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At least 1,765 records · Page 98

Biclique: an R package for maximal biclique enumeration in bipartite graphs

Bipartite graphs are widely used to model relationships between pairs of heterogeneous data types. Maximal bicliques are foundational structures in such graphs, and their enumeration is an important task in systems biology, epidemiology and many other problem domains. Thus, there is a need for an efficient, general purpose, publicly available tool to enumerate maximal bicliques in bipartite graphs. The statistical programming language R is a logical choice for such a tool, but until now no R package has existed for this purpose. Our objective is to provide such a package, so that the research community can more easily perform this computationally demanding task. Biclique is an R package that takes as input a bipartite graph and produces a listing of all maximal bicliques in this graph. Input and output formats are straightforward, with examples provided both in this paper and in the package documentation. Biclique employs a state-of-the-art algorithm previously developed for basic research in functional genomics.

97 MATHEMATICS AND COMPUTING↗

Block-structured, equal-workload, multi-grid-nesting interface for the Boussinesq wave model FUNWAVE-TVD (Total Variation Diminishing)

Abstract. We describe the development of a block-structured, equal-CPU-load (central processing unit), multi-grid-nesting interface for the Boussinesq wave model FUNWAVE-TVD (Fully Nonlinear Boussinesq Wave Model with Total Variation Diminishing Solver). The new model framework does not interfere with the core solver, and thus the core program, FUNWAVE-TVD, is still a standalone model used for a single grid. The nesting interface manages the time sequencing and two-way nesting processes between the parent grid and child grid with grid refinement in a hierarchical manner. Workload balance in the MPI-based (message passing interface) parallelization is handled by an equal-load scheme. A strategy of shared array allocation is applied for data management that allows for a large number of nested grids without creating additional memory allocations. Four model tests are conducted to verify the nesting algorithm with assessments of model accuracy and the robustness in the application in modeling transoceanic tsunamis and coastal effects.

Choi, Young-Kwang↗

Atmospheric and surface temperatures and airborne dust amounts during late southern summer from Mariner 9 IRIS data

The temperature structure and dust loading of the Martian atmosphere are investigated using thermal emission spectra recorded in 1972 by the Mariner 9 infrared interferometer spectrometer (IRIS). The analysis focuses on a subset of data consisting of approximately 2400 spectra obtained near the end of the southern summer season (L(sub s) equal to 343 deg to 348 deg), after the global dust storm had largely abated and airborne dust amounts were subsiding to background values. Simultaneous retrieval of the vertical distribution of both atmospheric temperature and dust optical depth is accomplished through an iterative procedure which is performed on each individual spectrum. The atmospheric transmittances are calculated using a Voigt quasi-random band model, which includes absorption by CO2 and dust, but neglects the effects of multiple scattering. Vertical profiles of temperature and dust optical depth are obtained using modified algorithms. These profiles are used to construct global maps of temperature and dust optical depth as functions of latitude (+/- 90 deg), altitude (approximately 0-50 km), and local time of day.

Santee, M.↗

Model Checking - My 27-Year Quest to Overcome the State Explosion Problem

Model Checking is an automatic verification technique for state-transition systems that are finite=state or that have finite-state abstractions. In the early 1980 s in a series of joint papers with my graduate students E.A. Emerson and A.P. Sistla, we proposed that Model Checking could be used for verifying concurrent systems and gave algorithms for this purpose. At roughly the same time, Joseph Sifakis and his student J.P. Queille at the University of Grenoble independently developed a similar technique. Model Checking has been used successfully to reason about computer hardware and communication protocols and is beginning to be used for verifying computer software. Specifications are written in temporal logic, which is particularly valuable for expressing concurrency properties. An intelligent, exhaustive search is used to determine if the specification is true or not. If the specification is not true, the Model Checker will produce a counterexample execution trace that shows why the specification does not hold. This feature is extremely useful for finding obscure errors in complex systems. The main disadvantage of Model Checking is the state-explosion problem, which can occur if the system under verification has many processes or complex data structures. Although the state-explosion problem is inevitable in worst case, over the past 27 years considerable progress has been made on the problem for certain classes of state-transition systems that occur often in practice. In this talk, I will describe what Model Checking is, how it works, and the main techniques that have been developed for combating the state explosion problem.

Clarke, Ed↗

Group Structure Machine Learning Proposal

Nuclear data is the linchpin underwriting several fundamental capabilities and mission needs at LANL. New techniques such as machine learning can be brought to bear to solve old problems such as multigroup cross-section accuracy. In neutron transport, generating multigroup cross sections is a complex and arcane task, but a crucial one, as accurate solutions require appropriate cross sections. There are two key challenges when generating multigroup cross sections: (1) choosing an accurate weight function, and (2) choosing appropriate energy boundaries. Often, energy boundaries are chosen using “expert judgment” that is not documented and is difficult to replicate. The long-standing Los Alamos 30-group structure has been in use since at least 1969 and is still in use today. Simplistic attempts over the years since to improve on the 30-group structure have been met with limited success. Machine learning algorithms would enable the selection of appropriate, problem-dependent group boundaries without an inordinate investment of scientist time. We will develop workflows and tools to enable these improved group boundary choices, which will reduce uncertainty and increase predictive capability of neutron-transport applications at LANL.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

VCL Laser Altimeter Surface Return Expected Geolocation Performance

The Vegetation Canopy Lidar (VCL) mission, expected to launch in the spring of 2002, will carry a unique Multi-Beam Laser Altimeter (MBLA) instrument designed to observe vegetative canopy structure for a nominal mission duration of 2 years. The VCL MBLA is a three-beam instrument where each laser is capable of producing returns with 30-m along-track spacing and 25-m-diameter footprints. Identifying the precise location of the point on the Earth's surface from which the laser energy reflects is a critical issue in the validation and application of the data. The resultant geolocation accuracy is dependent on the performance of many components of the VCL system including: laser pulse round trip travel time observation to surface, navigation tracking data, attitude determination system data, timing, laser pointing and body orientation stability, knowledge of instrument and navigation tracking point positions, media and geophysical corrections. Additionally, it is critical to calibrate on-orbit instrument parameters including pointing and range corrections. The geolocation and calibration methodology and algorithms will be summarized. A detailed geolocation error analysis identifying the contributions from each system component, along with the resultant expected geolocation accuracy, will be presented. A brief discussion of the operational geolocation process will also be presented. Science and data validation implications from geolocation performance will be summarized.

Luthcke, S. B.↗

An Overview of Unsteady Three-Dimensional Navier-Stokes Simulations of Multistage Turbomachinery Flows

Fluid dynamics of turbomachines are complicated by inherently three dimensional structures such as endwall boundary layers, hub corner separation bubbles and tip-leakage flows. In addition, the relative motion between rotors and stators causes unsteady aerodynamic interactions to occur between blade rows. It is necessary to understand the aerodynamics associated with these interactions in order to design turbomachines that are both light and compact as well as reliable and efficient. An unsteady, three-dimensional, thin-layer, Navier-Stokes zonal algorithm is used to investigate the unsteady aerodynamics of multi-stage turbines and compressors. Relative motion between rotors and stators is made possible by the use of systems of patched and overlaid grids. Time-averaged pressures and pressure envelopes have been computed for several two- and three-dimensional single- and multi-stage configurations. Flow visualizations and computed results are in good agreement with experimental data.

Gundy-Burlet, Karen L.↗

Computing the effective elasticity of anisotropic porous media from X-ray computed micro-tomography images

Development and optimization of composite materials designed for thermal protection of NASA’s spacecraft requires the understanding of their physical response to high-enthalpy environments. To predict their macro-scale properties and behavior, high-fidelity 3D simulations are performed at the micro-scale on realistic representations of these composites. The digital micro-structures are generated either synthetically or through X-ray micro-tomography reconstructions. One of the main challenges in the prediction of heatshield material structural response is the computation of the effective elasticity of the fibrous composite, as well as the understanding of the deformation and stresses generated at the micro-scale. These are driven by the fiber layout within the micro-structure and the distribution of the infused matrix. In this effort, the micro-mechanical linear elastic behavior of fibrous ablators is modeled through the use of a numerical method based on the Multi-Point Stress Approximation (MPSA) finite volume scheme. The MPSA, a generalization of the more commonly used Multi-Point Flux Approximation (MPFA), was discussed in a previous presentation at the 15th USCCN and in reference. To predict the behavior of fibrous and woven architectures, algorithms that compute the local fiber orientation are used. The implementation of the MPSA was verified using analytical solutions, engineering test cases and compared against legacy Finite Element Analysis (FEA) software. The stress analysis models were then applied to real geometries used by NASA in thermal protection systems such as fibrous preforms and woven materials and the results were compared to experimental data.

Federico Semeraro↗

MCS+: An Efficient Algorithm for Crawling the Community Structure in Multiplex Networks

In this article, we consider the problem of crawling a multiplex network to identify the community structure of a layer-of-interest. A multiplex network is one where there are multiple types of relationships between the nodes. In many multiplex networks, some layers might be easier to explore (in terms of time, money etc.). We propose MCS+, an algorithm that can use the information from the easier to explore layers to help in the exploration of a layer-of-interest that is expensive to explore. We consider the goal of exploration to be generating a sample that is representative of the communities in the complete layer-of-interest. This work has practical applications in areas such as exploration of dark (e.g., criminal) networks, online social networks, biological networks, and so on. For example, in a terrorist network, relationships such as phone records, e-mail records, and so on are easier to collect; in contrast, data on the face-to-face communications are much harder to collect, but also potentially more valuable. We perform extensive experimental evaluations on real-world networks, and we observe that MCS+ consistently outperforms the best baseline—the similarity of the sample that MCS+ generates to the real network is up to three times that of the best baseline in some networks. We also perform theoretical and experimental evaluations on the scalability of MCS+ to network properties, and find that it scales well with the budget, number of layers in the multiplex network, and the average degree in the original network.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

AMReX: Block-structured adaptive mesh refinement for multiphysics applications

Block-structured adaptive mesh refinement (AMR) provides the basis for the temporal and spatial discretization strategy for a number of Exascale Computing Project applications in the areas of accelerator design, additive manufacturing, astrophysics, combustion, cosmology, multiphase flow, and wind plant modeling. AMReX is a software framework that provides a unified infrastructure with the functionality needed for these and other AMR applications to be able to effectively and efficiently utilize machines from laptops to exascale architectures. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving accurate descriptions of different physical processes in complex multiphysics algorithms. AMReX supports algorithms that solve systems of partial differential equations in simple or complex geometries and those that use particles and/or particle–mesh operations to represent component physical processes. In this article, we will discuss the core elements of the AMReX framework such as data containers and iterators as well as several specialized operations to meet the needs of the application projects. In addition, we will highlight the strategy that the AMReX team is pursuing to achieve highly performant code across a range of accelerator-based architectures for a variety of different applications.

Zhang, Weiqun↗

Prospects of the ICESat-2 Laser Altimetry Mission for Savanna Ecosystem Structural Studies Based on Airborne Simulation Data

The next planned spaceborne lidar mission is the Ice, Cloud and land Elevation Satellite 2 (ICESat-2), which will use the Advanced Topographic Laser Altimeter System (ATLAS) sensor, a photon counting technique. To pre-validate the capability of this mission for studying three dimensional vegetation structure in savannas, we assessed the potential of the measurement approach to estimate canopy height in an oak savanna landscape. We used data from the Multiple Altimeter Beam Experimental Lidar (MABEL), an airborne photon counting lidar sensor developed by NASA's Goddard Space Flight Center. ATLAS-like data was generated using the MATLAS simulator, which adjusts MABEL data's detected number of signal and noise photons to that expected from the ATLAS instrument. Transects flown over the Tejon ranch conservancy in Kern County, California, USA were used for this work. For each transect we chose to use data from the near infrared channel that had the highest number of photons. We segmented each transect into 50 m, 25 m and 14 m long blocks and aggregated the photons in each block into a histogram based on their elevation values. We then used an automated algorithm to identify cut off points where the cumulative density of photons from the highest elevation indicates the presence of the canopy top and likewise where such cumulative density from the lowest elevation indicates the mean terrain elevation. MABEL derived height metrics were moderately correlated to discrete return lidar (DRL) derived height metrics r(sub 2) and RMSE values ranging from 0.60 to 0.73 and 2.9 m to 4.4 m respectively) but MATLAS simulation resulted in more modest correlations with DRL indices r(sub 2) ranging from 0.5 to 0.64 and RMSE from 3.6 m to 4.6 m). Simulations also indicated that the expected number of signal photons from ATLAS will be substantially lower, a situation that reduces canopy height estimation precision especially in areas of low density vegetation cover. On the basis of the simulated data, there is reason to believe that the ability of ICESat-2 to estimate height in savannas will be comparable to the original ICESat mission although the respective sensors have different measurement principles.

Gwenzi, David↗

Spectral function for 4 He using the Chebyshev expansion in coupled-cluster theory

Here, we compute spectral function for 4 He by combining coupled-cluster theory with an expansion of integral transforms into Chebyshev polynomials. Our method allows us to estimate the uncertainty of spectral reconstruction. The properties of the Chebyshev polynomials make the procedure numerically stable and considerably lower in memory usage than the typically employed Lanczos algorithm. We benchmark our predictions with other calculations in the literature and with electron-scattering data in the quasi-elastic peak. The spectral function formalism allows one to extend ab initio lepton-nucleus cross sections into the relativistic regime. This makes it a promising tool for modeling this process at higher-energy transfers. The results we present open the door for studies of heavier nuclei, important for the neutrino oscillation programs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Beyond carbon flux partitioning: Carbon allocation and nonstructural carbon dynamics inferred from continuous fluxes

Carbon (C) allocation and nonstructural carbon (NSC) dynamics play essential roles in plant growth and survival under stress and disturbance. However, quantitative understanding of these processes remains limited. Here, in this work, we propose a framework where we connect commonly measured carbon cycle components (eddy covariance fluxes of canopy CO 2 exchange, soil CO 2 efflux, and allometry-based biomass and net primary production) by a simple mass balance model to derive ecosystem-level NSC dynamics (NSC i ), C translocation (dC i ), and the biomass production efficiency (BPE i ) in above- and belowground plant (i = agp and bgp) compartments. We applied this framework to two long-term monitored loblolly pine (Pinus taeda) plantations of different ages in North Carolina and characterized the variations of NSC and allocation in years under normal and drought conditions. The results indicated that the young stand did not have net NSC flux at the annual scale, whereas the mature stand stored a near-constant proportion of new assimilates as NSC every year under normal conditions, which was comparable in magnitude to new structural growth. Roots consumed NSC in drought and stored a significant amount of NSC post drought. The above- and belowground dC i and BPE i varied more from year to year in the young stand and approached a relatively stable pattern in the mature stand. The belowground BPE bgp differed the most between the young and mature stands and was most responsive to drought. With the internal C dynamics quantified, this framework may also improve biomass production estimation, which reveals the variations resulting from droughts. Overall, these quantified ecosystem-scale dynamics were consistent with existing evidence from tree-based manipulative experiments and measurements and demonstrated that combining the continuous fluxes as proposed here can provide additional information about plant internal C dynamics. Given that it is based on broadly available flux data, the proposed framework is promising to improve the allocation algorithms in ecosystem C cycle models and offers new insights into observed variability in soil–plant–climate interactions.

54 ENVIRONMENTAL SCIENCES↗

Stiffness-generated rigid-body mode shapes for Lanczos eigensolution with SUPORT DOF by way of a MSC/NASTRAN DMAP alter

When using all MSC/NASTRAN eigensolution methods except Lanczos, the analyst can replace the coupled system rigid-body modes calculated within DMAP module READ with mass orthogonalized and normalized rigid-body modes generated from the system stiffness. This option is invoked by defining MSC/NASTRAN r-set degrees of freedom via the SUPORT bulk data card. The newly calculated modes are required if the rigid-body modes calculated by the eigensolver are not 'clean' due to numerical roundoffs in the solution. When performing transient structural dynamic load analysis, the numerical roundoffs can result in inaccurate rigid-body accelerations which affect steady-state responses. Unfortunately, when using the Lanczos method and defining r-set degrees of freedom, the rigid-body modes calculated within DMAP module REIGL are retained. To overcome this limitation and to allow MSC/NASTRAN to handle SUPORT degrees of freedom identically for all eigensolvers, a DMAP Alter has been written which replaces Lanczos-calculated rigid-body modes with stiffness-generated rigid-body modes. The newly generated rigid-body modes are normalized with respect to the system mass and orthogonalized using the Gram-Schmidt technique. This algorithm has been implemented as an enhancement to an existing coupled loads methodology.

Abdallah, Ayman A.↗

An Objective Classification of Saturn Cloud Features from Cassini ISS Images

A k -means clustering algorithm is applied to Cassini Imaging Science Subsystem continuum and methane band images of Saturn's northern hemisphere to objectively classify regional albedo features and aid in their dynamical interpretation. The procedure is based on a technique applied previously to visible- infrared images of Earth. It provides a new perspective on giant planet cloud morphology and its relationship to the dynamics and a meteorological context for the analysis of other types of simultaneous Saturn observations. The method identifies 6 clusters that exhibit distinct morphology, vertical structure, and preferred latitudes of occurrence. These correspond to areas dominated by deep convective cells; low contrast areas, some including thinner and thicker clouds possibly associated with baroclinic instability; regions with possible isolated thin cirrus clouds; darker areas due to thinner low level clouds or clearer skies due to downwelling, or due to absorbing particles; and fields of relatively shallow cumulus clouds. The spatial associations among these cloud types suggest that dynamically, there are three distinct types of latitude bands on Saturn: deep convectively disturbed latitudes in cyclonic shear regions poleward of the eastward jets; convectively suppressed regions near and surrounding the westward jets; and baro-clinically unstable latitudes near eastward jet cores and in the anti-cyclonic regions equatorward of them. These are roughly analogous to some of the features of Earth's tropics, subtropics, and midlatitudes, respectively. This classification may be more useful for dynamics purposes than the traditional belt-zone partitioning. Temporal variations of feature contrast and cluster occurrence suggest that the upper tropospheric haze in the northern hemisphere may have thickened by 2014. The results suggest that routine use of clustering may be a worthwhile complement to many different types of planetary atmospheric data analysis.

atmosphere dynamics↗

Transactional Knowledge Graph Generation To Model Adversarial Activities

A Knowledge Graph (KG) is a formal and structured representation of facts, relationships, and semantic descriptions of a set of entities. Traditionally, KGs are used to describe metadata about entities and to provide additional context to target application results. Many real-world domains also involve temporal interactions between entities in addition to the metadata data. Modeling these attributed transactions is a critical requirement when using KGs in complex real-world applications. Modeling adversarial activities is one such application that develops methodology and tools to produce realistic large-scale background activity graphs that include embedded Weapons of Mass Destruction (WMD) activity patterns. We present a novel platform for constructing a transactional knowledge graph from a diverse set of sources. We present the core components and architecture of the framework, and a use case for generating a background knowledge graph and WMD activity template to evaluate network alignment and subgraph matching algorithms.

Purohit, Sumit↗

Development of NDE/NDT Tools for High-Volume & High-Speed Inspection of CFRP Structures in Automotive Manufacturing

Main advantages of the air-coupled ultrasound testing (ACUT) and electromagnetic testing (EMT) techniques for NDE of CFRP composites were non-contact sensing, scalability for high-speed inspection, cost-effectiveness, and non-hazardous operation. Despite these advantages, no systems that would satisfy the project requirements were commercially available. Hence, one of the major efforts of the Michigan State University (MSU) team at the initial stage of the project was to close this technological gap by developing, optimizing, and validating array sensors that would provide sufficient sensitivity, spatial coverage, and resolution for robust defect detection. Optimization of the ACUT and EMT sensor designs was performed using experimentally validated finite element models. Initial experiments using array probes were conducted on relatively flat CFRP samples. In parallel, the MSU team designed and assembled a portable platform with two robotic arms. The robots were equipped with newly designed sensors that enabled high-speed NDE of curved CFRP parts. Presently, the developed robotic platform can be used as a demo/template NDE system, which is easily adaptable to manufacturing environments and in-line NDE. The ACUT NDE system developed by the MSU team used a high-power 4-channel pulser receiver for parallel data acquisition. The array probes were designed by stacking commercially available ACUT transducers, which operated in the frequency range between 100 kHz and 500 kHz. MSU optimized the excitation procedure and developed wave focusing cones so as to reduce the crosstalk between the transducers and to provide higher pulse repletion frequency (PRF). The through-transmission (TT) and single-side access (SSA) inspection modes were successfully implemented. In the TT-ACUT, structural defects in CFRP were detected by passing ultrasonic waves through the test part. Hence, the ACUT transmitters and receivers needed to be placed on the opposite sides of the test part. In the SSA-ACUT, guided waves (GW) were excited in the test part using the transmitters and were sensed by the receivers from the same side. Multi-channel TT-ACUT and SSA-ACUT provided high-speed NDE, and were successfully validated on CFRP test samples with interlaminar delaminations and other embedded defects The EM techniques developed by the MSU team included: 1) eddy current testing (ECT), 2) capacitive imaging (CI) and hybrid dual-mode imaging. In ECT, structural damage was detected in CFRP using coils sensor arrays. In ECT, the excitation magnetic field is generated by passing an alternating current through a coil, which is placed above the test sample. The excitation field penetrates the conductive sample and induces the eddy currents in its transect. In turn, the eddy currents generate the reaction field, which affects the total field sensed by a coil. Hence, the presence of structural flaws will alter the eddy current flow and the picked-up signal. ECT is mostly sensitive to local changes of the electric conductivity of the test sample, and CFRPs are mostly conductive in the direction of carbon fibers. Hence, ECT was well suited for the detection of fiber damage/fiber irregularities. The MSU team developed printed circuit boards (PCB) with coil sensor arrays optimized for NDE of CFRP. Unlike most commercial probes designed for ECT of metallic structures, the MSU array probes were designed for operation in [1-10] MHz frequency range, which was optimal for low-conductive CFRP. Multiple sensing topologies (coil groups excitation/sensing arrangements) were implemented and successfully validated. Capacitive Imaging (CI) technique developed by MSU was complementary to ECT. In contrast to ECT, which was sensitive to local changes of the electrical conductivity, the CI was sensitive to local changes of the dielectric constant. Therefore, CI could provide information about matrix damage/matrix irregularities in CFRP. The MSU CI sensor arrays were made of multiple circular or rectangular open-plate capacitors printed on PCB. Sensors of this type are not commercially available. In addition to ECT and CI, the MSU team developed a hybrid (dual-mode) inductive/capacitive measurement technique that synergistically combined the benefits of inductive and capacitive sensing for rapid NDE of fiber reinforced polymer (FRP) composite structures. Fiber damage and fiber irregularities in FRPs were detected by configuring hybrid sensors as coil sensors. Similarly, matrix damage, matrix irregularities and interlaminar delaminations were detected by configuring hybrid sensors as capacitive sensors. ECT and CI were performed sequentially by means of electronic switching. Hence, eliminating the need for mounting two separate sensor arrays on the probe. Portable robotic platform was developed by MSU for multi-technique high-speed NDE of CFRP test parts. The platform had two 6-axis robots, which enabled inspection of curved parts in approximately a 6×6×6 ft 3 active scan area. On the software side, the MSU team integrated scripts for NDE hardware control with scripts for robot motion control. MSU also implemented automated path planning for the robots, reconstruction of part’s surfaces via stereovision, 3D rendering of inspection data, and image processing algorithms for enhanced defect detection. Automotive composite parts manufactured by Plasan Composites from Phase I were used to validate the ACUT and EMT techniques on representative testbeds. Among those parts were three X-braces for a Dodge Viper, one composite calibration plaque with known defects at known locations, and four other test sections, including sections from a front splitter, a corner section from a composite hood, and a high-pressure RTM panel made using non crimp fabric. Other test samples included CFRP and GFRP calibration plates with fiber/matrix defects fabricated at MSU/CVRC.

36 MATERIALS SCIENCE↗

Performance analysis of a large-grain dataflow scheduling paradigm

A paradigm for scheduling computations on a network of multiprocessors using large-grain data flow scheduling at run time is described and analyzed. The computations to be scheduled must follow a static flow graph, while the schedule itself will be dynamic (i.e., determined at run time). Many applications characterized by static flow exist, and they include real-time control and digital signal processing. With the advent of computer-aided software engineering (CASE) tools for capturing software designs in dataflow-like structures, macro-dataflow scheduling becomes increasingly attractive, if not necessary. For parallel implementations, using the macro-dataflow method allows the scheduling to be insulated from the application designer and enables the maximum utilization of available resources. Further, by allowing multitasking, processor utilizations can approach 100 percent while they maintain maximum speedup. Extensive simulation studies are performed on 4-, 8-, and 16-processor architectures that reflect the effects of communication delays, scheduling delays, algorithm class, and multitasking on performance and speedup gains.

Young, Steven D.↗