The evolution of technology provides the opportunity of forming large processor ensembles working closely together. When decomposing application programs and assigning subtasks to different processors we expect not only high throughput, but also the fastest possible execution of each individual demand. The level of performance in these areas is strongly influenced by the hardware interconnection structure and by the communication software.

Experiences with Performance Measurement and Modeling of a Processor Array

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 modeling tool PEPP.

/pdf/automatic-scalability-analysis-of-parallel-programs-based-on-49ujjgc0wm.pdf

Automatic scalability analysis of parallel programs based on modeling techniques

Introduces queuing network models for the performance analysis of SPMD (single-program, multiple-data) applications executed on general-purpose parallel architectures such as MIMD (multiple-input, multiple data) and clusters of workstations. The models are based on the pattern of computation, communication and I/O operations of typical parallel applications. Analysis of the models leads to the definition of speedup surfaces which capture the relative influence of processors and I/O parallelism and show the effects of different hardware and software components on the performance. Since the parameters of the models correspond to measurable program and hardware characteristics, the models can be used to anticipate the performance behavior of a parallel application as a function of the target architecture (i.e. the number of processors, number of disks, I/O topology, etc.).

/pdf/integrated-performance-models-for-spmd-applications-and-mimd-13b7dkqul4.pdf

Integrated performance models for SPMD applications and MIMD architectures

In the hierarchically organized multiprocessor system EGPA, which has the structure of a pyramid, the performance of concurrent programs is studied. These studies are assisted by a hardware monitor (ZAHLMONITOR III), which measures not only the activity and idle states of CPU and channels, but records the complete history of processes in the CPU and interleaved I/O activities. The applied method is distinguished from usual hardware measurements for two reasons: it puts together the a priori independent event-streams coming from the different processors to a well ordered single event stream and it records not only hardware but also software events. Most useful have been traces of software events, which give the programmer insight into the dynamic cooperation of distributed subtasks of his program. This paper describes the measurement method and its application to the analysis of the behaviour of a highly asynchronous parallel algorithm: the projection of contour lines from a given point of view and the elimination of hidden lines.This work is sponsored by the Bundesminister fur Forschung und Technologie (German Federal Minister of Research and Technology).

Measuring simultaneous events in a multiprocessor system

The goal of performance and reliability evaluation during the development of computerbased systems is to predict the compliance of the projected system with a set of non-functional requirements. As an example, consider the expected mean end-to-end delay of data packets in a communication network, which can be predicted on the basis of a stochastic model during the early conceptual design phase. A glance at the software engineering practice reveals that despite their high financial savings potential academic methods of performance evaluation are not applied on a large scale. Frequently quoted reasons for these findings are the cumbersome notation of some stochastic description techniques and the impractical presentation of the theoretical foundations. The successful application of performance evaluation methods thus remains reserved to a handful of well-educated experts. This phenomenon, termed insularity problem by some members of the academic performance evaluation community, can be regarded as a special case of the general problem of low formal method acceptance in industrial software development. The first formal methods were developed by several computer scientists about 40 years ago with the ambitious goal to create programs which are proven to be correct by construction. Because of the quite revolutionary approach to programming and the inability of their developers to show that formal methods are appropriate to solve larger real-world problems they did not become widely accepted and used by the software engineering industry. A promising attempt to bridge this “industry-academia gap” was initiated in the early-mid 1990s with the advent of “lightweight” formal methods for the verification of functional system requirements, some of which could be applied successfully in industrial software development projects. The initial point of view which is adopted in this dissertation is to regard performance evaluation as a branch of requirements verification techniques which are applied during the development of software-based systems. Because of the similarities in the structure and the objectives of the methods in both areas, we assume that the transfer of the lightweight formal method concept to the area of performance evaluation will have a positive effect on the solution of the insularity problem. In order to corroborate this assumption, a new lightweight formal method for the prediction of nonfunctional system requirements is developed within the scope of this thesis. The method consists of a formal description technique which is based on a well-defined syntax and semantics. It enables the user to specify the system structure and behaviour, the interaction of the system with its enviroment as well as the interesting nonfunctional system requirements as a stochastic model on a high abstraction level. The syntax of our description language combines the advantages of the pragmatic network-oriented modelling paradigm with the succinctness of a pure textual notation. The evaluation of the system properties is carried out in a user-friendly manner by the automatic analysis of the model in the evaluation environment prototype which was implemented in the context of this thesis. In order to demonstrate the applicability of the method we present some detailed case studies from the area of communication systems (WLAN, GSM). The keynote of this dissertation is to promote the transfer of technology from academia to industry by the integration of formal methods for performance and reliability evaluation in the early phases of the software development process.

https://www4.cs.fau.de/~barner/me/barner05alightweight.pdf

A Lightweight Formal Method for the Prediction of Non-Functional System Properties

Synchronization Problems in Hierarchically Organized Multiprocessor Computer Systems

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Synchronization Problems in Hierarchically Organized Multiprocessor Computer Systems