The above discussion also makes clear that, for semantics of non-algebraic languages for describing concurrent systems, the characterization interleaving versus non-interleaving is not meaningful. The basic semantic equivalence that is used throughout the chapter is bisimilarity [51]. Nowadays the theory, design, analysis, evaluation and application of parallel and distributed computing systems are still burgeoning, to suit the increasing requirements on high … The second serves to list the model parameters that have to specify their values numerically. Decentralized computing E. All of these Business A distributed cloud is an execution environment where application components are placed at appropriate geographically-dispersed locations chosen to meet the requirements of the application. The chapter is written in the style of a tutorial. As presented in Section 5.3.3, we can consider Hadoop in general terms as a framework, a software library, a MapReduce programming approach or a cluster management technology. Scale Distributed Databases to store petabytes of data D. Loosely coupled G. None of these. B. G. None of these, 7: No special machines manage the network of  architecture in which resources are known as, A. Peer-to-Peer The existence of so many different semantics for concurrent systems has created a whole new area of research named comparative concurrency semantics [43]. F. None of these, 27: Interprocessor communication that takes place, A. The chapter concludes with a survey of the literature and a historic perspective. OpenMP application program interface (OpenMP API) is a shared memory multiprocessing application program inference for easy development of shared memory parallel programs. The Bufoosh algorithm addresses issues related to buffering algorithms for ER (Kawai, Garcia-Molina, Benjelloun, Larson, Menestrina, Thavisomboon, 2006). Data As mentioned, most process-algebraic theories are interleaving theories. Dan C. Marinescu, in Cloud Computing (Second Edition), 2018. Total-order semantics are often confused with interleaving semantics. The MapReduce library groups together all intermediate values and passes them to the Reduce function. A. HPC F. None of these. First, there was the development of powerful microprocessors, later made even more powerful through multi-core central processing units (CPUs). Difference Between Cloud Computing and Distributed Computing … Atomicity: Updates either succeed or fail, that is, the system avoids partial results. F. None of these. network based computational model that has the ability to process large volumes of data with the help of a group of networked computers that coordinate to solve a problem together Jorge Miguel, ... Fatos Xhafa, in Intelligent Data Analysis for e-Learning, 2017. Single system image: A client will see the same view regardless of the server to which it is connected. High ratio Identification Among them, we summarize the most significant case studies. Distributed and Cloud Computing From Parallel Processing to the Internet of Things Kai Hwang Geoffrey C. Fox Jack J. Dongarra AMSTERDAM † BOSTON † HEIDELBERG † LONDON NEW YORK † OXFORD † PARIS † SAN DIEGO SAN FRANCISCO † SINGAPORE † SYDNEY † TOKYO Efficiency S4 has a cluster consisting of computing machines, known as processing nodes (PNs). Cloud organization is based on a large number of ideas and on the experience accumulated since the first electronic computer was used to solve computationally challenging problems. For example, in distributed computing processors usually have their own private or distributed memory, while processors in parallel computing can have access to the shared memory. On a high level of abstraction, the behavior of a concurrent system is often represented by the actions that the system can perform and the ordering of these actions. B. This model should have enough detail level to adjust the modelled system to the real system. Therefore, the adoption of cloud computing to process data generated by IoT devices may not be applicable at all to classes of applications such as those needed for real-time, low latency, and mobile applications. While distributed computing spreads computation workload across multiple, interconnected servers, distributed cloud computing generalizes this to the cloud infrastructure itself. Parallel processes 3 As long as the computers are networked, they can communicate with each other to solve the problem. B. Cyber cycle Centralized computing Section 7 contains a brief intermezzo on algebraic renaming and communication functions, which is useful in the remaining sections. F. None of these, 25: Utilization rate of resources in an execution model is known to be its, A. 6: In which systems desire  HPC and HTC. D. 4 types F. None of these, 11: Virtualization that creates one single address space architecture that of, is called, A. E. All of these B. Transparency Section 10 studies a process algebra that incorporates several of the important characteristics of Petri-net theory. Therefore, it is beyond imagination to use cloud computing to collect data, store, and work out results. Rackspace currently hosts email for over 1 million users and thousands of companies on hundreds of servers. Dr.Avi Mendelson, in Heterogeneous Computing with OpenCL (Second Edition), 2013. The most important issues discussed in this manual are: The cluster requires exclusive machines for master services, NameNode and ResourceManager. –The cloud applies parallel or distributed computing, or both. 13: Data access and storage are elements of  Job throughput, of __________. 18: Uniprocessor computing devices  is called__________. In Section 3, the basic semantic framework used throughout this chapter is defined. The Hadoop documentation project offers a specific manual about Hadoop Cluster Setup [176]. G. None of these, 2: Writing parallel programs is referred to as, A. It is shown how labeled transition systems can be used to obtain both a total-order view of concurrent systems and a partial-order view, where the latter is based on the notion of step bisimilarity. E. All of these D. Secretive Organization principles for distributed systems such as modularity, layering, and virtualization are applied to the design of peer-to-peer and large-scale systems. Media mass In distributed computing, a single problem is divided into many parts, and each part is solved by different computers. B. This article discussed the difference between Parallel and Distributed Computing. It also provides some pointers to related work and it identifies some interesting topics for future study. Finally, the chapter covers composability bounds and scalability. The chapter combines and extends some of the ideas and results that appeared earlier in [2,4], and [8, Chapter 3]. The relation between cause addition and sequential composition, which is the most important operator for specifying causal orderings in process algebra, is studied. The simultaneous growth in availability of big data and in the number of simultaneous users on the Internet places particular pressure on the need to carry out computing tasks “in parallel,” or simultaneously. B. Parallel and distributed computing has offered the opportunity of solving a wide range of computationally intensive problems by increasing the computing power of sequential computers. The components are rack-aware regarding network topology and storage model. E. All of these E. All of these B. The programs using OpenMP are compiled into multithreading programs [163]. A better understanding of these concepts can be useful in the development of formalisms that are sufficiently powerful to support the development of large and complex systems. In a total-order semantics, actions of a process are always totally ordered, whereas in a partial-order semantics, actions may occur simultaneously or causally independent of each other. Cloud The Map/Reduce functions are as follows [167]: The Map function takes an input pair and produces a set of intermediate key/value pairs. The most important aspect of simulation methodologies is to yield behaviour and results close to the real system. E. All of these In this chapter we overview concepts in parallel and distributed systems important for understanding basic challenges in the design and use of computer clouds. The aims of the project are to develop methodologies and tools for parallel software engineering. E. All of these Although the Apache Hadoop project includes many Hadoop-related projects, the main modules are the Hadoop MapReduce and Hadoop distributed file system (HDFS) . Cause-addition operators allow for the explicit specification of causalities in algebraic expressions. 29: Which of the following is an primary goal of HTC paradigm___________. Two expressions in a formal language describe the same system if and only if they correspond to equivalent processes in the semantics, where the equivalence of processes is determined by a so-called semantic equivalence. B. Parallel and Distributed Computing MCQs – Questions Answers Test” is the set of important MCQs. It is our aim to provide a conceptual understanding of several important concepts that play a role in describing and analyzing the behavior of concurrent systems. Dan C. Marinescu, in Cloud Computing, 2013. Specific implementations of MPI exist, such as OpenMPI, MPICH and GridMPI [180]. In the context of this algebra, the relation between the causality mechanisms of standard ACP-style process algebra and Petri-net theory is investigated. The semantics of a formal language for describing the behavior of concurrent systems defines a process for each expression in the formal language. Deploy groups of distributed Java applications on the Cloud. Parallel Computing: Detailed Comparison of the Two A single-core CPU, on the other hand, can only run one process at the time, although CPUs are able to switch between tasks so quickly that they appear to run processes simultaneously. E. All of these The objective of a formal semantics is to create a precise and unambiguous framework for reasoning about concurrent systems. Cloud Computing – Distributed Computing, Advantages, Disadvantages Cloud Computing Lectures in Hindi/English for Beginners #CloudComputing parallel and distributed computing is that parallel computing is to execute multiple tasks using multiple processors simultaneously while in parallel computing, multiple computers are interconnected via a network to communicate and collaborate in order to achieve a common goal. The parallel and distributed computer systems have their power in the theoretical possibility of executing multiple tasks in co-operative form. Hence, this model not only provides failover controls, but also increases the performance level of the cluster. C. Mainframe computers In addition to the single-resource fairness, there are some work focusing on multiresource fairness, including DRF [7] and its extensions [69–72]. Hadoop has become a crucial part of Last.fm infrastructure, currently consisting of two Hadoop clusters spanning over 50 machines, 300 cores, and 100 TB of disk space. Parallel computing is a type of computation where many calculations or the execution of processes are carried out simultaneously. The Map function groups all lines with a single queue-id key, and then the Reduce phase determines if the log message values indicate that the queue-id is complete. E. All of these Flexibility Cloud Computing – Autonomic and Parallel Computing Cloud Computing Lectures in Hindi/English for Beginners #CloudComputing E. All of these The rest of the machines in the cluster are slave nodes, DataNode and NodeManager. C. Business Reliability: Once an update has been applied, it will persist. Parallel computing Latest posts by Prof. Fazal Rehman Shamil, Core Multiple Choice Questions of Software Engineering, Multiple Choice Questions (MCQs) of data and databases, Computer Science MCQs Leaks PDF EBook by Fazal Rehman Shamil, Corel DRAW Quiz Test Solved Mcqs Questions with Answers, Corel Draw MCQs for Graphic Designer Job Test, Operator overloading Solved MCQ’s (OOP), Polymorphism Mcqs In Object Oriented Programming(OOP), Social Networks MCQs Solved Questions Answers, Domain name system solved MCQs Quesitons Answers, Iterative Model MCQs Solved Questions Answers, incremental Model Solved MCQs and Questions Answers, UML diagrams solved MCQs Questions Answers. S4 (Simple Scalable Stream Processing System) is a distributed real-time data processing system developed by Yahoo. D. Both A and B However, unlike MapReduce which has a limitation on scaling, Yahoo! Fig. Database functions and procedure MCQs Answers, C++ STANDARD LIBRARY MCQs Questions Answers, Storage area network MCQs Questions Answers, FPSC Computer Instructor Syllabus preparation. In the case of Apache Hadoop there are custom services and cluster infrastructure solutions devoted to offering a comprehensive parallel processing framework for MapReduce applications. 5 Computing Paradigm Distinctions . D. Both A and B Cloud computing is based on a large number of ideas and the experience accumulated since the first electronic computer was used to solve computationally challenging problems. A branching-time semantics distinguishes processes with the same ordering of actions but different branching structures. The idea is to have a global resource manager and per-application master. A HDFS cluster consists of a name node that manages the file system metadata and data nodes that store the actual data [172]. a distributed computing system. In response to this new problem, many researchers have begun to develop novel approaches to the development of suitable methodologies and tools for parallel programming. However, in [2], it is shown that it is possible to develop both process-algebraic theories with an interleaving, partial-order semantics and algebraic theories with a non-interleaving, total-order semantics. have adopted the MapReduce model [169]. Although important improvements have been achieved in this field in the last 30 years, there are still many unresolved issues. C. Adaptation Cyber Crime Solved MCQs Questions Answers. Copyright © 2020 Elsevier B.V. or its licensors or contributors. This chapter does not discuss variations of process-algebraic theories in the linear-time/branching-time spectrum. Finally, Section 11 summarizes the most important conclusions of this chapter. The administrator defines the rack information, and then the cluster provides data and network availability based on the cluster characteristics. C. HRC The main tool corresponds to an event-driven simulator that uses synthetic descriptions of a parallel programme and a parallel architecture. Shared memory MPI addresses primarily the message-passing parallel programming model, in which data is moved from the address space of one process to that of another process through cooperative operations on each process. It provides a set of compiler directives to create threads, synchronize the operations, and manage the shared memory [177]. F. None of these. 1: Computer system of a parallel computer is capable of A. According to Dean et al. B. F. None of these, A. Furthermore, the engineering resources are limited and the system needs to be very reliable, as well as easy to use and maintain. These data need to be processed, stored, and allow the users to access them directly. 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URL: https://www.sciencedirect.com/science/article/pii/B9780128128107000054, URL: https://www.sciencedirect.com/science/article/pii/B9780124046276000026, URL: https://www.sciencedirect.com/science/article/pii/B978044482830950031X, URL: https://www.sciencedirect.com/science/article/pii/B9780124058941099885, URL: https://www.sciencedirect.com/science/article/pii/S0927545298800889, URL: https://www.sciencedirect.com/science/article/pii/B9780123819727000038, URL: https://www.sciencedirect.com/science/article/pii/B9780128054673000119, URL: https://www.sciencedirect.com/science/article/pii/B9780128053942000076, URL: https://www.sciencedirect.com/science/article/pii/B9780128045350000058, Partial-Order Process Algebra (and its Relation to Petri Nets), Heterogeneous Computing with OpenCL (Second Edition), Entity Resolution and Information Quality, In addition to the basic R-Swoosh algorithm, the research group at InfoLab has also developed other algorithms intended to optimize ER performance in, Benjelloun, Garcia-Molina, Kawai, Larson, Menestrina, Thavisomboon, 2006, Kawai, Garcia-Molina, Benjelloun, Menestrina, Whang, Gong, 2006, Kawai, Garcia-Molina, Benjelloun, Larson, Menestrina, Thavisomboon, 2006, A Taxonomy and Survey of Stream Processing Systems, Software Architecture for Big Data and the Cloud, Resource Management in Big Data Processing Systems, ]. 1: Computer system of a parallel computer is capable of, A. This led to so-called parallelism where multiple processes could run at the same time. B. The HDFS is the primary distributed storage used by Hadoop applications. Remo Suppi, ... Joan Sorribes, in Advances in Parallel Computing, 1998, A spectacular growth in the development of the high-performance parallel (and distributed) systems has been observed over the last decade. 3: Simplifies application’s of three-tier architecture is ____________. Centralized computing C. Science D. Tightly coupled A. Hadoop provides services for monitoring the cluster health and failover controls. Grid computing is distinguished from conventional high-performance computing systems such as cluster computing in that grid computers have each node set to perform a different … E. All of these Starting in the mid-1980s, two technology advancements made distributed systems feasible. G. None of these, 16: Resources and clients transparency that allows movement within a system is called, A.Mobility transparency We use cookies to help provide and enhance our service and tailor content and ads. D. Cyber-physical system E. Dependability Distributed process All the computers connected in a network communicate with each other to attain a common goal by makin… The Apache Hadoop software library is a framework devoted to processing large data sets across distributed clusters of computers using simple programming models. A modular P/T net models a system component that may interact with its environment via a well defined interface. The interested reader is referred to [28,29] and [27], Chapter 1 of this Handbook. Each framework decides which resources to accept or which computation to run on them. The per-application master is in charge of negotiating resources from the resource manager and working with the node managers to execute the tasks [171]. E. All of these E. Loosely coupled F. All of these Engineering Behind these general models, a cluster infrastructure has to be included as a crucial part of the general framework. In general, distributed computing is the opposite of centralized Management The meaning of expressions in such a formal language is often captured in a so-called formal semantics. Distributed programming on the cloud - Learn | Microsoft Docs A. B. D. Adaptation The quest of developing formalisms and semantics that are well suited for describing and analyzing the behavior of concurrent systems is characterized by a number of ongoing discussions on classifications of semantic equivalences. In Chapter 2 we review parallel and distributed systems concepts that are important to understanding the basic challenges in the design and use of computer … It proposes a distributed two-level scheduling mechanism called resource offers, which decides how many resources to offer. A distributed system consists of more than one self directed computer that communicates through a network. Memory in parallel systems can either be shared or distributed. C. Dependability An expansion theorem states that parallel composition can be expressed equivalently in terms of choice and sequential composition. The data stream within S4 is a sequence of events. In contrast, YARN [15] divides resources into containers (ie, a set of various resources like memory and CPU) and tries to guarantee fairness between queues. –Clouds can be built with physical or virtualized resources over large data centers that are centralized or distributed. Distributed Computingcan be defined as the use of a distributed system to solve a single large problem by breaking it down into several tasks where each task is computed in the individual computers of the distributed system. C. 3C E. All of these Each of these programming environments offers scope for benefiting domain-specific applications, but they all failed to address the requirement for general purpose software that can serve different hardware architectures in the way that, for example, Java code can run on very different ISA architectures. E. Parallel computing C. Parallel computing D. Parallel programming The run-time framework takes care of the details of partitioning the input data, scheduling the program’s execution across a set of machines, handling machine failures, and managing the required intermachine communication. The framework of labeled transition systems is used to formalize the notion of a process and bisimilarity of processes. Very often, such an interleaving theory has a total-order semantics, which causes the confusion between the terms “total-order” and “interleaving”. Adaptation E. All of these D. Replication transparency E. All of these This company provides managed systems and email services for enterprises. Distributed and Cloud Computing: From Parallel Processing to the Internet of Things offers complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing. This allows programmers, without any experience with parallel and distributed systems, to utilize the resources of a large distributed system [167]. Regarding the cluster usage, the Hadoop instance has 2400 cores, about 9 TB of memory, and runs at 100% utilization at many points during the day. If done properly, the computers perform like a single entity. In Section 6, the algebraic framework of Section 5 is extended with a class of algebraic operators, called causal state operators. However, this usually involves a complexity grade. Master the theory of Distributed Systems, Distributed Computing and modern Software Architecture. B. In other words, the MapReduce model arises as a reaction to the complexity of the parallel computing programming models, which consider the specific parallel factors involved in software development processes. Efficiency E. Adaptivity D. Flexibility D. Distributed computing B. 5: In which application system Distributed systems can run well? B. The semantics of such a theory is a non-interleaving semantics or a non-interleaving process algebra. The primary purpose of comparative concurrency semantics is the classification of semantics for concurrent systems in a meaningful way. C. Parallel computing D. Dependability Grid computing is the use of widely distributed computer resources to reach a common goal. B. F. None of these, A. Parallel and distributed computing has been a key technology for research and industrial innovation, and its importance continues to grow as we navigate the era of big data and the internet of things. Parallel computing and distributed computing are two types of computation. C. Parallel development 2C F. All of these IBM proposed the use of message-passing-based software in order to take advantage of its heterogeneous, non-coherent cell architecture and FPGA based solutions integrate libraries written in VHDL with C or C++ based programs to achieve the best of two environments. A. F. None of these. D. Many Client machines Numerous formal languages for describing and analyzing the behavior of concurrent systems have been developed. Parallel and distributed computing has been under many years of development, coupling with different research and application trends such as cloud computing, datacenter networks, green computing, etc. Adaptation C. Message passing D. Flexibility Centralized memory The Apache Hadoop NextGen MapReduce, also known as Apache Hadoop yet another resource negotiator (YARN) , or MapReduce 2.0 (MRv2) , is a cluster management technology. 2 types Readers with a strong systems background can skip this chapter, but it is important for application developers to read it. Space based Section 8 describes two approaches to modularizing P/T nets. The behavior of parallel and distributed systems, often called concurrent systems, is a popular topic in the literature on (theoretical) computing science. Parallel and Distributed Computing website. By means of step bisimilarity, it is possible to obtain a process-algebraic theory with a branching-time, interleaving, partial-order semantics in a relatively straightforward way. [167], MapReduce is a programming model and an associated implementation for processing and generating large data sets. To obtain this goal, a careful model is necessary. Many Server machines However, such processes may differ in their branching structure, where the branching structure of a process is determined by the moments that choices between alternative branches of behavior are made. Cloud computing takes place over the internet. D. Computer utilities E. Parallel computation As seen in the main conclusions presented in surveys of parallel programming models [180] and performance comparison studies [163], OpenMP is the best solution for shared memory systems, MPI is the convenient option for distributed memory systems, and MapReduce is recognized as the standard framework for big data processing. This manual describes how to install and configure Hadoop clusters and the management services that are available in the global framework. E. All of these A typical characteristic of a total-order semantics is that concurrency of actions is equivalent to non-determinism: A process that performs two actions in parallel is equivalent to a process that chooses non-deterministically between the two possible total orderings of the two actions. D. Both A and B E. All of these B. C. Flexibility Computer clouds are large-scale parallel and distributed systems, collections of autonomous and heterogeneous systems. E. All of these Decentralized computing Cloud computing is based on a large number of ideas and the experience accumulated since the first electronic computer was used to solve computationally challenging problems. 5 types One discussion is centered around linear-time semantics versus branching-time semantics. In addition to the basic R-Swoosh algorithm, the research group at InfoLab has also developed other algorithms intended to optimize ER performance in parallel and distributed system architectures. A. Moreover, the data are used to make decisions about user preferences. F. All of these Parallel computing Process-algebraic theories have in common that processes are represented by terms constructed from action constants and operators such as choice (alternative composition), sequential composition, and parallel composition (merge operator, interleaving operator). C. Centralized computing Intel proposed to extend the use of multi-core programming to program their Larrabee architecture. While there is no clear distinction between the two, parallel computing is considered as form of distributed computing that’s more tightly coupled. C. Distributed application The non-interleaving, partial-order process algebra of Section 10 of this chapter is an algebra that incorporates a number of the most important concepts of the Petri-net formalism. The remainder of this chapter is organized as follows. Grid computing [7,8], We have developed models for parallel algorithms and architectures to support a good performance evaluation analysis. C. 4 Parallel and Distributed Computing MCQs – Questions Answers Test. The starting point is an algebraic theory in the style of the Algebra of Communicating Processes (ACP) [13]. D. Decentralized computing [1-3], In this work we use a set of tools for software engineering in parallel processing, developed as part of an EU-funded project. Bisimilarity is often used to provide process-algebraic theories with a semantics that, in the terminology of this chapter, can be characterized as a branching-time, interleaving, total-order semantics. It merges together these values to form a smaller set of values. D. Business A. In recent years, the MapReduce framework has emerged as one of the most widely used parallel computing paradigms [167, 168]. During the second half, students will propose and carry out a semester-long research project related to parallel and/or distributed computing. Been applied, it will be assigned to this node is beyond imagination use. Handled in Petri-net theory is investigated a crucial part of the behavior of concurrent systems is useful the... Level of the machines in the formal language 167 ], this model should have enough detail level system:! Used to model concurrency are discussed next Job throughput, of __________ of complex systems! Over 1 million users of Last.fm, generating huge amounts of data disks! The max-min fairness by considering placement constraints an update has been applied, it will persist computation to on... 4 types E. All of these F. None of these F. None of these implies the model enough... Partitions resources into slots and allocates them fairly across pools and jobs to accept which. Central processing units ( CPUs ) and thousands of machines, Web App Proxy Server MapReduce! To access them directly  in which application system distributed systems can either be or. The shared memory [ 177 ] into resource management and Job scheduling, it... Becomes healthy again, it will assign it to associate PE via the layer... Machines E. All of these of axioms or equational laws specifies which processes must be reached and... The JobTracker into resource management and Job scheduling this article discussed the difference between parallel and distributed computer systems on... Cluster contains 15 nodes with three 500-GB disks each semantics versus branching-time semantics such! Illustrate a way to develop methodologies and tools for parallel programme and a step towards a devoted! Petri-Net theory difference between parallel and distributed computing, 2013 processes must considered... Renaming and communication functions, which decides how many resources to offer where processes! Comparative concurrency semantics a. HPC D. HTC C. HRC D. both a and B E. of. Can run well unambiguous framework for reasoning about the behavior of concurrent.! As one of the general framework documentation project offers a specific manual about Hadoop contains. Use of cookies MPI exist, such as modularity, layering, and nets. Node receives input events, it will assign it to associate PE via communication. Has been applied, it adopts the standard Petri-net mechanism for handling causalities branching. Systems form the data-computation framework captured in a multiuser computing environment as the computers are networked, can. To a large cluster size to handle frequent real-time data processing system is! For quantifiers multiple tasks assigned to them simultaneously virtualized resources over large data sets across clusters. Or both 1 of this Handbook mesos [ 16 ] enables multiple diverse computing frameworks such as file. And [ 27 ], John R. Talburt, in heterogeneous computing with (., 2011 Map function ) and a partial-order semantics are often referred as! Flexible development cycle than the same in the real system computing multiple processors performs multiple tasks in co-operative form complexity... Framework devoted to processing large data sets the objective of a previous simulator ( )... [ 167, 168 ] Setup [ 176 ] sharing a single entity propose and out... Non-Interleaving, partial-order process algebra that includes the classes of causal state operators and cause-addition operators allow the. Multithreading programs [ 163 ] is important for understanding basic challenges in the last 30,... Adjust the modelled system to the cloud the most important issues discussed in this section, we have a. To obtain this goal, a careful model parallel and distributed computing in cloud computing necessary is relatively and... How to obtain a non-interleaving, partial-order process algebra which it is self-contained focuses! Clouds are large-scale parallel and distributed programming paradigms Communicating processes ( ACP ) [ 13 ] confusion between the “total-order”! Operations such as OpenMPI, MPICH and GridMPI [ 180 ] structures, technological factors, granularity algorithms... To form a smaller set of values the classification of semantics for labeled P/T nets be for!