LU, QR, and Cholesky factorizations: Programming model, performance analysis and optimization techniques for the Intel Knights Landing Xeon Phi

Azzam Haidar, Stanimire Tomov, Konstantin Arturov, Murat Guney, Shane Story, Jack Dongarra

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Scopus citations

Abstract

A wide variety of heterogeneous compute resources, ranging from multicore CPUs to GPUs and coprocessors, are available to modern computers, making it challenging to design unified numerical libraries that efficiently and productively use all these varied resources. For example, in order to efficiently use Intel's Knights Landing (KNL) processor, the next-generation of Xeon Phi architectures, one must design and schedule an application in multiple degrees of parallelism and task grain sizes in order to obtain efficient performance. We propose a productive and portable programming model that allows us to write a serial-looking code, which, however, achieves parallelism and scalability by using a lightweight runtime environment to manage the resource-specific workload, and to control the dataflow and the parallel execution. This is done through multiple techniques ranging from multi-level data partitioning to adaptive task grain sizes, and dynamic task scheduling. In addition, our task abstractions enable unified algorithmic development across all the heterogeneous resources. Finally, we outline the strengths and the effectiveness of this approach - especially in regards to hardware trends and ease of programming high-performance numerical software that current applications need - in order to motivate current work and future directions for the next generation of parallel programming models for high-performance linear algebra libraries on heterogeneous systems.

Original languageEnglish
Title of host publication2016 IEEE High Performance Extreme Computing Conference, HPEC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509035250
DOIs
StatePublished - Nov 28 2016
Event2016 IEEE High Performance Extreme Computing Conference, HPEC 2016 - Waltham, United States
Duration: Sep 13 2016Sep 15 2016

Publication series

Name2016 IEEE High Performance Extreme Computing Conference, HPEC 2016

Conference

Conference2016 IEEE High Performance Extreme Computing Conference, HPEC 2016
Country/TerritoryUnited States
CityWaltham
Period09/13/1609/15/16

Funding

This material is based upon work supported by the National Science Foundation under Grant ACI-1339822, the Department of Energy, and Intel. The results were obtained in part with the financial support of the Russian Scientific Fund, Agreement N14-11-00190.

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