Performance-measurement tools in a multiprocessor environment

Burkhart, Helmar; Millen, R.

doi:10.1109/12.24274

Cited by 54 publications

(15 citation statements)

References 24 publications

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“…Thus, efforts have also been made to develop software tools [5], [12]. The advantage of software tools over analytical model is that not only will they cover a wider spectrum of architectures and algorithms but also can be used to debug parallel programs and to find possible bottlenecks.…”

Section: Related Workmentioning

confidence: 99%

Cost and time-cost effectiveness of multiprocessing

Sarkar

1993

IEEE Trans. Parallel Distrib. Syst.

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Speedup and efficiency are two measures for performance of pipelined computers. Now, these measures are used to evaluate performance of parallel algorithms for multiprocessor systems. However, to evaluate the performance of a parallel algorithm, these measures consider only the computation time and number of processors used, but do not include the number of the communication links in the system. In this paper, we define two new measures, cost effectiveness and time-cost effectiveness, for evaluating performance of a parallel algorithm for a multiprocessor system. From these two measures we define two characterization factors for multiprocessor systems. We use these new characterizing factors to analyze some well-known multiprocessor systems. It is found that for a given penalty function, every multiprocessor architecture has an optimal number of processors that produces maximum profit. If "too many" processors are used, the higher cost of the system reduces the profit obtained from the faster solution. On the other hand, if "too few" processors are used, the penalty paid for taking a longer time to obtain the solution reduces the profit.

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Section: Related Workmentioning

confidence: 99%

Cost and time-cost effectiveness of multiprocessing

Sarkar

1993

IEEE Trans. Parallel Distrib. Syst.

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“…In the early reports in the literature, relevant to the agent systems in the computer science, the word "agent" was used in the similar way. Burkhart and Millen [3] in their paper introduced many types of agents that have assigned specific tasks, realized in the IT system. This can be considered as the initial form of a multi-agent system, because not only the tasks carried out by agents, but also the relationships between agents was described.…”

Section: The Definition Of Agent and The Multiagent Systemmentioning

confidence: 99%

The comparison of the use of holonic and agent-based methods in modelling of manufacturing systems

Foit

Banas

Gwiazda

et al. 2017

IOP Conf. Ser.: Mater. Sci. Eng.

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Abstract. The rapid evolution in the field of industrial automation and manufacturing is often called the 4 th Industry Revolution. Worldwide availability of the internet access contributes to the competition between manufacturers, gives the opportunity for buying materials, parts and for creating the partnership networks, like cloud manufacturing, grid manufacturing (MGrid), virtual enterprises etc. The effect of the industry evolution is the need to search for new solutions in the field of manufacturing systems modelling and simulation. During the last decade researchers have developed the agent-based approach of modelling. This methodology have been taken from the computer science, but was adapted to the philosophy of industrial automation and robotization. The operation of the agent-based system depends on the simultaneous acting of different agents that may have different roles. On the other hand, there is the holon-based approach that uses the structures created by holons. It differs from the agentbased structure in some aspects, while the other ones are quite similar in both methodologies. The aim of this paper is to present the both methodologies and discuss the similarities and the differences. This may could help to select the optimal method of modelling, according to the considered problem and software resources.

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“…As done with performance monitoring, modeling can classify different parts of the program in order to obtain a detailed scalability profile (loss analysis [3,2]). The relative influence of the different program phases on the program's execution time can be determined in the model.…”

Section: Automatic Scalability Analysis With the Tool Peppmentioning

confidence: 99%

Automatic scalability analysis of parallel programs based on modeling techniques

Malony

Mertsiotakis

Quick³

1994

Computer Performance Evaluation Modelling Techniques and Tools

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When implementing parallel programs for parallel computer systems the performance scalability of these programs should be tested and analyzed on different computer configurations and problem sizes. Since a complete scalability analysis is too time consuming and is limited to only existing systems, extensions of modeling approaches can be considered for analyzing the behavior of parallel programs under different problem and system scenarios.In this paper, a method for automatic scalability analysis using modeling is presented. Initially, we identify the important problems that arise when attempting to apply modeling techniques to scalability analysis. Based on this study, we define the Parallelization Description Language (PDL) that is used to describe parallel execution attributes of a generic program workload. Based on a parallelization description, stochastic models like graph models or Petri net models can be automatically generated from a generic model to analyze performance for scaled parallel systems as well as scaled input data.The complexity of the graph models produced depends significantly on the type of parallel computation described. We present several computation classes where tractable graph models can be generated and then compare the results of these automatically scaled models with their exact solutions using the PEPP modeling tool.

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Performance-measurement tools in a multiprocessor environment

Cited by 54 publications

References 24 publications

Cost and time-cost effectiveness of multiprocessing

Cost and time-cost effectiveness of multiprocessing

The comparison of the use of holonic and agent-based methods in modelling of manufacturing systems

Automatic scalability analysis of parallel programs based on modeling techniques

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