A workflow for holistic performance system analysis

Abstract

This document describes the performance-analysis workflow defined in Task 3.2 of Work Package 3 of the EU FP7 project HOPSA. The HOPSA project (HOlistic Performance System Analysis) sets out for the first time to develop an integrated diagnostic infrastructure for combined application and system tuning. The document guides application developers in the process of tuning and optimising their codes for performance. It describes which tools should be used in which order to accomplish common performance analysis tasks. Since the document addresses primarily the user’s perspective, it follows the style of a user guide. It does, however, not replace the user guides of individual performance- analysis tools developed in HOPSA but rather connects them as it shows how to use the tools in a complementary way. At the centre of this document is the so-called lightweight measurement module (LWM2). Being responsible for the first step in the workflow, the system-wide mandatory collection of basic performance data, the module is covered in greater detail. Special emphasis is given to the interpretation of the job digest created with the help of LWM2. The metrics listed in this compact report indicate whether an application suffers from an inherent performance problem or whether application interference may have been at the root of dissatisfactory behaviour. They also provide a first assessment regarding the nature of a potential performance problem and help to decide on further diagnostic steps using any of the more powerful performance-analysis tools. For each of those tools, a short summary is given with information on the most important questions it can help to answer. Moreover, the document covers Score-P, a common measurement infrastructure shared by some of the tools. The performance data types supported by Score-P form a natural refinement hierarchy that can be followed to track down and represent even complex bottleneck situations at increasing levels of granularity. Finally, a brief excursion on system tuning explains how system providers can leverage the data collected by LWM2 to identify a suboptimal system configuration or faulty components