Xavier Teruel 's publication

Monitoring Heterogeneous Applications with the OpenMP Tools Interface

Michael Wagner, Germán Llort, Antonio Filgueras, Daniel Jiménez-González, Harald Servat, Xavier Teruel, Estanislao Mercadal, Carlos Álvarez, Judit Giménez, Xavier Martorell, Eduard Ayguadé and Jesús Labarta. Monitoring Heterogeneous Applications with the OpenMP Tools Interface. In Proceedings of Tools for High Performance Computing 2016. (p. 41-57). Stuttgart, GERMANY.

Integration of the OMPT features to our parallel runtime system and instrumentation framework helps to obtain detailed performance information about the execution of the accelerated tasks issued to the devices to allow an insightful analysis. The evaluation is focused in monitoring FPGA devices.

Abstract

Heterogeneous systems are gaining more importance in supercomputing, yet they are challenging to program and developers require support tools to understand how well their accelerated codes perform and how they can be improved. The OpenMP Tools Interface (OMPT) is a new performance monitoring interface that is being considered for integration into the OpenMP standard. OMPT allows monitoring the execution of heterogeneous OpenMP applications by revealing the activity of the runtime through a standardized API as well as facilitating the exchange of performance information between devices with accelerated codes, and the analysis tool. In this paper we describe our efforts implementing parts of the OMPT specification necessary to monitor accelerators. In particular, the integration of the OMPT features to our parallel runtime system and instrumentation framework helps to obtain detailed performance information about the execution of the accelerated tasks issued to the devices to allow an insightful analysis. As a result of this analysis, the parallel runtime of the programming model has been improved. We focus on the evaluation of monitoring FPGA devices studying the performance of a common kernel in scientific algorithms: matrix multiplication. Nonetheless, this development is as well applicable to monitor GPU accelerators and Intel; Xeon PhiTM co-processors operating under the OmpSs programming model.

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