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At least 1,261 records · Page 70

Scalable assembly of patterned ordered functional micelle arrays: final LDRD report

In this project, we demonstrated the synthesis of polystyrene-polyvinylpyridyne (PS-PVP) micelles, functionalization of these micelles to form organic/inorganic composite nanoparticles, and template directed assembly of dynamic PS-PVP micelles into features defined via soft nanoimprint lithography. We demonstrated unique assembly properties of dynamic micellar nanoparticles by combining a top down lithographic nanopatterning technique with a solution based bottom up self-assembly.

Fan, Hongyou↗

Research on Anaerobic Digestion: Optimization and Scalability of Mixed High-strength Food Processing Wastes for Renewable Biogas Energy

This research project developed and improved anaerobic digestion technologies, created a comprehensive Inventory of Ohio Biomass and a database of microorganisms of anaerobic digesters, and advanced knowledge and understanding of the underpinning microbiology of the anaerobic digestion process. The results and finding of this research project may be useful for future development and implementation of anaerobic digesters, especially at livestock farms. Policy makers and investors may also find the information on the biomass availability in Ohio and valuation of energy projects useful in policy making and making of investment decisions. The public may benefit from the information on biogas as an energy source and the potential impact of anaerobic digester projects on their neighborhoods.

09 BIOMASS FUELS↗

Institute for Scalable Application Development Software

Work by the University of Wisconsin as part of the DOE SciDAC CScADS includes the following accomplishments: Research on tool componentization, with concentration on the: InstructionAPI and InstructionSemanticsAPI ParseAPI DataflowAPI Co-organized a series of high successful workshops with Prof. John Mellor-Crummey, Rice University, on Performance Tools for Petascale Computing, held in Snowbird, Utah and Lake Tahoe, California in July or August of 2007 through 2012. Investigated the use of multicore in numerical libraries Dyninst porting to 32- and 64bit Power/PowerPC (including BlueGene) and 32- and 64-bit Pentium platforms. Applying our toolkits to advanced problems in binary code parsing associated with dealing with legacy and malicious code.

97 MATHEMATICS AND COMPUTING↗

Final Report: Super Instruction Architecture for Scalable Parallel Computations

The most advanced methods for reliable and accurate computation of the electronic structure of molecular and nano systems are the coupled-cluster techniques. These high-accuracy methods help us to understand, for example, how biological enzymes operate and contribute to the design of new organic explosives. The ACES III software provides a modern, high-performance implementation of these methods optimized for high performance parallel computer systems, ranging from small clusters typical in individual research groups, through larger clusters available in campus and regional computer centers, all the way to high-end petascale systems at national labs, including exploiting GPUs if available. This project enhanced the ACESIII software package and used it to study interesting scientific problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Heterogeneous scalable framework for multiphase flows

Two categories of challenges confront the developer of computational spray models: those related to the computation and those related to the physics. Regarding the computation, the trend towards heterogeneous, multi- and many-core platforms will require considerable re-engineering of codes written for the current supercomputing platforms. Regarding the physics, accurate methods for transferring mass, momentum and energy from the dispersed phase onto the carrier fluid grid have so far eluded modelers. Significant challenges also lie at the intersection between these two categories. To be competitive, any physics model must be expressible in a parallel algorithm that performs well on evolving computer platforms. This work created an application based on a software architecture where the physics and software concerns are separated in a way that adds flexibility to both. The develop spray-tracking package includes an application programming interface (API) that abstracts away the platform-dependent parallelization concerns, enabling the scientific programmer to write serial code that the API resolves into parallel processes and threads of execution. The project also developed the infrastructure required to provide similar API s to other application. The API allow object-oriented Fortran applications direct interaction with Trilinos to support memory management of distributed objects in central processing units (CPU) and graphic processing units (GPU) nodes for applications using C++.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Scalable methods for electronic excitations and optical responses of nanostructures: mathematics to algorithms to observables

The master project under which this work is funded had as its main objective to develop computational methods for modeling electronic excited-state and optical properties of various nanostructures. The specific goals of the computer science group were primarily to develop effective numerical algorithms in Density Functional Theory (DFT) and Time Dependent Density Functional Theory (TDDFT). There were essentially four distinct stated objectives. The first objective was to study and develop effective numerical algorithms for solving large eigenvalue problems such as those that arise in Density Functional Theory (DFT) methods. The second objective was to explore so-called linear scaling methods or Methods that avoid diagonalization. The third was to develop effective approaches for Time-Dependent DFT (TDDFT). Our fourth and final objective was to examine effective solution strategies for other problems in electronic excitations, such as the GW/Bethe-Salpeter method, and quantum transport problems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Scalable Statistical Analysis of Gaussian Models for Petascale Spatiotemporal Data (Final Technical Report)

Gaussian process models for spatial and spatiotemporal data are ubiquitous in scientific and engineering applications. Likelihood-based methods for fitting such models, which includes all Bayesian methods, have desirable statistical properties and are thus the methods of choice when feasible. However, calculating the likelihood function even once can be a challenge for N irregularly sited observations from such a process, requiring O(N 2 ) memory and O(N 3 ) complexity. Thus, there is a need for fast and accurate likelihood approximation even for N on the order of 10 5 , not to mention the 10 15 implied by petascale data. The main objective of this research was to develop computational tools for the statistical analysis of massive spatiotemporal datasets based on Gaussian process models. Another important objective was the development of appropriate statistical models for specific spatiotemporal processes arising in the physical sciences.

97 MATHEMATICS AND COMPUTING↗

Performance Verification of Production-Scalable Energy-Efficient Solutions: Winchester/Camberley Homes Mixed-Humid Climate

Winchester/Camberley Homes with the Building America program and its NAHB Research Center Industry Partnership collaborated to develop a new set of high performance home designs that could be applicable on a production scale. The new home designs are to be constructed in the mixed humid climate zone four and could eventually apply to all of the builder's home designs to meet or exceed future energy codes or performance-based programs. However, the builder recognized that the combination of new wall framing designs and materials, higher levels of insulation in the wall cavity, and more detailed air sealing to achieve lower infiltration rates changes the moisture characteristics of the wall system. In order to ensure long term durability and repeatable successful implementation with few call-backs, this report demonstrates through measured data that the wall system functions as a dynamic system, responding to changing interior and outdoor environmental conditions within recognized limits of the materials that make up the wall system. A similar investigation was made with respect to the complete redesign of the heating, cooling, air distribution, and ventilation systems intended to optimize the equipment size and configuration to significantly improve efficiency while maintaining indoor comfort. Recognizing the need to demonstrate the benefits of these efficiency features, the builder offered a new house model to serve as a test case to develop framing designs, evaluate material selections and installation requirements, changes to work scopes and contractor learning curves, as well as to compare theoretical performance characteristics with measured results.

2X6 WALLS↗

Scalable Adaptive Multilevel Solvers for Multiphysics Problems

In this project, we carried out many studies on adaptive and parallel multilevel methods for numerical modeling for various applications, including Magnetohydrodynamics (MHD) and complex fluids. We have made significant efforts and advances in adaptive multilevel methods of the multiphysics problems: multigrid methods, adaptive finite element methods, and applications.

97 MATHEMATICS AND COMPUTING↗

Photocopia-A Unibody Mono-material Compact and Scalable Photomultiplier

The Photocopia photomultiplier tube (PMT) takes advantage of two of the many unique properties of the hydrogenated amorphous silicon-germanium (a-SiGe) photoemitter material: its mechanical flexibility and mostly substrate-independent properties. The a-SiGe photoemitter has high secondary electron (SE) yield. It can be used both as the photocathode and as the gain medium. The active material can be grown on a flat, thin unibody substrate, formed and then “rolled up” ex situ. The completed structure would then be activated and sealed within a tube. The Ge component can be increased to enhance red-sensitivity. Compact sizes are possible, minimizing magnetic field effects. The Photocopia PMT will be a low cost alternative to MCPs for TOF detectors and provide better timing discrimination for Cherenkov detectors. Retention of the ability to activate to a normal photoyield state upon flexing (bending) the substrate of the a-SiGe material after growth, but prior to activation has been shown. The SE coefficient of the activated material has been characterized over the voltage range suitable for utilization as the gain material. The time response of the material is suited to PMT use.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Enabling Exascale Hardware and Software Design through Scalable System Virtualization (Final Report)

The purpose of this project has been to extend the state of the art of systems software for high-end computing (HEC) platforms, and to use systems software to better enable the evaluation of potential future HEC platforms, for example exascale platforms. Such platforms, and their systems software, have the goal of providing scientific computation at new scales, thus enabling new research in the physical sciences and engineering. Over time, the innovations in systems software for such platforms also become applicable to more widely used computing clusters, data centers, and clouds. This was a five-institution project, centered on the Palacios virtual machine monitor (VMM) systems software, a project begun at Northwestern, and originally developed in a previous collaboration between Northwestern University and the University of New Mexico. In this project, Northwestern (including via our subcontract to the University of Pittsburgh) contributed to the continued development of Palacios, along with other team members. We took the leadership role in (1) continued extension of support for emerging Intel and AMD hardware, (2) integration and performance enhancement of overlay networking, (3) connectivity with architectural simulation, (4) binary translation, and (5) support for modern Non-Uniform Memory Access (NUMA) hosts and guests. We also took a supporting role in support for specialized hardware for I/O virtualization, profiling, configurability, and integration with configuration tools. The efforts we led (1-5) were largely successful and executed as expected, with code and papers resulting from them. The project demonstrated the feasibility of a virtualization layer for HEC computing, similar to such layers for cloud or datacenter computing. For effort (3), although a prototype connecting Palacios with the GEM5 architectural simulator was demonstrated, our conclusion was that such a platform was less useful for design space exploration than anticipated due to inherent complexity of the connection between the instruction set architecture level and the microarchitectural level. For effort (4), we found that a code injection approach proved to be more fruitful. The results of our efforts are publicly available in the open source Palacios codebase and published papers, all of which are available from the project web site, v3vee.org. Palacios is currently one of the two codebases (the other being Sandia’s Kitten lightweight kernel) that underlies the node operating system for the DOE Hobbes Project, one of two projects tasked with building a systems software prototype for the national exascale computing effort.

97 MATHEMATICS AND COMPUTING↗

Scalability under a Power Bound using the GREMLINs Framework

With the move towards exascale, system and software developers will have to deal with issues of extreme parallelism. The system properties affected most by the increase in node and core count are the shared resources on node and across the system. The increase in parallelism leads to reduced memory and bandwidth when regarding individual cores. Since power is a limiting factor for supercomputers, and power is not fully utilized in current systems, overprovisioning compute resources is a viable approach to maximized power utilization. To maximize system performance in regard to these changing conditions, it is necessary to understand how resource restrictions impact performance and system behavior. For the purpose of understanding anticipated system properties the GREMLINs Framework was developed. The framework gives the opportunity to add power restrictions, hinder memory properties and introduce faults to study resilience, among others. These features give the opportunity to use current petascale technology to study problems system designers and software developers will have to face when moving towards exascale and beyond. This work describes the initial release of the GREMLINs Framework, developed for this work, and shows how it can be used to study the scaling behavior of proxy applications. These proxy applications represent a selection of HPC workloads important to the scientific community. The proxy applications studied are AMG2013, an algebraic multi-grid linear system solver, CoMD, a classical molecular dynamics proxy application and NEKBONE, an application that uses a high order spectral element method to solve the Navier-Stokes equations. The main interest of these studies lies in analysis regarding their power behavior at scale under a power bound. These findings show how the GREMLINs Framework can help systems and software designers to attain better application performance and can also be used as basis for CPU power balancing tools to use power more efficiently.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Scalable fault tolerance runtime technology for petascale computers (Final Project Report)

With the massive number of components comprising the forthcoming petascale computer systems, hardware failures will be routinely encountered during execution of large-scale applications. Due to the multidisciplinary, multiresolution, and multiscale nature of scientific problems that drive the demand for high end systems, applications place increasingly differing demands on the system resources: disk, network, memory, and CPU. In addition to MPI, future applications are expected to use advanced programming models such as those developed under the DARPA HPCS program as well as existing global address space programming models such as Global Arrays, UPC, and Co-Array Fortran. While there has been a considerable amount of work in fault tolerant MPI with a number of strategies and extensions for fault tolerance proposed, virtually none of advanced models proposed for emerging petascale systems is currently fault aware. To achieve fault tolerance, development of underlying runtime and OS technologies able to scale to petascale level is needed. This project has evaluated range of runtime techniques for fault tolerance for advanced programming models.

97 MATHEMATICS AND COMPUTING↗

Scalable Parallel Methods for Analyzing Metagenomics Data at Extreme Scale

The field of bioinformatics and computational biology is currently experiencing a data revolution. The exciting prospect of making fundamental biological discoveries is fueling the rapid development and deployment of numerous cost-effective, high-throughput next-generation sequencing technologies. The result is that the DNA and protein sequence repositories are being bombarded with new sequence information. Databases are continuing to report a Moore’s law-like growth trajectory in their database sizes, roughly doubling every 18 months. In what seems to be a paradigm-shift, individual projects are now capable of generating billions of raw sequence data that need to be analyzed in the presence of already annotated sequence information. While it is clear that data-driven methods, such as sequencing homology detection, are becoming the mainstay in the field of computational life sciences, the algorithmic advancements essential for implementing complex data analytics at scale have mostly lagged behind. Sequence homology detection is central to a number of bioinformatics applications including genome sequencing and protein family characterization. Given millions of sequences, the goal is to identify all pairs of sequences that are highly similar (or “homologous”) on the basis of alignment criteria. While there are optimal alignment algorithms to compute pairwise homology, their deployment for large-scale is currently not feasible; instead, heuristic methods are used at the expense of quality. In this dissertation, we present the design and evaluation of a parallel implementation for conducting optimal homology detection on distributed memory supercomputers. Our approach uses a combination of techniques from asynchronous load balancing (viz. work stealing, dynamic task counters), data replication, and exact-matching filters to achieve homology detection at scale. Results for a collection of 2.56M sequences show parallel efficiencies of ~75-100% on up to 8K cores, representing a time-to-solution of 33 seconds. We extend this work with a detailed analysis of single-node sequence alignment performance using the latest CPU vector instruction set extensions. Preliminary results reveal that current sequence alignment algorithms are unable to fully utilize widening vector registers.

59 BASIC BIOLOGICAL SCIENCES↗