ASSIST: An FDO Source-to-Source Transformation Tool for HPC Applications

Youenn Lebras, Andres S. Charif Rubial, Romain Dolbeau and William Jalby ()
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Youenn Lebras: UVSQ/Exascale Computing Research
Andres S. Charif Rubial: UVSQ/Exascale Computing Research
Romain Dolbeau: Atos
William Jalby: UVSQ/Exascale Computing Research

A chapter in Tools for High Performance Computing 2017, 2019, pp 39-56 from Springer

Abstract: Abstract The complexity and the diversity of computer architectures have dramaticaly evolved over the last decade, which makes it impossible to manually optimize codes for all these architectures. In addition, compilers must remain conservative with respect to their optimization choices because of their static cost model. One way to guide them is to use feedback data from data profiling of a representative training dataset (FDO/PGO) for a given application. It then becomes possible, based on that knowledge, to add specific compiler directives and/or flags to enhance performance. Moreover, automatic transformations simplifying portions of the application (e.g. specialization) can be applied. In this paper we present ASSIST, a directive-oriented source-to-source manipulation tool that aims at providing such assistance. The tool is integrated into the MAQAO toolset and takes advantage of all the available static and dynamic profiling data produced by the other tools. It also features a set of code transformations triggered by directives. The combination of both leads to an autotuning process that helps users to keep their code as generic as possible whilst also benefiting from a performance gain related to feedback or user knowledge. We demonstrate how we can build a compiler’s PGO-like tool and compare our first results to the Intel compiler PGO mode.

Date: 2019
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DOI: 10.1007/978-3-030-11987-4_3

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