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12
SPNP: Stochastic Petri Net Package
, 1989
"... We present SPNP, a powerful GSPN package developed at Duke University. SPNP allows the modeling of complex system behaviors. Advanced constructs are available, such as marking dependent arc multiplicities, enabling functions, arrays of places or transitions, and subnets; in addition, the full expres ..."
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Cited by 155 (34 self)
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We present SPNP, a powerful GSPN package developed at Duke University. SPNP allows the modeling of complex system behaviors. Advanced constructs are available, such as marking dependent arc multiplicities, enabling functions, arrays of places or transitions, and subnets; in addition, the full expressive power of the C programming language is available to increase the flexibility of the net description.
Performance and Reliability Analysis Using Directed Acyclic Graphs
 IEEE Trans. Software Eng
, 1987
"... AbstractA graphbased modeling technique has been developed for the stochastic analysis of systems containing concurrency. The basis of the technique is the use of directed acyclic graphs. These graphs represent eventprecedence networks where activities may occur serially, probabilistically, or co ..."
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Cited by 39 (5 self)
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AbstractA graphbased modeling technique has been developed for the stochastic analysis of systems containing concurrency. The basis of the technique is the use of directed acyclic graphs. These graphs represent eventprecedence networks where activities may occur serially, probabilistically, or concurrently. When a set of activities occurs concurrently, the condition for the set of activities to complete is that a specified number of the activities must complete. This includes the special cases that one or all of the activities must complete. The cumulative distribution function associated with an activity is assumed to have exponential polynomial form. Further generality is obtained by allowing these distributions to have a mass at the origin and/or at infinity. The distribution function for the time taken to complete the entire graph is computed symbolically in the time parameter t. The technique allows two or more graphs to be combined hierarchically. Applications of the technique to the evaluation of concurrent program execution time and to the reliability analysis of faulttolerant systems are discussed. Index TermsAvailability, directed acyclic graphs, faulttolerance, Markov models, performance evaluation, program performance, reliability. I.
A heuristic for optimizing stochastic activity networks with applications to statistical digital circuit sizing
 IEEE Transactions on Circuits and SystemsI
, 2004
"... A deterministic activity network (DAN) is a collection of activities, each with some duration, along with a set of precedence constraints, which specify that activities begin only when certain others have finished. One critical performance measure for an activity network is its makespan, which is th ..."
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Cited by 12 (4 self)
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A deterministic activity network (DAN) is a collection of activities, each with some duration, along with a set of precedence constraints, which specify that activities begin only when certain others have finished. One critical performance measure for an activity network is its makespan, which is the minimum time required to complete all activities. In a stochastic activity network (SAN), the durations of the activities and the makespan are random variables. The analysis of SANs is quite involved, but can be carried out numerically by Monte Carlo analysis. This paper concerns the optimization of a SAN, i.e., the choice of some design variables that affect the probability distributions of the activity durations. We concentrate on the problem of minimizing a quantile (e.g., 95%) of the makespan, subject to constraints on the variables. This problem has many applications, ranging from project management to digital integrated circuit (IC) sizing (the latter being our motivation). While there are effective methods for optimizing DANs, the SAN optimization problem is much more difficult; the few existing methods cannot handle largescale problems.
Bounds on the Speedup and Efficiency of Partial Synchronization in Parallel Processing Systems
 Journal of the ACM
, 1993
"... In this paper, we derive bounds on the speedup and efficiency of applications that schedule tasks on a set of parallel processors. We assume that the application runs an algorithm that consists of N iterations and before starting its i + 1'st iteration, a processor must wait for data (i.e., sync ..."
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Cited by 7 (1 self)
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In this paper, we derive bounds on the speedup and efficiency of applications that schedule tasks on a set of parallel processors. We assume that the application runs an algorithm that consists of N iterations and before starting its i + 1'st iteration, a processor must wait for data (i.e., synchronize) calculated in the i'th iteration by a subset of the other processors of the system. Processing times and interconnections between iterations are modeled by random variables with possibly deterministic distributions. Scientific applications consisting of iterations of recursive equations are examples of applications that can be modeled within this formulation. We consider the efficiency of such applications and show that, although efficiency decreases with an increase in the number of processors, it has a nonzero limit when the number of processors increases to infinity. We obtain a lower bound for the efficiency by solving a equation which depends on the distribution of task ...
Task Graph Performance Bounds Through Comparison Methods
, 2001
"... When a parallel computation is represented in a formalism that imposes seriesparallel structure on its task graph, it becomes amenable to automated analysis and scheduling. Unfortunately, its execution time will usually also increase as precedence constraints are added to ensure seriesparallel str ..."
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Cited by 5 (1 self)
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When a parallel computation is represented in a formalism that imposes seriesparallel structure on its task graph, it becomes amenable to automated analysis and scheduling. Unfortunately, its execution time will usually also increase as precedence constraints are added to ensure seriesparallel structure. Bounding the slowdown ratio would allow an informed tradeoff between the benefits of a restrictive formalism and its cost in loss of performance. This dissertation deals with seriesparallelising task graphs by adding precedence constraints to a task graph, to make the resulting task graph seriesparallel. The weak bounded slowdown conjecture for seriesparallelising task graphs is introduced. This states that the slowdown is bounded if information about the workload can be used to guide the selection of which precedence constraints to add. A theory of best seriesparallelisations is developed to investigate this conjecture. Partial evidence is presented that the weak slowdown bound is likely to be 4/3, and this bound is shown to be tight.
An Interpretive Framework for Application Performance Prediction
 Proceedings of the 1993 International Conference On Parallel and Distributed Systems
, 1993
"... Software development in parallel/distributed environment is a nontrivial task and depends greatly on the availability of appropriate support in terms of development tools and environments. Perforamnce prediction /evaluation tools form a critical part of any software development environment as they ..."
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Cited by 4 (3 self)
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Software development in parallel/distributed environment is a nontrivial task and depends greatly on the availability of appropriate support in terms of development tools and environments. Perforamnce prediction /evaluation tools form a critical part of any software development environment as they enable the developer to visualize the effects of various design choices on the performance of the application. This paper presents an interpretive model for a source driven performance prediction framework. A prototype framework based on the proposed model has been developed for the iPSC/860 system. Numerical results obtained on this system are presented. These results confirm the potential of interpretive performance prediction techniques and their applicability. Keywords: Performance prediction, Performance interpretation, Parallel/Distributed software development, System & Application characterization. 1 Introduction Software development in any Parallel/Distributed computing environment ...
Application Load Imbalance on Parallel Processors
 in Proc. of the Int. Paral. Proc. Symposium (IPPS'96
, 1996
"... This paper addresses the issue of dynamic load imbalance in a class of synchronous iterative applications, and develops a model to represent their workload dynamics. Such models of application load dynamics help in more accurate performance prediction and in the design of efficient load balancing al ..."
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Cited by 1 (0 self)
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This paper addresses the issue of dynamic load imbalance in a class of synchronous iterative applications, and develops a model to represent their workload dynamics. Such models of application load dynamics help in more accurate performance prediction and in the design of efficient load balancing algorithms. Our model captures the workload dynamics across iterations, and predicts the workload distribution at any given iteration as the cumulative effect of workload dynamics during the preceding iterations. The model parameters are derived using empirical data from initial runs of the application. The model development is illustrated using data from a parallel Nbody simulation application. 1
Probabilistic Analysis of Scheduling Precedence Constrained Parallel Tasks on Multicomputers with Contiguous Processor Allocation
 IEEE Transactions on Computer
, 2000
"... AbstractÐGiven a set of precedence constrained parallel tasks with their processor requirements and execution times, the problem of scheduling precedence constrained parallel tasks on multicomputers with contiguous processor allocation is to find a nonpreemptive schedule of the tasks on a multicompu ..."
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Cited by 1 (0 self)
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AbstractÐGiven a set of precedence constrained parallel tasks with their processor requirements and execution times, the problem of scheduling precedence constrained parallel tasks on multicomputers with contiguous processor allocation is to find a nonpreemptive schedule of the tasks on a multicomputer such that the schedule length is minimized. This scheduling problem is substantially more difficult than other scheduling problems due to precedence constraints among tasks, the inherent difficulty of task scheduling, and processor allocation in multicomputers. We present an approximation algorithm called LLB that schedules tasks levelbylevel using the largesttaskfirst strategy supported by the binary system partitioning scheme to handle the three difficult issues in our scheduling problem. Though algorithm LLB does not have a bounded worstcase performance ratio, we show through probabilistic analysis that LLB has a quite reasonable averagecase performance ratio for typical classes of parallel computations. In particular, algorithm LLB has an averagecase performance ratio less than two for large scale parallel computations that have wide task graphs (i.e., that exhibit large parallelism). Index TermsÐAveragecase performance ratio, binary system partitioning, contiguous processor allocation, largesttaskfirst, parallel task, precedence constraint, probabilistic analysis, task scheduling.
Stochastic performance prediction for iterative algorithms in distributed environments
 Journal of Parallel and Distributed Computing
, 1999
"... dongarra msr.emp.ornl.gov ..."
Stochastic Models For Performance Analyses Of Iterative Algorithms In Distributed Environments
, 1998
"... This research aims at creating a framework to analyze the performance of iterative algorithms in distributed environments. The parallelization of certain iterative algorithms is indeed a crucial issue for the efficient solution of large or complex optimization problems. Diverse implementation techni ..."
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Cited by 1 (1 self)
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This research aims at creating a framework to analyze the performance of iterative algorithms in distributed environments. The parallelization of certain iterative algorithms is indeed a crucial issue for the efficient solution of large or complex optimization problems. Diverse implementation techniques for such parallelizations have become popular. They are examined here with a view to understanding their impact on the algorithm behavior in a distributed environment. Several theoretical results concerning the sufficient conditions for, and speed of, convergence for parallel iterative algorithms are available. However, there is a gap between those results and what is relevant to the user at the application level. In particular, an estimate of the algorithm execution time is often desirable. The performance characterization presented in this dissertation follows a stochastic approach partially based on a Markov process. It addresses different characteristics of the algorithmic execution...