Inherent Parallelism and Speedup Estimation of Sequential Programs

Although several automated Parallel Conversion solutions are available, very few have attempted, to provide proper estimates of the available Inherent Parallelism and expected Parallel Speedup. CALIPER which is the outcome of this research work is a parallel performance estimation technology that can fill this void. High level language structures such as Functions, Loops, Conditions, etc which ease program development, can be a hindrance for effective performance analysis. We refer to these program structures as the Program Shape. As a preparatory step, CALIPER attempts to remove these shape related hindrances, an activity we refer to as Program Shape Flattening. Programs are also characterized by dependences that exist between different instructions and impose an upper limit on the parallel conversion gains. For parallel estimation, we first group instructions that share dependences, and add them to a class we refer to as Dependence Class or Parallel Class. While instructions belonging to a class run sequentially, the classes themselves run in parallel. Parallel runtime, is now the runtime of the class that runs the longest. We report performance estimates of parallel conversion as two metrics. The inherent parallelism in the program is reported, as Maximum Available Parallelism (MAP) and the speedup after conversion as Speedup After Parallelization (SAP).

Formation of the secondary species range of the invasive mollusk Arion lusitanicus sensu lato in Chernivtsi Region

Invasions of species into ecosystems lead to their transformation and in some cases to degradation. The spanish slug Arion lusitanicus Mabille, 1868 (Mollusca: Gastropoda: Stylommatophora: Arionidae) has been spread actively in Europe including some regions of Ukraine recently. This is a dangerous invasive species that causes significant damage to natural and agroecosystems. There is a lack of nformation on the distribution of the species in Chernivtsi region. Therefore, the aim of the work was to assess the current distribution and allocation of the boundaries of the secondary range of Arion lusitanicus sensu lato in Chernivtsi Region. Data on the spread of A. lusitanicus in the region have been obtained from the website of the National Biodiversity Information Network UkrBIN, as well as collected in the field during 2016-2019 and by surveying residents of settlements of Chernivtsi region. Estimation of A. lusitanicus populations density in selected localities has been performed applying the method of total collection and direct in situ calculation with parallel estimation of habitat area. The mapping method in Quantum GIS was used to present the cartographic material. As a result, it has been found that A. lusitanicus was recorded for the first time from Chernivtsi region in 2011–2012 in the city of Chernivtsi (Rosha district) and in the Novoselytsia district. The uneven spatial distribution of A. lusitanicus mollusk colonies on the territory of Chernivtsi region has been shown: the maximum number of localities within urban settlements and the absence of species on alpine and certain steppe territories. It has been noted that the boundaries A. lusitanicus range in Chernivtsi region are confined to the territory with an altitude of 350 m above sea level and are transitive, indicating the active spreading of the species.

A Parallel Estimation System of Stator Resistance and Rotor Speed for Active Disturbance Rejection Control of Six-Phase Induction Motor

In this paper, a parallel estimation system of the stator resistance and the rotor speed is proposed in speed sensorless six-phase induction motor (6PIM) drive. First, a full-order observer is presented to provide the stator current and the rotor flux. Then, an adaptive control law is designed using the Lyapunov stability theorem to estimate the rotor speed. In parallel, a stator resistance identification scheme is proposed using more degrees of freedom of the 6PIM, which is also based on the Lyapunov stability theorem. The main advantage of the proposed method is that the stator resistance adaptation is completely decoupled from the rotor speed estimation algorithm. To increase the robustness of the drive system against external disturbances, noises, and parameter uncertainties, an active disturbance rejection controller (ADRC) is introduced in direct torque control (DTC) of the 6PIM. The experimental results clarify the effectiveness of the proposed approaches.

Tracking Multiple Marine Ships via Multiple Sensors with Unknown Backgrounds

In multitarget tracking, knowledge of the backgrounds plays a crucial role in the accuracy of the tracker. Clutter and detection probability are the two essential background parameters which are usually assumed to be known constants although they are, in fact, unknown and time varying. Incorrect values of these parameters lead to a degraded or biased performance of the tracking algorithms. This paper proposes a method for online tracking multiple targets using multiple sensors which jointly adapts to the unknown clutter rate and the probability of detection. An effective filter is developed from parallel estimation of these parameters and then feeding them into the state-of-the-art generalized labeled multi-Bernoulli filter. Provided that the fluctuation of these unknown backgrounds is slowly-varying in comparison to the rate of measurement-update data, the validity of the proposed method is demonstrated via numerical study using multistatic Doppler data.

A Fusion Method of Point-Cloud Based on Parallel Estimation of Distribution Algorithm

The paper proposes a new method that utilizes Parallel Estimation of Distribution (PED) to obtain disparity map of two images and fuses 3D point-cloud by the disparity. Estimation of Distribution (ED) has several advantages such as low complexity and high efficiency while it also has the shortcoming that it’s sensitive to initial samples and the final solution is local optimum but global optimum. In order to exert its merit and overcome the shortcoming, this paper will improve the ED by parallel sampling to diminish the sensitivity with Adaptive Support-Weight method. We called it Parallel Estimation of Distribution (PED). After disparity map is obtained, the two images will be divided into high frequency and low frequency by lifting wavelet respectively and the frequency coefficient of each image will be averaged into fusion frequency. Finally, the fused frequency coefficient will be transformed by inverse lifting wavelet to the final fused image. The experiment has proved that the matching speed is outstanding without losing precision.