Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “clustering algorithm”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19

Scalability of a Low-Cost Multi-Teraflop Linux Cluster for High-End Classical Atomistic and Quantum Mechanical Simulations

Scalability of a low-cost, Intel Xeon-based, multi-Teraflop Linux cluster is tested for two high-end scientific applications: Classical atomistic simulation based on the molecular dynamics method and quantum mechanical calculation based on the density functional theory. These scalable parallel applications use space-time multiresolution algorithms and feature computational-space decomposition, wavelet-based adaptive load balancing, and spacefilling-curve-based data compression for scalable I/O. Comparative performance tests are performed on a 1,024-processor Linux cluster and a conventional higher-end parallel supercomputer, 1,184-processor IBM SP4. The results show that the performance of the Linux cluster is comparable to that of the SP4. We also study various effects, such as the sharing of memory and L2 cache among processors, on the performance.

Kikuchi, Hideaki↗

Strake-generated vortex interactions for a fighter-like configuration

A combination of the Euler, and thin-layer Navier-Stokes equations were solved for the flowfield around a wing-strake-fuselage configuration similar to the F-16A aircraft. The flowfield was divided into multiple blocks using a zoning program, and the TNSWF solution program, based on an implicit solution algorithm, updates each subregion of the flowfield sequentially. The total grid contained approximately 300,000 grid points, and clustering was effected normal to all aircraft surfaces. The computed solutions agreed well quantitatively with wind-tunnel pressure distribution data, and they agreed well qualitatively with flow visualization from wind- and water-tunnel tests.

Reznick, Steven G.↗

Land Analysis System (LAS)

Version 4.1 of LAS provides flexible framework for algorithm development and processing and analysis of image data. Over 500,000 lines of code enable image repair, clustering, classification, film processing, geometric registration, radiometric correction, and manipulation of image statistics.

Pease, P. B.↗

Precise and Efficient Static Array Bound Checking for Large Embedded C Programs

In this paper we describe the design and implementation of a static array-bound checker for a family of embedded programs: the flight control software of recent Mars missions. These codes are large (up to 250 KLOC), pointer intensive, heavily multithreaded and written in an object-oriented style, which makes their analysis very challenging. We designed a tool called C Global Surveyor (CGS) that can analyze the largest code in a couple of hours with a precision of 80%. The scalability and precision of the analyzer are achieved by using an incremental framework in which a pointer analysis and a numerical analysis of array indices mutually refine each other. CGS has been designed so that it can distribute the analysis over several processors in a cluster of machines. To the best of our knowledge this is the first distributed implementation of static analysis algorithms. Throughout the paper we will discuss the scalability setbacks that we encountered during the construction of the tool and their impact on the initial design decisions.

Venet, Arnaud↗

Multigrid techniques for nonlinear eigenvalue probems: Solutions of a nonlinear Schroedinger eigenvalue problem in 2D and 3D

This paper presents multigrid (MG) techniques for nonlinear eigenvalue problems (EP) and emphasizes an MG algorithm for a nonlinear Schrodinger EP. The algorithm overcomes the mentioned difficulties combining the following techniques: an MG projection coupled with backrotations for separation of solutions and treatment of difficulties related to clusters of close and equal eigenvalues; MG subspace continuation techniques for treatment of the nonlinearity; an MG simultaneous treatment of the eigenvectors at the same time with the nonlinearity and with the global constraints. The simultaneous MG techniques reduce the large number of self consistent iterations to only a few or one MG simultaneous iteration and keep the solutions in a right neighborhood where the algorithm converges fast.

Costiner, Sorin↗

Principles and scope of synthetic photometry

The synthetic photometry algorithm and various applications for the algorithm are described. The synthetic photometry algorithm provides magnitudes and colors computed from a spectral energy flux distribution and the response functions of a photometric system. The principles of synthetic photometry which include the observed and theoretical stellar energy distributions and passbands of the photometric systems are discussed. The equations utilized in the algorithm to compute the magnitudes and color indices are provided. There is a need for an evaluation of the passbands and a correlation between the observed photometric and spectrophotometric data of the stars. The algorithm is used as a universal translator providing the communication channels between different reseach areas; it is applicable to clusters, faint star counts, and deep multicolor surveys of galaxies.

Buser, R.↗

Sea surface velocities from visible and infrared multispectral atmospheric mapping sensor imagery

High resolution (100 m), sequential Multispectral Atmospheric Mapping Sensor (MAMS) images were used in a study to calculate advective surface velocities using the Maximum Cross Correlation (MCC) technique. Radiance and brightness temperature gradient magnitude images were formed from visible (0.48 microns) and infrared (11.12 microns) image pairs, respectively, of Chandeleur Sound, which is a shallow body of water northeast of the Mississippi delta, at 145546 GMT and 170701 GMT on 30 Mar. 1989. The gradient magnitude images enhanced the surface water feature boundaries, and a lower cutoff on the gradient magnitudes calculated allowed the undesirable sunglare and backscatter gradients in the visible images, and the water vapor absorption gradients in the infrared images, to be reduced in strength. Requiring high (greater than 0.4) maximum cross correlation coefficients and spatial coherence of the vector field aided in the selection of an optimal template size of 10 x 10 pixels (first image) and search limit of 20 pixels (second image) to use in the MCC technique. Use of these optimum input parameters to the MCC algorithm, and high correlation and spatial coherence filtering of the resulting velocity field from the MCC calculation yielded a clustered velocity distribution over the visible and infrared gradient images. The velocity field calculated from the visible gradient image pair agreed well with a subjective analysis of the motion, but the velocity field from the infrared gradient image pair did not. This was attributed to the changing shapes of the gradient features, their nonuniqueness, and large displacements relative to the mean distance between them. These problems implied a lower repeat time for the imagery was needed in order to improve the velocity field derived from gradient imagery. Suggestions are given for optimizing the repeat time of sequential imagery when using the MCC method for motion studies. Applying the MCC method to the infrared brightness temperature imagery yielded a velocity field which did agree with the subjective analysis of the motion and that derived from the visible gradient imagery. Differences between the visible and infrared derived velocities were 14.9 cm/s in speed and 56.7 degrees in direction. Both of these velocity fields also agreed well with the motion expected from considerations of the ocean bottom topography and wind and tidal forcing in the study area during the 2.175 hour time interval.

Pope, P. A.↗

Dependence of Cumulus Anvil Radiative Properties on Environmental Conditions in the Tropical West Pacific

Areally extensive, optically thick anvil clouds associated with mesoscale convective clusters dominate the shortwave cloud forcing in the tropics and provide longwave forcing comparable to that of thin cirrus. Changes in the cover and optical thickness of tropical anvils as climate warms can regulate the sign of cloud feedback. As a prelude to the study of MMCR data from the ARM TWP sites, we analyze ISCCP-derived radiative characteristics of anvils observed in the tropical west Pacific during the TOGA-COARE IOP. Anvils with radius greater than 100 km were identified and tracked from inception to decay using the Machado-Rossow algorithm. Corresponding environmental conditions just prior to the start of the convectove event were diagnosed using the Lin-Johnson objective analysis product. Small clusters (100-200 km radius) are observed to have a broad range of optical thicknesses (10-50), while intermediate optical thickness clusters are observed to range in size from 100 km to almost 1000 km. Large-size clusters appear to be favored by strong pre-storm large scale upward motion throughout the troposphere, moist low-to-midlevel relative humidities, environments with slightly higher CAPE than those for smaller clusters, and strong front-to-rear flow. Optically thick anvils are favored in situations of strong low-level moisture convergence and strong upper-level shear.

Ye, B.↗

Scheduling Operations for Massive Heterogeneous Clusters

High-performance computing (HPC) programming has become increasingly difficult with the advent of hybrid supercomputers consisting of multicore CPUs and accelerator boards such as the GPU. Manual tuning of software to achieve high performance on this type of machine has been performed by programmers. This is needlessly difficult and prone to being invalidated by new hardware, new software, or changes in the underlying code. A system was developed for task-based representation of programs, which when coupled with a scheduler and runtime system, allows for many benefits, including higher performance and utilization of computational resources, easier programming and porting, and adaptations of code during runtime. The system consists of a method of representing computer algorithms as a series of data-dependent tasks. The series forms a graph, which can be scheduled for execution on many nodes of a supercomputer efficiently by a computer algorithm. The schedule is executed by a dispatch component, which is tailored to understand all of the hardware types that may be available within the system. The scheduler is informed by a cluster mapping tool, which generates a topology of available resources and their strengths and communication costs. Software is decoupled from its hardware, which aids in porting to future architectures. A computer algorithm schedules all operations, which for systems of high complexity (i.e., most NASA codes), cannot be performed optimally by a human. The system aids in reducing repetitive code, such as communication code, and aids in the reduction of redundant code across projects. It adds new features to code automatically, such as recovering from a lost node or the ability to modify the code while running. In this project, the innovators at the time of this reporting intend to develop two distinct technologies that build upon each other and both of which serve as building blocks for more efficient HPC usage. First is the scheduling and dynamic execution framework, and the second is scalable linear algebra libraries that are built directly on the former.

Humphrey, John↗

The NASA Analogy Software Cost Model: A Web-Based Cost Analysis Tool

This paper provides an overview of the many new features and algorithm updates in the release of the NASA Analogy Software Cost Tool (ASCoT). ASCoT is a web-based tool that provides a suite of estimation tools to support early lifecycle NASA Flight Software analysis. ASCoT employs advanced statistical methods such as Cluster Analysis to provide an analogy based estimate of software delivered lines of code and development effort, a regression based Cost Estimating Relationships (CER) model that estimates cost (dollars), and a COCOMO II based estimate. The ASCoT algorithms are designed to primarily work with system level inputs such as mission type (earth orbiter vs. planetary vs. rover), the number of instruments, and total mission cost. This allows the user to supply a minimal number of mission-level parameters which are better understood early in the life-cycle, rather than a large number of complex inputs.

Hihn, Jairus↗

Cluster Seeking Techniques in Pattern Recognition

A cluster seeking technique is defined as a method of dividing data into subsets, called clusters. These clusters contain data points that are similar to each other and different from the elements of other clusters. Various cluster seeking techniques were broken down into seven categories: (1) probabilistic, (2) signal detection, (3) clustering, (4) clumping, (5) eigenvalue, (6) minimal mode seeking, and (7) miscellaneous. Each category is described and one or more algorithms of that type are presented.

Barr, B. J.↗

M-MRAC for SPHERES

This paper presents application of the modified reference model MRAC (M-MRAC) method to control the relative position and orientation of a cluster of satellites known collectively as the Synchronized Position Hold, Engage, Reorient Experimental Satellites (SPHERES). The approach uses fast estimation algorithms to achieve guaranteed tracking of reference commands for both input and output signals in the presence of uncertainties in mass and inertia data and external disturbances. The tracking errors can be systematically decreased by the proper selection of the design parameters in the identification model. The generated control signals have acceptable magnitudes and exhibit no oscillations. The benefits of the method are demonstrated in numerical simulations.

Relative motion↗

Classification of Ascension Island and Natal Ozonesondes Using Self-Organizing Maps

Ozone profiles from balloon-borne ozonesondes are used for development of satellite algorithms and in chemistry-climate model initialization, assimilation and evaluation. An important issue in the application of these profiles is how best to treat variations where varying photochemical and dynamical influences can cause the ozone mixing ratio in the tropospheric segments of the profile to change by of a factor of 2-3 within a day. Clustering techniques are an ideal way to approach the statistical classification of profile data and we apply self-organizing maps to tropical tropospheric SHADOZ data, hypothesizing that the data will sort according to various influences on ozone, namely anthropogenic sources like biomass burning, meteorological conditions, and stratospheric or extra-tropical intrusions. Self-organizing maps, that use a learning algorithm to reveal the most prominent features of a data set according to a specified number of clusters, have been determined for the 1998-2009 SHADOZ profiles over Ascension Island (512 profiles, 7.98 deg. S, 14.42 deg. W) and Natal, Brazil (425 profiles, 5.42degS, 35.38degW). The 2 × 2 self-organizing map, which creates 4 clusters, reveals that deviations from the average ozone in the free troposphere include both increased ozone resulting from seasonal biomass burning in Africa and locally reduced ozone brought about by convective lifting of unpolluted boundary-layer air. Expanding to a 4 × 4 self-organizing map shows how biomass burning influences the yearly cycle of tropospheric ozone at Ascension Island and captures the seasonality of ozone at both Ascension Island and Natal. Comparing Ascension Island and Natal using a 4 × 4 self-organizing map at each site reveals similarities in mid-tropospheric ozone, but shows differences in lower-tropospheric ozone due to Ascension Island being closer to African biomass burning and more affected by descent from the mean Walker circulation, with less convective activity, than Natal.

algorithms↗

The Development of Two Science Investigator-led Processing Systems (SIPS) for NASA's Earth Observation System (EOS)

In 2001, NASA Goddard Space Flight Center's Laboratory for Terrestrial Physics started the construction of a science Investigator-led Processing System (SIPS) for processing data from the Ozone Monitoring Instrument (OMI) which will launch on the Aura platform in mid 2004. The Ozone Monitoring Instrument (OMI) is a contribution of the Netherlands Agency for Aerospace Programs (NIVR) in collaboration with the Finnish Meteorological Institute (FMI) to the Earth Observing System (EOS) Aura mission. It will continue the Total Ozone Monitoring System (TOMS) record for total ozone and other atmospheric parameters related to ozone chemistry and climate. OMI measurements will be highly synergistic with the other instruments on the EOS Aura platform. The LTP previously developed the Moderate Resolution Imaging Spectrometer (MODIS) Data Processing System (MODAPS), which has been in full operations since the launches of the Terra and Aqua spacecrafts in December, 1999 and May, 2002 respectively. During that time, it has continually evolved to better support the needs of the MODIS team. We now run multiple instances of the system managing faster than real time reprocessings of the data as well as continuing forward processing. The new OMI Data Processing System (OMIDAPS) was adapted from the MODAPS. It will ingest raw data from the satellite ground station and process it to produce calibrated, geolocated higher level data products. These data products will be transmitted to the Goddard Distributed Active Archive Center (GDAAC) instance of the Earth Observing System (EOS) Data and Information System (EOSDIS) for long term archive and distribution to the public. The OMIDAPS will also provide data distribution to the OMI Science Team for quality assessment, algorithm improvement, calibration, etc. We have taken advantage of lessons learned from the MODIS experience and software already developed for MODIS. We made some changes in the hardware system organization, database and software to adapt the system for OMI. We replaced the fundamental database system, Sybase, with an Open Source RDBMS called PostgreSQL, and based the entire OMIDAPS on a cluster of Linux based commodity computers rather than the large SGI servers that MODAPS uses. Rather than relying on a central I/O server host, the new system distributes its data archive among multiple server hosts in the cluster. OMI is also customizing the graphical user interfaces and reporting structure to more closely meet the needs of the OMI Science Team. Prior to 2003, simulated OMI data and the science algorithms were not ready for production testing. We initially constructed a prototype system and tested using a 25 year dataset of Total Ozone Mapping Spectrometer (TOMS) and Solar Backscatter Ultraviolet Instrument (SBUV) data. This prototype system provided a platform to support the adaptation of the algorithms for OMI, and provided reprocessing of the historical data aiding in its analysis. In a recent reanalysis of the TOMS data, the OMIDAPS processed 108,000 full orbits of data through 4 processing steps per orbit, producing about 800,000 files (400 GiB) of level 2 and greater data files. More recently we have installed two instances of the OMIDAPS for integration and testing of OM1 science processes as they get delivered from the Science Team. A Test instance of the OMIDAPS has also supported a series of "Interface Confidence Tests" (ICTs) and End-to-End Ground System tests to ensure the launch readiness of the system. This paper will discuss the high-level hardware, software, and database organization of the OMIDAPS and how it builds on the MODAPS heritage system. It will also provide an overview of the testing and implementation of the production OMIDAPS.

Tilmes, Curt↗

UWB Tracking Software Development

An Ultra-Wideband (UWB) two-cluster Angle of Arrival (AOA) tracking prototype system is currently being developed and tested at NASA Johnson Space Center for space exploration applications. This talk discusses the software development efforts for this UWB two-cluster AOA tracking system. The role the software plays in this system is to take waveform data from two UWB radio receivers as an input, feed this input into an AOA tracking algorithm, and generate the target position as an output. The architecture of the software (Input/Output Interface and Algorithm Core) will be introduced in this talk. The development of this software has three phases. In Phase I, the software is mostly Matlab driven and calls C++ socket functions to provide the communication links to the radios. This is beneficial in the early stage when it is necessary to frequently test changes in the algorithm. Phase II of the development is to have the software mostly C++ driven and call a Matlab function for the AOA tracking algorithm. This is beneficial in order to send the tracking results to other systems and also to improve the tracking update rate of the system. The third phase is part of future work and is to have the software completely C++ driven with a graphics user interface. This software design enables the fine resolution tracking of the UWB two-cluster AOA tracking system.

Gross, Julia↗

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

Shameldin, Ramez Ahmed↗

Efficient Implementation for Unitary Coupled Cluster State Preparation for Near-Term Quantum Computers

Unitary coupled cluster theory (UCC) is a common wave function ansatz for quantum simulation of molecular electronic structure using the variational quantum eigenvalue solver (VQE). Even for small molecules using a double-ζ basis, the number of variational parameters required to minimize the electronic energy (i.e., optimize the circuit) is large and beyond the reach of current quantum computers. For example, a circuit simulating C2 using the UCCSD ansatz and the cc-pVDZ basis set with frozen-core will require over 10,000 variational parameters and a Hilbert space of over 10^(8) determinants. To make progress on simulating such molecular systems on near-term quantum computers, we explore how much of the optimization can be approximately prepared with classical simulation while reducing the number of optimization steps performed on a quantum device. Recently, Chen, Cheng, and Freericks [J. Chem. Theory Comput. 2021, 17, 841-847] presented an algorithm for the factorized form of the UCC ansatz that allows for efficient UCC optimizations on classical hardware. We flip the algorithm around and use it to prepare approximate quantum circuits for systems that require a large number of qubits to represent. We will present results from our implementation and discuss strategies for incorporating this implementation for algorithms involving near-term quantum computers.

Quantum Computing↗

Efficient Implementation for Unitary Coupled Cluster State Preparation for Near-Term Quantum Computers

Unitary coupled cluster theory (UCC) is a common wave function ansatz for quantum simulation of molecular electronic structure using the variational quantum eigenvalue solver (VQE). Even for small molecules using a double-ζ basis, the number of variational parameters required to minimize the electronic energy (i.e., optimize the circuit) is large and beyond the reach of current quantum computers. For example, a circuit simulating C2 using the UCCSD ansatz and the cc-pVDZ basis set with frozen-core will require over 10,000 variational parameters and a Hilbert space of over 10^(8) determinants. To make progress on simulating such molecular systems on near-term quantum computers, we explore how much of the optimization can be approximately prepared with classical simulation while reducing the number of optimization steps performed on a quantum device. Recently, Chen, Cheng, and Freericks [J. Chem. Theory Comput. 2021, 17, 841-847] presented an algorithm for the factorized form of the UCC ansatz that allows for efficient UCC optimizations on classical hardware. We flip the algorithm around and use it to prepare approximate quantum circuits for systems that require a large number of qubits to represent. We will present results from our implementation and discuss strategies for incorporating this implementation for algorithms involving near-term quantum computers.

Quantum Computing↗