ACM Transactions on Computer Systems (TOCS)
Analytic Queueing Network Models for Parallel Processing of Task Systems
IEEE Transactions on Computers
Performance and Reliability Analysis Using Directed Acyclic Graphs
IEEE Transactions on Software Engineering
On the computation of performance characteristics of concurrent programs using GSPNs
Performance Evaluation - Special issue: performance modeling of parallel processing systems
Static and dynamic processor scheduling disciplines in heterogeneous parallel architectures
Journal of Parallel and Distributed Computing
Predicting Performance of Parallel Computations
IEEE Transactions on Parallel and Distributed Systems
Analysis of Fork-Join Program Response Times on Multiprocessors
IEEE Transactions on Parallel and Distributed Systems
Dependability Modeling and Analysis of Distributed Programs
IEEE Transactions on Software Engineering
Toward a Definition of Modeling Power for Stochastic Petri Net Models
PNPM '87 The Proceedings of the Second International Workshop on Petri Nets and Performance Models
Concurrency in parallel processing systems (distributed, multiprocessing)
Concurrency in parallel processing systems (distributed, multiprocessing)
A probabilistic framework for estimation of execution time in heterogeneous computing systems
A probabilistic framework for estimation of execution time in heterogeneous computing systems
Performance Analysis Using Stochastic Petri Nets
IEEE Transactions on Computers
Representation and analysis of behavior for multiprocess systems by using stochastic Petri nets
Mathematical and Computer Modelling: An International Journal
Specification and Control of Cooperative Work in a Heterogeneous Computing Environment
HCW '98 Proceedings of the Seventh Heterogeneous Computing Workshop
Simulation of Task Graph Systems in Heterogeneous Computing Environments
HCW '99 Proceedings of the Eighth Heterogeneous Computing Workshop
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A stochastic Petri net (SPN) is systematically constructed from a task graph whose component subtasks are statically allocated onto the processor suite of a heterogeneous computing system (HCS). Given that subtask execution times are exponentially distributed an exponential distribution can be generated for the overall completion time. In particular the enabling functions and rate functions used to specify the SPN model provide needed versatility to integrate processor heterogeneity, task priorities, allocation schemes, communication costs, and other factors characteristic of a HCS into a comprehensive performance analysis. The manner in which these parameters are incorporated into the SPN allows the model to be transformed into a testbed for optimization schemes and heuristics. The proposed approach can be applied to arbitrary task graphs including non-series-parallel.