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At least 559 records · Page 31

PREEMPT: Scalable Epidemic Interventions Using Submodular Optimization on Multi-GPU Systems

Preventing and slowing the spread of epidemics is achieved through techniques such as vaccination and social distancing. Given practical limitations on the number of vaccines and cost of administration, optimization becomes a necessity. Previous approaches using mathematical programming methods have shown to be effective but are limited by computational costs. In this work, we make several contributions: First, we present a new approach for intervention via maximizing the influence of vaccinated nodes on the network. We call this method \preempt. Next, we prove submodular properties associated with the objective function of our method so that it aids in construction of an efficient greedy approximation strategy. Consequently, we present a new parallel algorithm based on greedy hill climbing for \preempt, and present an efficient parallel implementation for distributed CPU-GPU heterogeneous platforms. Our results demonstrate that \preempt{} is able to achieve a significant reduction (up to 6.75$\times$) in the percentage of people infected on a city-scale network. We also show strong scaling results of \preempt{} on 128 nodes of the Summit supercomputer. Our parallel implementation is able to significantly reduce time to solution, from hours to minutes on large networks. This work represents a first-of-its-kind effort in parallelizing greedy hill climbing and applying it toward devising effective interventions for epidemics.

Minutoli, Marco↗

Geometric Mapping of Tasks to Processors on Parallel Computers with Mesh or Torus Networks

We present a new method for reducing parallel applications' communication time by mapping their MPI tasks to processors in a way that lowers the distance messages travel and the amount of congestion in the network. Assuming geometric proximity among the tasks is a good approximation of their communication interdependence, we use a geometric partitioning algorithm to order both the tasks and the processors, assigning task parts to the corresponding processor parts. In this way, interdependent tasks are assigned to “nearby” cores in the network. We also present a number of algorithmic optimizations that exploit specific features of the network or application to further improve the quality of the mapping. We specifically address the case of sparse node allocation, where the nodes assigned to a job are not necessarily located in a contiguous block nor within close proximity to each other in the network. Furthermore, our methods generalize to contiguous allocations as well, and results are shown for both contiguous and non-contiguous allocations. We show that, for the structured finite difference mini-application MiniGhost, our mapping methods reduced communication time up to 75% relative to MiniGhost's default mapping on 128K cores of a Cray XK7 with sparse allocation. For the atmospheric modeling code E3SM/HOMME, our methods reduced communication time up to 31% on 16K cores of an IBM BlueGene/Q with contiguous allocation.

97 MATHEMATICS AND COMPUTING↗

Aerodynamic Shape Optimization Using Hybridized Differential Evolution

An aerodynamic shape optimization method that uses an evolutionary algorithm known at Differential Evolution (DE) in conjunction with various hybridization strategies is described. DE is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Various hybridization strategies for DE are explored, including the use of neural networks as well as traditional local search methods. A Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the hybrid DE optimizer. The method is implemented on distributed parallel computers so that new designs can be obtained within reasonable turnaround times. Results are presented for the inverse design of a turbine airfoil from a modern jet engine. (The final paper will include at least one other aerodynamic design application). The capability of the method to search large design spaces and obtain the optimal airfoils in an automatic fashion is demonstrated.

Madavan, Nateri K.↗

Moment representation in the lattice Boltzmann method on massively parallel hardware

The widely-used lattice Boltzmann method (LBM) for computational fluid dynamics is highly scalable, but also significantly memory bandwidth-bound on current architectures. This paper presents a new regularized LBM implementation that reduces the memory footprint by only storing macroscopic, moment-based data. We show that the amount of data that must be stored in memory during a simulation is reduced by up to 47%. We also present a technique for cache-aware data re-utilization and show that optimizing cache utilization to limit data motion results in a similar improvement in time to solution. These new algorithms are implemented in the hemodynamics solver HARVEY and demonstrated using both idealized and realistic biological geometries. We develop a performance model for the moment representation algorithm and evaluate the performance on Summit.

Vardhan, Madhurima↗

NASA Tech Briefs, March 2013

Topics covered include: Remote Data Access with IDL Data Compression Algorithm Architecture for Large Depth-of-Field Particle Image Velocimeters Vectorized Rebinning Algorithm for Fast Data Down-Sampling Display Provides Pilots with Real-Time Sonic-Boom Information Onboard Algorithms for Data Prioritization and Summarization of Aerial Imagery Monitoring and Acquisition Real-time System (MARS) Analog Signal Correlating Using an Analog-Based Signal Conditioning Front End Micro-Textured Black Silicon Wick for Silicon Heat Pipe Array Robust Multivariable Optimization and Performance Simulation for ASIC Design; Castable Amorphous Metal Mirrors and Mirror Assemblies; Sandwich Core Heat-Pipe Radiator for Power and Propulsion Systems; Apparatus for Pumping a Fluid; Cobra Fiber-Optic Positioner Upgrade; Improved Wide Operating Temperature Range of Li-Ion Cells; Non-Toxic, Non-Flammable, -80 C Phase Change Materials; Soft-Bake Purification of SWCNTs Produced by Pulsed Laser Vaporization; Improved Cell Culture Method for Growing Contracting Skeletal Muscle Models; Hand-Based Biometric Analysis; The Next Generation of Cold Immersion Dry Suit Design Evolution for Hypothermia Prevention; Integrated Lunar Information Architecture for Decision Support Version 3.0 (ILIADS 3.0); Relay Forward-Link File Management Services (MaROS Phase 2); Two Mechanisms to Avoid Control Conflicts Resulting from Uncoordinated Intent; XTCE GOVSAT Tool Suite 1.0; Determining Temperature Differential to Prevent Hardware Cross-Contamination in a Vacuum Chamber; SequenceL: Automated Parallel Algorithms Derived from CSP-NT Computational Laws; Remote Data Exploration with the Interactive Data Language (IDL); Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals; Partitioned-Interval Quantum Optical Communications Receiver; and Practical UAV Optical Sensor Bench with Minimal Adjustability.

Source record↗

Management of analytical redundancy in digital flight control systems for aircraft

This paper presents a design method for optimal redundancy management for nonlinear systems with application to highly maneuvering aircraft. The approach taken is based on selecting the failure states to be covered by the system design and constructing a cost function that represents the cost of making an incorrect decision. The decision logic which minimizes the cost requires a bank of extended Kalman filters running in parallel. This produces a severe computational requirement. To reduce this requirement, a suboptimal logic is developed based on using a nonlinear single-stage prediction algorithm in the filters with filter gains and decision logic selected using steady-state results obtained from a linearization of the vehicle and sensor dynamics. The design process is then applied to designing a redundancy management system for the F8-C aircraft. Results indicate that the system is superior in failure detection to a system using the same structure but using a linear single-stage prediction algorithm in the filters.

Montgomery, R. C.↗

Digital optical computers at the optoelectronic computing systems center

The Digital Optical Computing Program within the National Science Foundation Engineering Research Center for Opto-electronic Computing Systems has as its specific goal research on optical computing architectures suitable for use at the highest possible speeds. The program can be targeted toward exploiting the time domain because other programs in the Center are pursuing research on parallel optical systems, exploiting optical interconnection and optical devices and materials. Using a general purpose computing architecture as the focus, we are developing design techniques, tools and architecture for operation at the speed of light limit. Experimental work is being done with the somewhat low speed components currently available but with architectures which will scale up in speed as faster devices are developed. The design algorithms and tools developed for a general purpose, stored program computer are being applied to other systems such as optimally controlled optical communication networks.

Jordan, Harry F.↗

Concurrent and vectorized mixed time, explicit nonlinear structural dynamics algorithms

A nonlinear structural dynamics program with an element library that exploits parallel processing is described. The aim is to exploit scheduling-allocation so that parallel processing and vectorization can effectively be treated in a general purpose program with explicit time integration and different time steps in different parts of the mesh. The program uses an element group scheme, which, as a by-product, also provides an automatic scheme for assigning different time steps to different parts of the mesh. The program has been tested on the Alliant FX/8; it shows a fivefold improvement in speed over compiler optimization.

Belytschko, Ted↗

An implicit barotropic mode solver for MPAS-ocean using a modern Fortran solver interface

Here, we demonstrate use of a modern Fortran solver interface to manage solver algorithms for an implicit barotropic mode solver in the Model for Predictions Across Scales-Ocean (MPAS-O). ForTrilinos, a Fortran interface to Trilinos that contains a large collection of solver capabilities written in C++, has been implemented in MPAS-O to provide access to a suite of linear solver options. By virtue of the simplified wrapper and interface generator (SWIG) automation tool that generates modern Fortran interfaces to C++ code, we were able to implement the Fortran solver interface in MPAS-O using a familiar Fortran coding style while minimizing performance degradation. The ForTrilinos solver interface is written within MPAS-O’s time stepping modules as a subroutine in conjunction with MPAS-O code. Applied to an idealized ocean and a high-resolution realistic ocean test case, parallel performance of ForTrilinos solvers is examined. It is found that parallel scalability of the ForTrilinos solvers is highly dependent on the number of global synchronization points per solver iteration in each iterative solver algorithm. ForTrilinos solvers perform best compared to the Fortran hand-crafted (FHC) solver when the amount of work per processor is large enough. However, parallel scalability is better with the FHC solver and so when the work per core is modest FHC outperforms ForTrilinos. The intercomparison between the ForTrilinos and FHC solvers reveals that this performance hit in the ForTrilinos solver mostly comes from the global synchronization process, while suggesting that the matrix-vector multiplication process in the FHC solver needs to be optimized for better performance.

97 MATHEMATICS AND COMPUTING↗

The effect of model uncertainty on some optimal routing problems

The effect of model uncertainties on optimal routing in a system of parallel queues is examined. The uncertainty arises in modeling the service time distribution for the customers (jobs, packets) to be served. For a Poisson arrival process and Bernoulli routing, the optimal mean system delay generally depends on the variance of this distribution. However, as the input traffic load approaches the system capacity the optimal routing assignment and corresponding mean system delay are shown to converge to a variance-invariant point. The implications of these results are examined in the context of gradient-based routing algorithms. An example of a model-independent algorithm using online gradient estimation is also included.

Mohanty, Bibhu↗

Event Selection and Background Rejection in Time Projection Chambers Using Convolutional Neural Networks and a Specific Application to the AdEPT Gamma-ray Polarimeter Mission

The Advanced Energetic Pair Telescope gamma-ray polarimeter uses a time projection chamber for measuring pair production events and is expected to generate a raw instrument data rate four orders of magnitude greater than is transmittable with typical satellite data communications. GammaNet, a convolutional neural network, proposes to solve this problem by performing event classification on-board for pair production and background events, reducing the data rate to a level that can be accommodated by typical satellite communication systems. In order to train GammaNet, a set of 1.1 × 10(exp 6) pair production events and 10(exp 6) background events were simulated for the Advanced Energetic Pair Telescope using the Geant4 Monte Carlo code. An additional set of 10(exp 6) pair production and 10 background events were simulated to test GammaNet’s capability for background discrimination. With optimization, GammaNet has achieved the proposed background rejection requirements for Galactic Cosmic Ray proton events. Given the best case assumption for downlink speeds, signal sensitivity for pair production ranged between 1.1 ± 0.5% to 69 ± 2% for 5 and 250 MeV incident gamma rays. This range became 0.1 ± 0.1% to 17 ± 2% for the worst case scenario of downlink speeds. The application of a feature visualization algorithm to GammaNet demonstrated decreased response to electronic noise and events exiting or entering the frame and increased response to parallel tracks that are close in proximity. GammaNet has been successfully implemented and shows promising results.

Richard L. Garnett↗

Parallelized hybrid optimization methods for nonsmooth problems using NOMAD and linesearch

Two parallelized hybrid methods are presented for single-function optimization problems with side constraints. The optimization problems are difficult not only due to possible existence of local minima and nonsmoothness of functions, but also due to the fact that objective function and constraint values for a solution vector can only be obtained by querying a black box whose execution requires considerable computational effort. Examples are optimization problems in Engineering where objective function and constraint values are computed via complex simulation programs, and where local minima exist and smoothness of functions is not assured. The hybrid methods consist of the well-known method NOMAD and two new methods called DENCON and DENPAR that are based on the linesearch scheme CS-DFN. The hybrid methods compute for each query a set of solution vectors that are evaluated in parallel. The hybrid methods have been tested on a set of difficult optimization problems produced by a certain seeding scheme for multiobjective optimization. We compare computational results with solution by NOMAD, DENCON, and DENPAR as stand-alone methods. It turns out that among the stand-alone methods, NOMAD is significantly better than DENCON and DENPAR. However, the hybrid methods are definitely better than NOMAD.

97 MATHEMATICS AND COMPUTING↗

Automatic variable selection in ecological niche modeling: A case study using Cassin’s Sparrow (Peucaea cassinii)

MERRA/Max provides a feature selection approach to dimensionality reduction that enables direct use of global climate model outputs in ecological niche modeling. The system accomplishes this reduction through a Monte Carlo optimization in which many independent MaxEnt runs, operating on a species occurrence file and a small set of randomly selected variables in a large collection of variables, converge on an estimate of the top contributing predictors in the larger collection. These top predictors can be viewed as potential candidates in the variable selection step of the ecological niche modeling process. MERRA/Max’s Monte Carlo algorithm operates on files stored in the underlying filesystem, making it scalable to large data sets. Its software components can run as parallel processes in a high-performance cloud computing environment to yield near real-time performance. In tests using Cassin’s Sparrow (Peucaea cassinii) as the target species, MERRA/Max selected a set of predictors from Worldclim’s Bioclim collection of 19 environmental variables that have been shown to be important determinants of the species’ bioclimatic niche. It also selected biologically and ecologically plausible predictors from a more diverse set of 86 environmental variables derived from NASA’s Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) reanalysis, an output product of the Goddard Earth Observing System Version 5 (GEOS-5) modeling system. We believe these results point to a technological approach that could expand the use global climate model outputs in ecological niche modeling, foster exploratory experimentation with otherwise difficult-to-use climate data sets, streamline the modeling process, and, eventually, enable automated bioclimatic modeling as a practical, readily accessible, low-cost, commercial cloud service.

John L. Schnase↗

Prediction of perovskite and other ternary oxide multilayers as mirrors for soft X-rays

Highlights: • Theoretical framework to identify optimal multilayers for high x-ray reflectivity. • Perovskite oxide multilayers are proposed as soft x-ray mirrors. • High soft x-ray reflectivity up to 33% are expected in perovskite multilayers. - Abstract: We propose multilayers of perovskite and related ternary oxides with a general formula of ABO{sub 3} as high reflectivity mirrors, especially for use in water window region (2.3–4.4 nm). The high reflectivity combinations of oxide multilayers were deduced using evolutionary search algorithms such as genetic algorithms, and the calculation speed was accelerated via parallel computing methods We also propose a figure of merit for X-ray reflectivity in periodic multilayers systems, which can simplify the future efforts on identifying material combinations, and the search through this multi-dimensional parameter space. The highest reflectivity value was found to be over 33% at 3.1 nm in the water window region. The effect of interface roughness was simulated and the decrease in reflectivity was found to be modest for practically achievable roughness values. This work establishes the foundation for future experimental and theoretical studies towards achieving high reflectivity x-ray mirrors of complex oxide multilayers.

36 MATERIALS SCIENCE↗

High-throughput feedback-enabled optogenetic stimulation and spectroscopy in microwell plates

Abstract The ability to perform sophisticated, high-throughput optogenetic experiments has been greatly enhanced by recent open-source illumination devices that allow independent programming of light patterns in single wells of microwell plates. However, there is currently a lack of instrumentation to monitor such experiments in real time, necessitating repeated transfers of the samples to stand-alone analytical instruments, thus limiting the types of experiments that could be performed. Here we address this gap with the development of the optoPlateReader (oPR), an open-source, solid-state, compact device that allows automated optogenetic stimulation and spectroscopy in each well of a 96-well plate. The oPR integrates an optoPlate illumination module with a module called the optoReader, an array of 96 photodiodes and LEDs that allows 96 parallel light measurements. The oPR was optimized for stimulation with blue light and for measurements of optical density and fluorescence. After calibration of all device components, we used the oPR to measure growth and to induce and measure fluorescent protein expression in E. coli . We further demonstrated how the optical read/write capabilities of the oPR permit computer-in-the-loop feedback control, where the current state of the sample can be used to adjust the optical stimulation parameters of the sample according to pre-defined feedback algorithms. The oPR will thus help realize an untapped potential for optogenetic experiments by enabling automated reading, writing, and feedback in microwell plates through open-source hardware that is accessible, customizable, and inexpensive.

59 BASIC BIOLOGICAL SCIENCES↗

Optimal mapping of irregular finite element domains to parallel processors

Mapping the solution domain of n-finite elements into N-subdomains that may be processed in parallel by N-processors is an optimal one if the subdomain decomposition results in a well-balanced workload distribution among the processors. The problem is discussed in the context of irregular finite element domains as an important aspect of the efficient utilization of the capabilities of emerging multiprocessor computers. Finding the optimal mapping is an intractable combinatorial optimization problem, for which a satisfactory approximate solution is obtained here by analogy to a method used in statistical mechanics for simulating the annealing process in solids. The simulated annealing analogy and algorithm are described, and numerical results are given for mapping an irregular two-dimensional finite element domain containing a singularity onto the Hypercube computer.

Flower, J.↗

Optimal design of microtube recuperators for an indirect supercritical carbon dioxide recompression closed Brayton cycle

This paper presents a baseline design and optimization approach developed in Aspen Custom Modeler (ACM) for microtube shell-and-tube exchangers (MSTEs) used for high- and low-temperature recuperation in a 10 MWe indirect supercritical carbon dioxide (sCO 2 ) recompression closed Brayton cycle (RCBC). The MSTE-type recuperators are designed using one-dimensional models with thermal-hydraulic correlations appropriate for sCO 2 and properties models that capture considerable nonlinear changes in CO 2 properties near the critical and pseudo-critical points. Using the successive quadratic programming (SQP) algorithm in ACM, optimal recuperator designs are obtained for either custom or industry-standard microtubes considering constraints based on current advanced manufacturing techniques. The three decision variables are the number of tubes, tube pitch-to-diameter ratio, and tube diameter. Five different objective functions based on different key design measures are considered: minimization of total heat transfer area, heat exchanger volume, metal weight, thermal residence time, and maximization of compactness. Sensitivities studies indicate the constraint on the maximum number of tubes per shell does affect the number of parallel heat exchanger trains but not the tube selection, total number of tubes, tube length and other key design measures in the final optimal design when considering industry-standard tubes. In this study, the optimally designed high- and low-temperature recuperators have 47,000 3/32 inch tubes and 63,000 1/16 inch tubes, respectively. In addition, sensitivities to the design temperature approach and maximum allowable pressure drop are studied, since these specifications significantly impact the optimal design of the recuperators as well as the thermal efficiency and the economic performance of the entire sCO 2 Brayton cycle.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Preface to the Special Issue on TOUGH Symposium 2015

The TOUGH Symposium 2015 was held in Berkeley, California, September 28-30, 2015. The TOUGH family of codes, developed at the Energy Geosciences Division of Lawrence Berkeley National Laboratory (LBNL), is a suite of computer programs for the simulation of multiphase and multicomponent fluid and heat flows in porous and fractured media with applications in many geosciences fields, such as geothermal reservoir engineering, nuclear waste disposal, geological carbon sequestration, oil and gas reservoirs, gas hydrate research, vadose zone hydrology and environmental remediation. Since the first release in the 1980s, many modifications and enhancements have been continuously made to TOUGH and its various descendants (iTOUGH2, TOUGH+, TOUGH-MP, TOUGHREACT, TOUGH+HYDRATE, TMVOC...), at LBNL and elsewhere. Today, these codes are used worldwide in academia, government organizations and private companies in problems involving coupled hydrological, thermal, biogeochemical and geomechanical processes. The Symposia, organized every 2-3 years, bring together developers and users for an open exchange on recent code enhancements and applications. In 2015, the Symposium was attended by one hundred participants, representing thirty-four nationalities. This Special Issue in Computers & Geosciences gathers extended versions of selected Symposium proceedings related to (i) recent enhancements to the TOUGH family of codes and (ii) coupled flow and geomechanics processes modeling. In this special issue, a paper by Jung et al. provides a new base version of TOUGH, TOUGH3. This latest version addresses the computational robustness and efficiency needed for the increasing complexity of the simulated processes and the growing size of model domains. Moreover, it consolidates the serial and parallel versions into a single code, hence, inconsistencies between different versions are less likely to occur, and code maintenance and development become more efficient. Finsterle et al. present a review of the capabilities of iTOUGH2 and illustrate the workflow of an integrated simulation-optimization framework. Liu et al. present an approach to reduce the computational cost of performing Bayesian inverse modeling and demonstrate their approach using a synthetic experiment simulated with TOUGH2. Regarding the mesh generation process, the paper by Doughty presents a generalization of the grid-generation algorithm embedded in TOUGH2 (MESHMAKER) to create one-column grids with fractal dimension, useful for representing flow through fractures or highly heterogeneous media with fractal geometry, and also for inverse methods. Sentís and Gable present a module to interface the open source code Lagrit with TOUGH2, that assists in the processes of mesh generation and model setup, and that can be particularly useful for complex geometries and large models. Bonduà et al. present a pre-processing tool (VORO2MESH) that features a full 3D Voronoi approach for structured and unstructured grids, and an enhanced post-processor (TOUGH2Viewer) for the visualization of 3D Voronoi grids. The literature review shows that coupled fluid flow and geomechanics has gained increasing attention in the last years in many geosciences fields. In this context, several codes of the TOUGH family have been successfully coupled with geomechanics software. The paper by Rutqvist presents a review of some of these TOUGH-based geomechanics models, of which the TOUGH-FLAC simulator – presented for the first time in the TOUGH Symposium 2003 – is well-known worldwide and has been used in a large variety of applications, encompassing the application domains of the TOUGH codes. Blanco-Martín et al. present an extension of TOUGH-FLAC to the finite strain framework, motivated by the existence of large strains associated with rock salt deformation in the context of heat-generating nuclear waste disposal. Following a paper published in the Special Issue of the TOUGH Symposium 2012 in this journal, Kim et al. present the current status of the TOUGH-RSBN simulator for coupled hydro-mechanical modeling of hydraulic fracturing using a discrete fracture network approach, and present some validation and demonstration cases. Rinaldi and Nespoli present TOUGH-SEED, an injection-induced seismicity modeling approach using TOUGH2 and a geomechanics stochastic model, and apply it to the Basel EGS project. Finally, Rinaldi et al. use the PEST protocol implemented in iTOUGH2, combined with TOUGH-FLAC as the forward model, to perform inverse modeling for the In Salah CO2 demonstration site in Algeria. Using pore pressures and InSAR displacements as observations, this approach allows for a multi-physics joint inversion and takes advantage of the inverse capabilities of iTOUGH2 (parameter estimation, sensitivity analysis, uncertainty estimation …), applied to coupled fluid flow and geomechanics. On behalf of the members of the TOUGH Symposium 2015 Organizing Committee, I hope that this collection of papers will provide the readers of Computers & Geosciences with a recent view of the capabilities of the TOUGH family of codes, as well as with current modeling research domains in the geosciences. Last but not least, I would like to express my gratitude to all the reviewers who kindly contributed to this Special Issue, as well as the Journal staff who have made this publication possible.

99 GENERAL AND MISCELLANEOUS↗