Parallel Time Research Articles

Learning From the Dark Side: A Parallel Time Series Modelling Framework for Forecasting and Fault Detection on Intelligent Vehicles

Learning From the Dark Side: A Parallel Time Series Modelling Framework for Forecasting and Fault Detection on Intelligent Vehicles

Proactive scheduling for steel plants with unrelated parallel machines and time uncertainty

This paper deals with the steel plant proactive scheduling problem with unrelated parallel machines and time uncertainty to enhance the rationality of machine assignment and processing path, improve the schedule robustness and guarantee capability of energy. First, a scheduling model is formulated with the objectives of average process time, matching degree and oxygen consumption fluctuation. Then, an improved preference-based NSGA-II is designed to solve the problem. The algorithm introduces the preference information into the optimization process and designs an individual sorting method based on the technique for order preference by similarity to ideal solution (TOPSIS) to guide the evolution direction. Besides, to improve the local search ability, variable neighborhood search is incorporated to generate new solutions with high quality. Computational experiments prove that the algorithm can effectively address the proactive scheduling problem. The sensitivity analysis and results of different scheduling models verify the robustness and superiority in machine matching and energy synergy of the model.

Deriving a new centrodal Runge Kutta method with predictor corrector style

In this research, we derived a new Runge - Kutta (RK) method with a centrodal mean, based on the principle of guesswork and correction, to obtain a new connection for this method, where we can use its two parts at the same time (in parallel). So, it’s makes this method more suitable for multi-processor computers that exist at this time than sequential methods previous.

Formation of bijels stabilized by magnetic ellipsoidal particles in external magnetic fields.

Bicontinuous interfacially-jammed emulsion gels (bijels) are increasingly used as emulsion templates for the fabrication of functional porous materials including membranes, electrodes, and biomaterials. Control over the domain size and structure is highly desirable in these applications. For bijels stabilized by spherical particles, particle size and volume fraction are the main parameters that determine the emulsion structure. Here, we investigate the use of ellipsoidal magnetic particles and study the effect of external magnetic fields on the formation of bijels. Using hybrid Lattice Boltzmann-molecular dynamics simulations, we analyze the effect of the magnetic field on emulsion dynamics and the structural properties of the resulting bijel. We find that the formation of bijels remains robust in the presence of magnetic fields, and that the domain size and tortuosity become anisotropic when ellipsoidal particles are used. We show that the magnetic fields lead to orientational ordering of the particles which in turn leads to alignment of the interfaces. The orientational order facilitates enhanced packing of particles in the interface which leads to different jamming times in the directions parallel and perpendicular to the field. Our results highlight the potential of magnetic particles for fabrication and processing of emulsion systems with tunable properties.

PARALLEL BUCKET-SORT ALGORITHM ON OPTICAL CHAINED-CUBIC TREE INTERCONNECTION NETWORK

The performance of sorting algorithms has a great impact on many computationally intensive applications. Researchers worked on parallelizing many sorting algorithms on various interconnection networks to improve their sequential counterpart performance. One of these interconnection networks is the optical chained-cubic tree (OCCT). In this paper, a parallel bucket sort (PBS) algorithm is presented and applied to the OCCT interconnection network. This PBS algorithm is evaluated analytically and by simulation in terms of various performance metrics including parallel runtime, computation time, communication time, concatenation time, speedup, and efficiency, for a different number of processors, dataset sizes, and data distributions including random and descending. Simulation results show that the highest obtained speedup is approximately 912x on OCCT using 1020 processors, which means the parallel runtime of the PBS on 1020 processors is 912 times faster than the sequential runtime of BS on a single processor.

A Novel Parallel Timing Synchronization Scheme for High-Speed Receivers

A Novel Parallel Timing Synchronization Scheme for High-Speed Receivers

Optimizing the gravitational tree algorithm for many-core processors

ABSTRACT Gravitational N-body simulations calculate numerous interactions between particles. The tree algorithm reduces these calculations by constructing a hierarchical oct-tree structure and approximating gravitational forces on particles. Over the last three decades, the tree algorithm has been extensively used in large-scale simulations, and its parallelization in distributed memory environments has been well studied. However, recent supercomputers are equipped with many CPU cores per node, and optimizations of the tree construction in shared memory environments are becoming crucial. We propose a novel tree construction method in contrast to the conventional top-down approach. It first creates all leaf cells without traversing the tree and then constructs the remaining cells by a bottom-up approach. We evaluated the performance of our novel method on the supercomputer Fugaku and an Intel machine. On a single thread, our method accelerates one of the most time-consuming processes of the conventional tree construction method by a factor of above 3.0 on Fugaku and 2.2 on the Intel machine. Furthermore, as the number of threads increases, our parallel tree construction time reduces considerably. Compared to the conventional sequential tree construction method, we achieve a speed up of over 45 on 48 threads of Fugaku and more than 56 on 112 threads of the Intel machine. In stark contrast to the conventional method, the tree construction with our method no longer constitutes a bottleneck in the tree algorithm, even when using many threads.

Percepts, affects, clinamen: Alienation and entanglement in What Time Is It There? (2001)

This article takes as its starting point an uncanny dialectics of alienation, desire and connection that permeates Tsai Ming-liang’s oeuvre. Through approaching the non-intersecting parallel narratives in What Time Is It There? (2001) with the Epicurean and Lucretian notion of clinamen and the Deleuzian concepts of any-space-whatevers, percepts and affects, this article explores the relation between non-intersecting parallel spaces and times and a liminal, spectral cinematic space and time that is created by moving images themselves, which makes the dialectics of alienation and connection possible. This article argues that What Time involves Tsai’s meta-cinematic approach to cinema’s potentiality that enables both characters and spectators to engage directly with moving images and reimagine the world through its spectrality and non-human perception.

Neutrophil Gelatinase-Associated Lipocalin in Peritoneal Dialysis-Related Peritonitis: Correlation with White Blood Cells over Time and a Possible Role as the Outcome Predictor

Introduction: The present study aimed to monitor peritoneal neutrophil gelatinase-associated lipocalin (pNGAL) during peritonitis episodes and to enhance its diagnostic value by evaluating pNGAL at scheduled times in parallel with white blood cell (WBC) count. In addition, we investigated possible correlations between pNGAL and the etiology of peritonitis, evaluating it as a possible marker of the clinical outcome. Methods: Twenty-two patients with peritoneal dialysis (PD)-related peritonitis were enrolled. Peritonitis was divided into Gram-positive, Gram-negative, polymicrobial, and sterile. WBC count and neutrophil gelatinase-associated lipocalin (NGAL) in PD effluent were measured at different times (days 0, 1, 5, 10, 15, and/or 20 and 10 days after antibiotic therapy discontinuation). NGAL was measured by standard quantitative laboratory-based immunoassay and by colorimetric NGAL dipstick (NGALds) (dipstick test). Results: We found strong correlations between peritoneal WBC, laboratory-based NGAL, and NGALds values, both overall and separated at each time point. On day 1, we observed no significant difference in WBC, both NGALds (p = 0.3, 0.9, and 0.2) between Gram-positive, Gram-negative, polymicrobial, and sterile peritonitis. No significant difference has been found between de novo versus relapsing peritonitis for all markers (p > 0.05). We observed a parallel decrease of WBC and both NGAL in patients with favorable outcomes. WBC count and both pNGAL resulted higher in patients with negative outcomes (defined as relapsing peritonitis, peritonitis-associated catheter removal, peritonitis-associated hemodialysis transfer, peritonitis-associated death) at day 10 (p = 0.04, p = 0.03, and p = 0.05, respectively) and day 15 (p = 0.01, p = 0.04, and tendency for p = 0.005). There was a tendency toward higher levels of WBC and NGAL in patients with a negative outcome at day 5. No significant difference in all parameters was proven at day 1 (p = 0.3, p = 0.9, p = 0.2) between groups. Conclusion: This study confirms pNGAL as a valid and reliable biomarker for the diagnosis of PD-peritonitis and its monitoring. Its trend is parallel to WBC count during peritonitis episodes, in particular, patients with unfavorable outcomes.

Flexibel fyrkantighet möter meningslös skötsamhet

AbstractEvery year, over 1,000 children and young people, between the ages of 8 and 20, are placed in special youth homes in Sweden due to criminality, substance abuse or ”other socially destructive behaviour”. This article is based on interviews with youth and staff about what happens at the institution and how they regard the purpose of the stay in a facility that has the character of a total institution, in Goffman’s understanding. With support in Adam’s theories about time rhythms and Abbott’s concepts of time/event, we analyze how staff and youth cooperate in creating institutional life where they share the space, while having distance from each other and avoid creating closeness as their interaction is limited in time. Due to several parallel time rhythms affecting their everyday life and time at the institution the young people develop an approach between resisting or developing what can be termed as ”meaningless diligence”. Everyday life becomes easier to manage if they follow what the staff say, but they cannot see that it leads to a better future. The staff describe an approach where they are careful both to follow rules and to make constant individual and situational exceptions, a ”flexible rigidity” to fixed rules and time-schedules, to deal with specific events and needs. Together they maintain institutional life and the young people are adapted to the situation here and now, not to the life outside or after the institution.

Businesses in high-income zip codes often saw sharper visit reductions during the COVID-19 pandemic

As the COVID-19 pandemic unfolded, the mobility patterns of people worldwide changed drastically. While travel time, costs, and trip convenience have always influenced mobility, the risk of infection and policy actions such as lockdowns and stay-at-home orders emerged as new factors to consider in the location-visitation calculus. We use SafeGraph mobility data from Minnesota, USA, to demonstrate that businesses (especially those requiring extended indoor visits) located in affluent zip codes witnessed sharper reductions in visits (relative to parallel pre-pandemic times) outside of the lockdown periods than their poorer counterparts. To the extent visits translate into sales, we contend that post-pandemic recovery efforts should prioritize relief funding, keeping the losses relating to diminished visits in mind.

A multi-objective complex product assembly scheduling problem considering transport time and worker competencies

The hybrid flow shop scheduling problem (HFSP) is a research hotspot in the shop scheduling problem. However, few studies have investigated HFSP involving parallel machine scheduling and worker competencies. Therefore, this study investigates a complex product assembly line scheduling problem considering parallel team scheduling, worker competencies, and transport time. The makespan, transport time, imbalance degree of team workload, and imbalance degree of cycle time are taken as optimization objectives. First, a mathematical model considering transport time and worker competencies is developed, and then a mixed encoding and decoding method is proposed. Second, an algorithm that hybridizes the genetic algorithm and simulated annealing algorithm is proposed, involving an improved Nawaz-Enscore-Ham heuristic method and a strengthened elite retention strategy to improve the quality of the solution. Finally, based on nine examples generated from real production statuses, the proposed algorithm is compared with the other four algorithms. The results show that the proposed algorithm is superior in terms of the quality and efficiency of solutions.

Task graph-based performance analysis of parallel-in-time methods

In this paper, we present a performance model based on task graphs for various iterative parallel-in-time (PinT) methods. PinT methods have been developed to speed up the simulation time of time-dependent problems using modern parallel supercomputers. The performance model is based on a data-driven notation of the methods, from which a task graph is generated. Based on this task graph and a distribution of time points across processes typical for PinT methods, a theoretical lower runtime bound for the method can be obtained, as well as a prediction of the runtime for a given number of processes. In particular, the model is able to cover the large parameter space of PinT methods and make predictions for arbitrary parameter settings. Here, we describe a general procedure for generating task graphs based on three iterative PinT methods, namely, Parareal, multigrid-reduction-in-time (MGRIT), and the parallel full approximation scheme in space and time (PFASST). Furthermore, we discuss how these task graphs can be used to analyze the performance of the methods. In addition, we compare the predictions of the model with parallel simulation times using five different PinT libraries.

Dark-centred umbels in Apiaceae: diversity, development and evolution.

The wild carrot (Daucus carota) is famous for its dark flowers in the umbel centre. Several studies have been conducted to figure out their functional significance, but the evolution of the dark centre remains an enigma. In the present paper, we consider all known apioid species with dark-centred umbels to get a deeper understanding of their biology and evolution. Based on herbaria studies, literature and field work, we reconstructed the distribution area of 10 species (7 genera, 6 clades) of Apiaceae-Apioideae. To recognize homology of the dark structures, developmental studies were conducted in Artedia squamata and Echiophora trichophylla Field studies included architecture, flower morph distribution (andromonoecy) and flowering sequence within the plants, abundancy and behaviour of umbel visitors and preliminary manipulation experiments (removal/adding of dark structures). The dark structures are not homologous to each other. In the Daucus alliance, central flowers or umbellets are conspicuous, whereas in other species dark brush-like (A. squamata) or club-shaped structures (Dicyclophora persica, Echinophora trichophylla, Tordylium aegyptiacum, T. cappadocicum) develop from a naked receptacle. Species are andromonoecious, have a modular architecture and flower in multicyclic protandrous sequence. Among the many umbel visitors, beetles were the most abundant group. Only visitors found on umbels in both flowering phases were recognized as possible pollinators. Manipulation experiments indicated that the dark structures influence the behaviour of some, but not all umbel visitors. In Echinophora trichophylla, a massive gall infection was observed. It is evident that the dark structures evolved several times in parallel. The brush- and club-shaped structures are interpreted as the results of mutations affecting umbel development. Dark umbel centres are most likely stabilized by selection due to their general adaptive function. Their appearance in an area known as a hotspot of beetle pollination gives rise to the assumption that they may act as beetle marks.

Serial and parallel kernelization of Multiple Hitting Set parameterized by the Dilworth number, implemented on the GPU

The NP-hard Multiple Hitting Set problem is the problem of finding a minimum-cardinality set intersecting each of the sets in a given input collection a given number of times. Generalizing a well-known data reduction algorithm due to Weihe, we show a problem kernel for Multiple Hitting Set parameterized by the Dilworth number, a graph parameter introduced by Foldes and Hammer in 1978 yet seemingly so far unexplored in the context of parameterized complexity theory. Using matrix multiplication, we speed up the algorithm to quadratic sequential time and logarithmic parallel time. We experimentally evaluate our algorithms. By implementing our algorithm on GPUs, we show the feasibility of realizing kernelization algorithms on SIMD (Single Instruction, Multiple Data) architectures.

Ancient theatre acoustical qualities reconstruction dilemma for modern use and the international charters

PurposeThe general attitude of the ancient theatre conservation strategies and policies is still concerned primarily with their architectural physical appearance without considering their authentic scientific acoustical qualities. The paper attempts to illustrate and discuss how to enhance their acoustic heritage to arouse the audience's interest and needs. Thus, supporting their reconstruction based on recent acoustical research and community needs-related concerns and opportunities for ancient theatre's modern use.Design/methodology/approachIt is based on reviewing the main issues related to reconstruction in the international charters and conventions and how to infuse ancient theatres with their full role. It discusses the dilemma and debates regarding the theatre stage wall, colonnade (portico) restoration and anastylosis. Is it sufficient enough to recover the theatre sound volume? Or to rethink for full physical reconstructions of these missing related acoustical theatre architectural elements to their original level and layout as in ancient times in parallel to their virtual reconstruction?FindingsThe cultural significance of the authentic theatre's acoustical qualities needs to reform the conservation strategies and policies for a more flexible and resilient approach. It should be postulated, re-examined and advocated parallel to their 3D virtual reconstruction in the related international charters and conventions.Practical implicationsThe paper's implications are not immediate; it is far-reaching. It suggests the importance of acoustics in analysing historic theatre performance venues and reforming conservation strategies and approaches. This issue is especially critical for architects, conservators, the heritage community and the public audience.Originality/valueRecommendations are made for potential bold reconstruction actions that may be taken to achieve further sustainability, comfort, and permeability in modern theatre-use performances. Their physical reconstruction for improving the performance of contemporary theatre use regarding retaining the acoustic cultural significance should be more flexible and resilient in the charters.

Temperature-drift effect analysis of microstrip filters based on parallel high-order DGTD and FETD method with memory reduction technique

The temperature-drift effect of microstrip filters is analyzed by the proposed electromagnetic-thermal co-simulation method based on parallel high-order discontinuous Galerkin time domain (DGTD) and finite-element time-domain (FETD) algorithms with a memory reduction technique. The element matrices of DGTD method are factorized into the product of coefficient matrices and universal matrices. The coefficient matrices are different for each tetrahedral element and need to be stored for all the elements. While the universal matrices are the same for all the tetrahedral elements and only need to be stored for one element. Since the sizes of the coefficient matrices are much smaller than the element matrices of DGTD method, the proposed method avoids storing the large element matrices and greatly reduce the memory requirement of the DGTD method. Thus it reduces the memory requirement of the whole electromagnetic-thermal co-simulation which is dominated by the memory consumption of the DGTD method. Large-scale parallel technique is adopted to accelerate the process of electromagnetic-thermal co-simulation. The proposed method provides a very powerful tool for temperature-drift effect analysis of microstrip filters.

Multi-scale one-dimensional convolution tool wear monitoring based on multi-model fusion learning skills

Effective tool wear monitoring (TWM) is crucial for accurately assessing the degree of tool wear, guiding tool replacement during actual cutting processes, ensuring stable machine operation, and improving workpiece processing quality. With the arrival of the era of Big data, more and more data-driven monitoring methods are used for TWM problems, but it also exposes the problems of over reliance on artificial feature extraction and selection, low robustness of the actual industrial environment and poor generalization of different machining processes. To solve these problems, this paper proposes a multi-scale one-dimensional convolution (MODC-MMFL) end-to-end TWM integrated network model based on multi-model fusion learning (MMFL) skills. Firstly, multi-scale local features of multi-sensor signals are adaptively extracted by multi-scale one-dimensional convolution (MODC) network, to realize multi-feature fusion. Then, using MMFL skills, the MMFL network is composed of deep attention temporal convolutional network (DATCN) and stacked bidirectional gate recurrent unit network (SBIGRU)， parallel learning time series features related to tool wear characteristics，and use a fusion layer to fuse these learned features, in which residual channel attention mechanism (RCAM) is used to improve network performance in DATCN network. Finally, the predicted tool wear value is output by fully connected regression network (FCR). In addition, this paper uses the PHM tool wear dataset to conduct experimental study on the proposed model, first verifying the effectiveness of the proposed model. Then, ablation experiments were conducted to investigate the impact of hyper-parameters on the predictive performance of the model. The model was enhanced through hyper-parameter tuning, and a generalized enhanced model was established. The experimental results showed that the enhanced model had better predictive performance compared to ordinary models. Finally, Gaussian noise is added to the original signal of the PHM tool wear dataset to simulate the high noise signal of the actual industrial environment. The noise signal is used to carry out experimental study on the enhanced model. The experimental results show that the enhanced model still has good prediction performance in the high noise environment and has high robustness to the actual industrial environment. After the above research, this paper uses the NASA tool wear dataset to conduct experimental study on the proposed model. The experimental results show that the proposed model has good predictive performance for different machining processes, verifying the generalizability of the proposed model for different machining processes. In summary, the model proposed in this paper can accurately predict tool wear values based on processing monitoring information, and has good predictive performance, anti-interference ability, and environmental adaptability, making it very suitable for practical industrial applications.

A Parallel Solution of Timing Synchronization in High-Speed Remote Sensing Data Transmission

Considering the problem that the timing synchronization calculation in high-speed remote sensing signal reception is complex and it is difficult for it to be parallel, this paper deduces and designs a parallel timing error estimation and correction scheme. This paper presents the design of polyphase DFT filter banks with non-maximum decimation. The feedforward timing error estimation and correction method is then improved to enhance synchronization performance. Finally, an implementation scheme for parallel timing error estimation and correction is proposed using the polyphase filter bank time domain decomposition method and the filter polyphase model. In the estimation module, the parallel implementation structure of the joint second-order and fourth-order cyclic statistics methods is designed, which improves the estimation accuracy. In the correction module, a fractional delay filtering method with higher accuracy is adopted in order to improve the calibration accuracy and reduce the computational complexity. The timing synchronization of a high-speed remote sensing signal with timing error is simulated and verified. The experimental results show that the parallel method proposed in this paper greatly reduces the processing speed of subband data, and has a good synchronization performance, which is close to the theoretical limit in the demodulation error rate. This paper utilizes a multi-phase DFT filter bank architecture to achieve parallel timing synchronization, which presents a novel approach for the future parallel reception of high-speed remote sensing signals.

CUDA-BASED PARALLELIZATION OF GRADIENT BOOSTING AND BAGGING ALGORITHM FOR DIAGNOSING DIABETES

Data, its volume, structure, and form of presentation are among the most significant problems in working in the medical field. The probability of error is very high without innovative high-tech data analysis tools. It is easy to miss an important factor that is critical but lost among other, less important information. This work aims to study the proposed parallel gradient boosting algorithm in combination with the Bagging algorithm in the classification of diabetes to achieve greater stability and higher accuracy, reduce computational complexity and improve performance in medicine. The methods of parallelization of the Gradient Boosting algorithm in combination with the Bagging algorithm are investigated in the paper. Performance scores were obtained: approximately 7 using ThreadPoolExecutor and an eight-core computer system and 9.5 based on CUDA technology. Performance indicators that go to the unit are calculated. This, in turn, confirms the effectiveness of the proposed parallel algorithm. Another significant result of the study is improving algorithm accuracy by increasing the number of algorithms in the composition. The problem of diagnosing a patient's diabetes based on specific measurements included in the data set is considered. Detailed analysis and pre-processing of the selected dataset were performed. The parallelization of the proposed algorithm is implemented using the multi-core architecture of modern computers and CUDA technology. The process of learning models and training samples was parallelized. The theoretical estimation of the computational complexity of the offered parallel algorithm is given. A comparison of serial and parallel algorithm execution time using ThreadPoolExecutor when varying the number of threads and algorithms in the composition is presented. And also, the comparative analysis of time expenses at consecutive and parallel execution based on CPU and GPU is carried out.