David Swanson

Bio: David Swanson is an academic researcher from University of Nebraska–Lincoln. The author has contributed to research in topics: Load balancing (computing) & File system. The author has an hindex of 19, co-authored 82 publications receiving 1309 citations. Previous affiliations of David Swanson include Lincoln University (Pennsylvania).

Separation of chiral phases in monolayer crystals of racemic amphiphiles

Abstract: OPTICAL activity manifested by chiral molecules and crystals is of long-standing interest in physics, chemistry, biology and geology1,2. The structure of chiral lattices in two and three dimensions may provide insights into chiral discrimination, and chiral phases play an important part in the physics and applications of liquid-crystal and amphiphilic films3–7. Here we report the observation of spontaneous separation of chiral phases in an oriented monolayer of rigid, chiral amphiphiles deposited on mica. Atomic force microscopy of the ordered films reveals domains of mirror-image structures. We propose that this may be the signature of separation into domains of pure enantiomers, although other possibilities exist. This separation of chiral phases in two dimensions may be considered analogous to the spontaneous resolution of enantiomers in three-dimensional crystallization, as exploited by Pasteur in 1848 to isolate enantiomers of sodium tartrate1.

Matchmaking: A New MapReduce Scheduling Technique

Abstract: MapReduce is a powerful platform for large-scale data processing. To achieve good performance, a MapReduce scheduler must avoid unnecessary data transmission by enhancing the data locality (placing tasks on nodes that contain their input data). This paper develops a new MapReduce scheduling technique to enhance map task's data locality. We have integrated this technique into Hadoop default FIFO scheduler and Hadoop fair scheduler. To evaluate our technique, we compare not only MapReduce scheduling algorithms with and without our technique but also with an existing data locality enhancement technique (i.e., the delay algorithm developed by Face book). Experimental results show that our technique often leads to the highest data locality rate and the lowest response time for map tasks. Furthermore, unlike the delay algorithm, it does not require an intricate parameter tuning process.

An efficient fault-tolerant scheduling algorithm for real-time tasks with precedence constraints in heterogeneous systems

Abstract: In this paper, we investigate an efficient off-line scheduling algorithm in which real-time tasks with precedence constraints are executed in a heterogeneous environment. It provides more features and capabilities than existing algorithms that schedule only independent tasks in real-time homogeneous systems. In addition, the proposed algorithm takes the heterogeneities of computation, communication and reliability into account, thereby improving the reliability. To provide fault-tolerant capability, the algorithm employs a primary-backup copy scheme that enables the system to tolerate permanent failures in any single processor. In this scheme, a backup copy is allowed to overlap with other backup copies on the same processor, as long as their corresponding primary copies are allocated to different processors. Tasks are judiciously allocated to processors so as to reduce the schedule length as well as the reliability cost, defined to be the product of processor failure rate and task execution time. In addition, the time for detecting and handling a permanent fault is incorporated into the scheduling scheme, thus making the algorithm more practical. To quantify the combined performance of fault-tolerance and schedulability, the performability measure is introduced Compared with the existing scheduling algorithms in the literature, our scheduling algorithm achieves an average of 16.4% improvement in reliability and an average of 49.3% improvement in performability.

Middleware infrastructure for parallel and distributed programming models in heterogeneous systems

Abstract: We introduce a middleware infrastructure that provides software services for developing and deploying high-performance parallel programming models and distributed applications on clusters and networked heterogeneous systems. This middleware infrastructure utilizes distributed agents residing on the participating machines and communicating with one another to perform the required functions. An intensive study of the parallel programming models in Java has helped identify the common requirements for a runtime support environment, which we used to define the middleware functionality. A Java-based prototype, based on this architecture, has been developed along with a Java object-passing interface (JOPI) class library. Since this system is written completely in Java, it is portable and allows executing programs in parallel across multiple heterogeneous platforms. With the middleware infrastructure, users need not deal with the mechanisms of deploying and loading user classes on the heterogeneous system. Moreover, details of scheduling, controlling, monitoring, and executing user jobs are hidden, while the management of system resources is made transparent to the user. Such uniform services are essential for facilitating the development and deployment of scalable high-performance Java applications on clusters and heterogeneous systems. An initial deployment of a parallel Java programming model over a heterogeneous, distributed system shows good performance results. In addition, a framework for the agents' startup mechanism and organization is introduced to provide scalable deployment and communication among the agents.

Image Harvest: an open-source platform for high-throughput plant image processing and analysis.

Abstract: High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Langmuir-Blodgett films

Abstract: The controlled transfer of organized monolayers of amphiphilic molecules from the airwater interface to a solid substrate was the first molecular-scale technology for the creation of new materials. However, the potential benefits of the technology envisioned by Langmuir and Blodgett in the 1930s have yet to be fully realized. Problems of reproducibility and defects and the lack of basic understanding of the packing of complex molecules in thin films have continued to thwart practical applications of Langmuir-Blodgett films and devices made from such films. However, modern high-resolution x-ray diffraction and scanning probe microscopy have proven to be ideal tools to resolve many of the basic questions involving thin organic films. Here, studies are presented of molecular order and organization in thin films of fatty acid salts, the prototypical system of Katharine Blodgett. Even these relatively simple systems present liquid, hexatic, and crystalline order; van der Waals and strained layer epitaxy on various substrates; wide variations in crystal symmetry and interfacial area with counterions; modulated superstructures; and coexisting lattice structures. The wide variety of possible structures presents both a challenge and an opportunity for future molecular design of organic thin-film devices.

Using Mpi Portable Parallel Programming With The Message Passing Interface

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Chiral recognition in dimerization of adsorbed cysteine observed by scanning tunnelling microscopy.

Abstract: Stereochemistry plays a central role in controlling molecular recognition and interaction: the chemical and biological properties of molecules depend not only on the nature of their constituent atoms but also on how these atoms are positioned in space. Chiral specificity is consequently fundamental in chemical biology and pharmacology1,2 and has accordingly been widely studied. Advances in scanning probe microscopies now make it possible to probe chiral phenomena at surfaces at the molecular level. These methods have been used to determine the chirality of adsorbed molecules3,4,5, and to provide direct evidence for chiral discrimination in molecular interactions6 and the spontaneous resolution of adsorbates into extended enantiomerically pure overlayers3,7,8,9. Here we report scanning tunnelling microscopy studies of cysteine adsorbed to a (110) gold surface, which show that molecular pairs formed from a racemic mixture of this naturally occurring amino acid are exclusively homochiral, and that their binding to the gold surface is associated with local surface restructuring. Density-functional theory10 calculations indicate that the chiral specificity of the dimer formation process is driven by the optimization of three bonds on each cysteine molecule. These findings thus provide a clear molecular-level illustration of the well known three-point contact model11,12 for chiral recognition in a simple bimolecular system.