PAPIFY: Automatic Instrumentation and Monitoring of Dynamic Dataflow Applications Based on PAPI

Abstract

The widening of the complexity-productivity gap in application development witnessed in the last years is becoming an important issue for the developers. New design methods try to automate most designers tasks to bridge this gap. In addition, new Model of Computations (MoCs), as those dataflow-based, ease the expression of parallelism within applications, leading to higher designer productivity. Rapid prototyping design tools offer fast estimations of the soundness of design choices. A key step when prototyping an application is to have representative performance indicators to estimate the validity of those design choices. Such indicators can be obtained using hardware information, while new libraries, e.g.,Performance Application Programming Interface (PAPI), ease the access to such hardware information. In this work, PAPIFY toolbox is presented as a tool to perform automatic PAPI-based instrumentation of dynamic dataflow applications. It combines PAPIFY with a dataflow Y-chart based design framework, which is called PREESM, and its companion run-time reconfiguration manager, which is called Synchronous Parameterized and Interfaced Dataflow Embedded Runtime (SPiDER). PAPIFY toolbox accounts for an automatic code generator for static and dynamic applications, a dedicated library to manage the monitoring at run-time and two User Interfaces (UIs) to ease both the configuration and the analysis of the captured run-time information. Additionally, its main advantages are 1) its capability of adapting the monitoring according to the system status and 2) adaptation of the monitoring accordingly to application workload redistribution in run-time. A thorough overhead characterization using Sobel-morpho and Stereo-matching dataflow applications shows that PAPIFY run-time monitoring overhead is up to 10%.

Keywords

• Performance monitoring
• PMCs
• PAPI
• automatic code generation
• dataflow
• models of computation