Techniques in Parallel Systems

Supercomputing systems today often come in the form of large numbers of commodity systems linked together into a computing cluster. These systems, like any distributed system, can have large numbers of independent hardware components cooperating or collaborating on a computation. Unfortunately, any of this vast number of components can fail at any time, resulting in potentially erroneous output. In order to improve the robustness of supercomputing applications in the presence of failures, many techniques have been developed to provide resilience to these kinds of system faults. This survey provides an overview of these various fault-tolerance techniques.Comment: 11 page