A Tool For The Simulation Of Stream Processing Tasks On Two Dimensional Processor Arrays

ABSTRACT

A tool for the simulation of stream processing tasks on two dimensional processor arrays is developed in this work. The tool, a Many-core Energy and Latency Estimator (MELE) has provided abstractions from the many design constraints facing application developers on Many-core platforms. A set of models have been designed to improve the programmer’s ability to iteratively map data flow applications to the target machine. Included in the model set are; an application model, which presents the resource requirements of the application to the virtual machine; a machine model, which collects the parameters of the modeled machine, and makes use of a set of performance functions in calculating the delay in carrying out tasks; and an energy model, which uses a set of energy functions to calculate the energy cost of carrying out tasks. The set of models transforms the application mapped to the virtual machine into its Intermediate Representation. An Abstract Interpreter has been developed to run on the Ptolemy II modeling platform as a means of returning feedback from the Intermediate Representation to the programmer. Two case studies have been used to showcase the use of MELE in analyzing the mapping of data flow applications. The case studies have also been used to explain how a rank based system can arrive at the most suitable mapping of an application to the processor. Results from the case studies show that the use of a greater number of cores in the processing does not necessarily result in the highest ranked mapping. Also, separate mappings arrive at their steady state processing cost values at different times. Based on these results, developers can now simulate the performance of several processors using one generic tool and arrive at the optimum mapping for an application.

Keywords: Many-core, Energy, Latency, Generic, Hardware, Ranking