International Journal of Parallel Emergent and Distributed Systems最新文献

{"title":"Time-reversal symmetries in two-dimensional reversible partitioned cellular automata and their applications","authors":"K. Morita","doi":"10.1080/17445760.2022.2102169","DOIUrl":"https://doi.org/10.1080/17445760.2022.2102169","url":null,"abstract":"Time-reversal symmetry (T-symmetry) in a reversible cellular automaton (CA) is the property in which forward and backward evolutions of configurations are governed by the same local transition function. We show that the framework of partitioned cellular automata (PCAs) is useful to study T-symmetries of reversible CAs. Here, we investigate reversible elementary square PCAs (ESPCAs) and reversible elementary triangular PCAs (ETPCAs), and prove that a large number of reversible ESPCAs and all reversible ETPCAs are T-symmetric under some kinds of simple transformations on configurations. As applications, these results are used to find and analyse backward evolution processes in reversible PCAs. For example, for a given functional module implemented in a reversible PCA, such as a reversible logic element, we can obtain its inverse functional module very easily using its T-symmetry.","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43008180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Four-splitting based coarse-grained multicomputer parallel algorithm for the optimal binary search tree problem","authors":"Jerry Lacmou Zeutouo, Vianney Kengne Tchendji, J. Myoupo","doi":"10.1080/17445760.2022.2102168","DOIUrl":"https://doi.org/10.1080/17445760.2022.2102168","url":null,"abstract":"ABSTRACT This paper presents a parallel solution based on the coarse-grained multicomputer (CGM) model using the four-splitting technique to solve the optimal binary search tree problem. The well-known sequential algorithm of Knuth solves this problem in time and space, where n is the number of keys used to build the optimal binary search tree. To parallelise this algorithm on the CGM model, the irregular partitioning technique, consisting in subdividing the dependency graph into subgraphs (or blocks) of variable size, has been proposed to tackle the trade-off of minimising the number of communication rounds and balancing the load of processors. This technique, however, induces a high latency time of processors (which accounts for most of the global communication time) because varying the blocks' sizes does not enable them to start evaluating some blocks as soon as the data they need are available. The four-splitting technique proposed in this paper solves this shortcoming by evaluating a block as a sequence of computation and communication steps of four subblocks. This CGM-based parallel solution requires execution time with communication rounds, where p is the number of processors and k is the number of times the size of blocks is subdivided. An experimental study conducted to evaluate the performance of this CGM-based parallel solution showed that compared to the solution based on the irregular partitioning technique where the speedup factor is up to ×10.39 on 128 processors with 40,960 keys when k = 2, the speedup factor of this solution is up to ×13.12 and rises up to ×14.93 when k = 5.","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48120625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A paradigm for secure object access and unrestricted mobility in distributed systems","authors":"L. Lopriore","doi":"10.1080/17445760.2022.2095384","DOIUrl":"https://doi.org/10.1080/17445760.2022.2095384","url":null,"abstract":"In distributed architectures consisting of processing nodes, we associate a node chain with each object. The node chain connects a node named in the object identifier to the nodes reserving secondary and primary memory space for the object. No restriction exists on object movements across the network. A process can access a given object only if it holds a security gate referencing this object. The gate includes a password and the specification of an access authorisation. Gate weakening and revocation are fully supported. GRAPHICAL ABSTRACT","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44469494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Competitive influence maximisation model with monetary incentive","authors":"Nadia Niknami, Jie Wu","doi":"10.1080/17445760.2022.2094379","DOIUrl":"https://doi.org/10.1080/17445760.2022.2094379","url":null,"abstract":"ABSTRACT The spreading of information in social networks can be modelled as a process of diffusing information with a probability from its source to its neighbours. There is a challenge in the real world where competing companies implement their strategies to gain influence in the same social network at the same time. To effectively control the spreading of processes within the network, the effective use of limited resources is of prime importance. When budgets are fixed, competitors will search for a set of seed members to diffuse influence and maximise the number of members that are affected. Each competitor seeks to maximise its influence by investing in the most influential members in the given social network. In this paper, we utilise the Colonel Blotto game to help competitors figure out how many resources should be allocated to influential nodes to increase the influences on nodes. This is done while also taking into account that competing campaigns are trying to do the same thing. We propose a Max-Influence-Independent-Set (MIIS) algorithm to determine the most influential independent set and find the optimal investment to gain maximum influence in the given social network. The effectiveness of this approach is evaluated under different parameter values, namely probability distributions, topologies, and density. GRAPHICAL ABSTRACT","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42242246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"KNOWM memristors in a bridge synapse delay-based reservoir computing system for detection of epileptic seizures","authors":"Dawid Przyczyna, Grzegorz Hess, K. Szaciłowski","doi":"10.1080/17445760.2022.2088751","DOIUrl":"https://doi.org/10.1080/17445760.2022.2088751","url":null,"abstract":"ABSTRACT Nanodevices that show the potential for non-linear transformation of electrical signals and various forms of memory can be successfully used in new computational paradigms, such as neuromorphic or reservoir computing. In this work, we present single-node Echo State Machine (SNESM) RC system based on bridge synapse as a computational substrate (consisting of 4 memristors and a differential amplifier) used for epileptic seizure detection. The results show that the evolution of the signal in a feedback loop helps improve the classification accuracy of the system for that task. The transformation in SNESM changes the correlation and distribution of the complexity parameters of the input signal. In general, there are more differences in the correlation of complexity parameters between the transformed signal and the input signal, which may explain the improvement in the classification scores. SNESM could prove to be a useful time series signal processing system designed to improve accuracy in classification tasks.","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43474857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time management in a chess game through machine learning","authors":"Guga Burduli, Jie Wu","doi":"10.1080/17445760.2022.2088746","DOIUrl":"https://doi.org/10.1080/17445760.2022.2088746","url":null,"abstract":"ABSTRACT Chess includes two significant factors: playing good moves and managing your time optimally. Time, especially in blitz games, is just as essential to the game as making good moves. Nowadays, several incredible engines are already developed, more than enough to defeat all the best human chess players. For studying how to make good moves, these engines are crucially useful. Professional chess players are using them in addition to coaches to prepare for the matches or to examine the mistakes in their played games. However, managing time still is a huge challenge. There are no basic rules for managing time. A lot of factors influence the decision about how much time should be spent in a particular position. For computers, it is easier because they calculate much faster and they have all the theoretical knowledge. However, even grandmaster chess human players are struggling with time trouble. In this article, we describe how the data was collected from an online chess platform and show methods of how time can be managed based on different features. In this regard, we will use two different models: using a customised neural network and using a proposed segmented least square approximation method. In both of the models, we will use our collected data. GRAPHICAL ABSTRACT","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44973837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study and evaluation of optimum location deployment for environment adaptive applications","authors":"Y. Yamato","doi":"10.1080/17445760.2022.2088749","DOIUrl":"https://doi.org/10.1080/17445760.2022.2088749","url":null,"abstract":"Heterogeneous hardware other than a small-core central processing unit (CPU) such as a graphics processing unit (GPU), field-programmable gate array (FPGA), or many-core CPU is increasingly being used. However, to use heterogeneous hardware, programmers must have sufficient technical skills to utilise OpenMP, CUDA, and OpenCL. On the basis of this, I have proposed environment-adaptive software that enables automatic conversion, configuration, and high performance operation of once written code, in accordance with the hardware. However, although it has been considered to convert the code according to the offload devices, there has been no study where to place the offloaded applications to satisfy users' requirements of price and response time. In this paper, as a new element of environment-adapted software, I examine a method to calculate appropriate locations using the linear programming method. I confirm that applications can be arranged appropriately through simulation experiments when some conditions such as application type and users' requirements are changed. GRAPHICAL ABSTRACT","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42026438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Re-configurable, expandable, and cost-effective heterogeneous FPGA cluster approach for resource-constrained data analysis","authors":"Dulana Rupanetti, Hassan A. Salamy, Cheol-Hong Min, Kundan Nepal","doi":"10.1080/17445760.2022.2085703","DOIUrl":"https://doi.org/10.1080/17445760.2022.2085703","url":null,"abstract":"Field programmable gate arrays (FPGAs) have become widely prevalent in recent years as a great alternative to application-specific integrated circuits (ASIC) and as a potentially cheap alternative to expensive graphics processing units (GPUs). Introduced as a prototyping solution for ASIC, FPGAs are now widely popular in applications such as artificial intelligence (AI) and machine learning (ML) models that require processing data rapidly. As a relatively low-cost option to GPUs, FPGAs have the advantage of being reprogrammed to be used in almost any data-driven application. In this work, we propose an easily scalable and cost-effective cluster-based co-processing system using FPGAs for ML and AI applications that is easily reconfigured to the requirements of each user application. The aim is to introduce a clustering system of FPGA boards to improve the efficiency of the training component of machine learning algorithms. Our proposed configuration provides an opportunity to utilise relatively inexpensive FPGA development boards to produce a cluster without expert knowledge in VHDL, Verilog, or the system designs related to FPGA development. Consisting of two parts – a computer-based host application to control the cluster and an FPGA cluster connected through a high-speed Ethernet switch, allows the users to customise and adapt the system without much effort. The methods proposed in this paper provide the ability to utilise any FPGA board with an Ethernet port to be used as a part of the cluster and unboundedly scaled. To demonstrate the effectiveness of the proposed work, a two-part experiment to demonstrate the flexibility and portability of the proposed work – a homogeneous and heterogeneous cluster, was conducted with results compared against a desktop computer and combinations of FPGAs in two clusters. Data sets ranging from 60,000 to 14 million, including stroke prediction and covid-19, were used in conducting the experiments. Results suggest that the proposed system in this work performs close to 70% faster than a traditional computer with similar accuracy rates. GRAPHICAL ABSTRACT","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44864873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Arbitrary pattern formation by opaque fat robots on infinite grid","authors":"Manash Kumar Kundu, Pritam Goswami, Satakshi Ghosh, B. Sau","doi":"10.1080/17445760.2022.2088750","DOIUrl":"https://doi.org/10.1080/17445760.2022.2088750","url":null,"abstract":"ABSTRACT Arbitrary Pattern formation ( ) by a swarm of mobile robots is a widely studied problem in the literature. Many works regarding have been proposed on plane and infinite grid by point robots. But in practical application, it is impossible to design point robots. In Bose et al. [Arbitrary pattern formation on infinite grid by asynchronous oblivious robots. Theor Comput Sci. 2020;815:213–227], the robots are assumed opaque fat robots but the environment is plane. To the best of our knowledge, no work till now ever considered the problem assuming opaque fat robots on infinite grid where movements are restricted. In this paper, we have provided a collisionless distributed algorithm and solved using 9 colours.","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46154097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"When is deep learning better and when is shallow learning better: qualitative analysis","authors":"Salvador Robles Herrera, M. Ceberio, V. Kreinovich","doi":"10.1080/17445760.2022.2070748","DOIUrl":"https://doi.org/10.1080/17445760.2022.2070748","url":null,"abstract":"In many practical situations, deep neural networks work better than the traditional ‘shallow’ ones; however, in some cases, the shallow neural networks lead to better results. At present, deciding which type of neural networks will work better is mostly done by trial and error. It is therefore desirable to come up with some criterion of when deep learning is better and when shallow is better. In this paper, we argue that this depends on whether the corresponding situation has natural symmetries: if it does, we expect deep learning to work better, otherwise we expect shallow learning to be more effective. Our general qualitative arguments are strengthened by the fact that in the simplest case, the connection between symmetries and effectiveness of deep learning can be theoretically proven.","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41749336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}