Sequential Merging Research Articles

Mesoscale Factors Contributing to the Extreme Rainstorm on 20 July 2021 in Zhengzhou, China, as Revealed by Rapid Update 4DVar Analysis

Abstract The purpose of this study is to diagnose mesoscale factors responsible for the formation and development of an extreme rainstorm that occurred on 20 July 2021 in Zhengzhou, China. The rainstorm produced 201.9 mm of rainfall in 1 h, breaking the record of mainland China for 1-h rainfall accumulation in the past 73 years. Using 2-km continuously cycled analyses with 6-min updates that were produced by assimilating observations from radar and dense surface networks with a four-dimensional variational (4DVar) data assimilation system, we illustrate that the modification of environmental easterlies by three mesoscale disturbances played a critical role in the development of the rainstorm. Among the three systems, a mesobeta-scale low pressure system (mesolow) that developed from an inverted trough southwest of Zhengzhou was key to the formation and intensification of the rainstorm. We show that the rainstorm formed via sequential merging of three convective cells, which initiated along the convergence bands in the mesolow. Further, we present evidence to suggest that the mesolow and two terrain-influenced flows near the Taihang Mountains north of Zhengzhou, including a barrier jet and a downslope flow, contributed to the local intensification of the rainstorm and the intense 1-h rainfall. The three mesoscale features coexisted near Zhengzhou in the several hours before the extreme 1-h rainfall and enhanced local wind convergence and moisture transport synergistically. Our analysis also indicated that the strong midlevel south/southwesterly winds from the mesolow along with the gravity-current-modified low-level northeasterly barrier jet enhanced the vertical wind shear, which provided favorable local environment supporting the severe rainstorm.

Practice of applying models of clustering of incoming semi-structured data in management systems

A scheme for solving the problem of binary clustering of incoming data in the control system is proposed. Different ways of presenting the initial data of the clustering problem are considered. Methods of sequential shortening and sequential merging of clusters and the model of initial placement of clusters are considered. Estimating the number of clusters is given to solve the clustering problem. A binary clustering method has been proposed for points in a circle. The clustering practice was performed based on the research results, and the developed model and algorithms were implemented. The optimal variant of the processing process based on clustering methods for semi-formed information sources is proposed based on the proposed structure.

Joinable Parallel Balanced Binary Trees

In this article, we show how a single function, join , can be used to implement parallel balanced binary search trees ( BSTs ) simply and efficiently. Based on join , our approach applies to multiple balanced tree data structures, and a variety of functions for ordered sets and maps. We describe our technique as an algorithmic framework called join-based algorithms . We show that the join function fully captures what is needed for rebalancing trees for a variety of tree algorithms, as long as the balancing scheme satisfies certain properties, which we refer to as joinable trees. We discuss four balancing schemes that are joinable: AVL trees, red-black trees, weight-balanced trees, and treaps. We present a variety of tree algorithms that apply to joinable trees, including insert , delete , union , intersection , difference , split , range , filter , and so on, most of them also parallel. These algorithms are generic across balancing schemes. Many algorithms are optimal in the comparison model, and we provide a general proof to show the efficiency in work for joinable trees. The algorithms are highly parallel, all with polylogarithmic span (parallel dependence). Specifically, the set-set operations union , intersection , and difference have work \( O(m\log (\frac{n}{m}+1)) \) and polylogarithmic span for input set sizes \( n \) and \( m\le n \) . We implemented and tested our algorithms on the four balancing schemes. In general, all four schemes have quite similar performance, but the weight-balanced tree slightly outperforms the others. They have the same speedup characteristics, getting around 73 \( \times \) speedup on 72 cores (144 hyperthreads). Experimental results also show that our implementation outperforms existing parallel implementations, and our sequential version achieves close or much better performance than the sequential merging algorithm in C++ Standard Template Library (STL) on various input sizes.

Clarification of the formation process of the super massive black hole by Infrared astrometric satellite, Small-JASMINE

AbstractSmall-JASMINE (hearafter SJ), infrared astrometric satellite, will measure the positions and the proper motions which are located around the Galactic center, by operating at near infrared wave-lengths. SJ will clarify the formation process of the super massive black hole (hearafter SMBH) at the Galactic center. In particular, SJ will determine whether the SMBH was formed by a sequential merging of multiple black holes. The clarification of this formation process of the SMBH will contribute to a better understanding of merging process of satellite galaxies into the Galaxy, which is suggested by the standard galaxy formation scenario. A numerical simulation (Tanikawa and Umemura, 2014) suggests that if the SMBH was formed by the merging process, then the dynamical friction caused by the black holes have influenced the phase space distribution of stars. The phase space distribution measured by SJ will make it possible to determine the occurrences of the merging process.

Perfectly Load-Balanced, Stable, Synchronization-Free Parallel Merge

We present a simple, work-optimal and synchronization-free solution to the problem of stably merging in parallel two given, ordered arrays of m and n elements into an ordered array of m+n elements. The main contribution is a new, simple, fast and direct algorithm that determines, for any prefix of the stably merged output array, the exact prefixes of each of the two input arrays needed to produce this output prefix. More precisely, for any given index in the resulting, but not yet constructed output array, representing the desired output prefix, the algorithm computes the indices (called co-ranks) in each of the two input arrays representing the required input prefixes without having to merge the input arrays. The co-ranking algorithm takes [Formula: see text] time steps, and uses O(1) space. Co-ranking is used in parallel to partition the input arrays into a collection of as many pairs as desired, each pair with exactly the same number of elements. Any stable, sequential merge algorithm can be used to merge pairs independently. The result is a perfectly load-balanced, stable, parallel merge algorithm. Co-ranking and sequential merging of pairs can be done without synchronization. Compared to other, linear speed-up approaches to the parallel merge problem, the algorithm is considerably simpler and can be up to a factor of two faster. Compared to previous algorithms for solving the co-ranking problem, the new algorithm works for arbitrary output array indices and maintains stability in the presence of repeated elements at no extra space or time cost. When the number of processing elements p does not exceed (m + n)/ log min(m, n), the parallel merge algorithm has perfect, linear speedup p. Furthermore, it is easy to implement on both shared and distributed memory systems.

Complex minimization method for finite state machines implemented on programmable logic devices

A complex method for the minimization of finite state machines (FSMs) implemented on Programmable Logic Devices (PLDs) is proposed. In this method, such optimization criteria as the cost of implementation, power consumption, and speed of operation are taken into account already at the stage of minimizing internal states. It also makes it possible to take into consideration the parameters of technology of integrated circuits and the state assignment method. In addition, the proposed method allows one to minimize the number of transitions and input variables of the FSM. The method is based on sequential merging of two internal states. For this purpose, the set of all pairs of states that can be merged is found, and the pair that best satisfies the optimization criteria is chosen for merging. Algorithms for the estimation of optimization criteria values are described, and some features of the computer implementation of the proposed method are discussed.

Triplet-based sequential merging approach to omnidirectional camera motion reconstruction

A frame grouping and merging scheme of sub-sequences to estimate precise camera motion parameters over long omnidirectional sequences is addressed. In this triplet-based approach, the back-projection errors of corresponding points by the camera model for grouping subsequences are used. This process accounts for the relative reliability of the estimated camera model in field of view. Experimental results show that the proposed method solves the problem inherent in sequential algorithm: its susceptibility to drift over long sequences.

Frame grouping for factorization-based reconstruction over long image sequences

For 3-D reconstruction from uncalibrated sequences, projective reconstruction is needed as a preceding step, which is classified into a merging method and factorization. Factorization-based methods generally suffer less from drift and error accumulation than sequential merging. However, they assume that most corresponding points must remain in all frames. To overcome this limitation, we present a new frame grouping method for factorization-based projective reconstruction over long image sequences. The proposed method breaks a full sequence into subsequences by considering a survival rate of the corresponding points over a sequence, the reprojection error, and the distribution of matching points on the image. All projective reconstructions in subsequences are registered into the same coordinate frame for a complete description of the scene. Experimental results demonstrate that our algorithm can recover more precise 3-D structure than the sequential merging method.

Merging on the BSP model

The design of complex parallel algorithms relies heavily on a set of primitive operations. In this work, we examine the problem of merging two sorted sequences in an architecture independent setting. We derive parallel algorithms that can be used on a variety of parallel machines and whose performance can be reliably predicted if these algorithms are analyzed under the bulk-synchronous parallel (BSP) model. While our algorithms are fairly simple themselves, description of their performance in terms of the BSP parameters is somewhat complicated. The main reward for quantifying these complications, is that it enables parallel software to be written once and for all that can be migrated efficiently among a variety of parallel platforms. The optimal merging algorithm presented in this work achieves asymptotically optimal parallel efficiency compared to any optimal sequential merging algorithm.

The collisionless coalescence instability with two-species and in-plane-current effects

The investigation by means of particle simulations of the process whereby magnetic island structures tend to merge into larger units is extended to include the effects of electron dynamics and the in-plane components of the currents. With the ions marginally unmagnetized (ρi/λ∼1, where ρi is the asymptotic ion gyroradius and λ is the current sheet half-thickness), the electrons reduce the linear growth rate by some 20%, but they do not alter the basic coalescence physics. During the nonlinear stage of the pairwise merging process, a quadrupole out-of-the-plane magnetic field structure with peak amplitude ∼0.1B0 is formed, but this field collapses after the merging is completed. In the parameter regime accessible to the simulations [flux bundle size L/(c/ωpi)≳3 and mass ratio Mi/me≤36], there is no indication of any significant change in the reconnection rate that could be associated with whistler-mediated reconnection. The sequential merging of 4 islands into one large island leads to the formation of a vacuum X point and substantial particle energization.

An optimal parallel algorithm for merging using multiselection

We consider the problem of merging two sorted arrays and on an exclusive read, exclusive write parallel random access machine (EREW PRAM, see [8] for a definition). Our approach consists of identifying elements in and which would have appropriate rank in the merged array. These elements partition the arrays and into equal-size subproblems which then can be assigned to each processor for sequential merging. Here, we present a novel parallel algorithm for selecting the required elements, which leads to a simple and optimal algorithm for merging in parallel. Thus, our technique differs from those of other optimal parallel algorithms for merging where the subarrays are defined by elements at fixed positions in and . Formally, the problem of selection can be stated as follows. Given two ordered multisets and of sizes and , where , the problem is to select the th smallest element in and combined. The problem can be solved sequentially in log time without explicitly merging and [5, 6]. Multiselection, a generalization of selection, is the problem where given a sequence of integers 1

Asynchronous parallel merging

An asynchronous scheduling strategy for use in conjunction with any sequential merging algorithm to implement an asynchronous parallel merging algorithm on an MIMD multiprocessor is presented. In particular, an asynchronous parallel implementation of the 2-way merge algorithm is described and used as a component in three versions of a parallel sorting algorithm. Their performance is compared when executed on the Sequent Balance 8000 multiprocessor.

Alternative Multidimensional Scaling Methods for Large Stimulus Sets

Seven data collection methods available for scaling large stimulus sets are evaluated via simulation under three scaling approaches, using data from a known configuration. Pick or order methods produced better recoveries than subjective methods, and grouping followed by sequential merging was superior to other grouping methods.