Workload\u2010aware loop schedulers were introduced to deliver better performance than classical loop scheduling strategies. However, they presented limitations such as inflexible built\u2010in workload estimators and suboptimal chunk scheduling. Targeting these challenges, we proposed previously a workload\u2010aware scheduling strategy called BinLPT, which relies on three features: (i) user\u2010supplied estimations of the workload of the loop; (ii) a greedy heuristic that adaptively partitions the iteration space in several chunks; and (iii) a scheduling scheme based on the Longest Processing Time (LPT) rule and on\u2010demand technique. In this paper, we present two new contributions to the state\u2010of\u2010the\u2010art. First, we introduce a multiloop support feature to BinLPT, which enables the reuse of estimations across loops. Based on this feature, we integrated BinLPT into a real\u2010world elastodynamics application, and we evaluated it running on a supercomputer. Second, we present an evaluation of BinLPT using simulations as well as synthetic and application kernels. We carried out this analysis on a large\u2010scale NUMA machine under a variety of workloads. Our results revealed that BinLPT is better at balancing the workloads of the loop iterations and this behavior improves as the algorithmic complexity of the loop increases. Overall, BinLPT delivers up to 37.15% and 9.11% better performance than well\u2010known loop scheduling strategies, for the application kernels and the elastodynamics simulation, respectively.<\/p>\n","protected":false},"excerpt":{"rendered":"
Workload\u2010aware loop schedulers were introduced to deliver better performance than classical loop scheduling strategies. However, they presented limitations such as inflexible built\u2010in workload estimators and suboptimal chunk scheduling. Targeting these challenges, we proposed previously a workload\u2010aware scheduling strategy called BinLPT, which relies on three features: (i) user\u2010supplied estimations of the workload of the loop; (ii) […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"31","msr_copyright":"","msr_conference_name":"","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"","msr_other_contributors":"","msr_speaker":"","msr_award":"","msr_affiliation":"","msr_institution":"","msr_host":"","msr_version":"","msr_duration":"","msr_original_fields_of_study":null,"msr_release_tracker_id":"","msr_s2_match_type":"","msr_citation_count_updated":"","msr_published_date":"2019-2-18","msr_highlight_text":"","msr_notes":"","msr_longbiography":"","msr_publicationurl":"","msr_external_url":"","msr_secondary_video_url":"","msr_conference_url":"","msr_journal_url":"","msr_s2_pdf_url":"","msr_year":0,"msr_citation_count":0,"msr_influential_citations":0,"msr_reference_count":0,"msr_s2_match_confidence":0,"msr_microsoftintellectualproperty":false,"msr_s2_open_access":false,"msr_s2_author_ids":[],"msr_pub_ids":[],"msr_hide_image_in_river":0,"footnotes":""},"msr-research-highlight":[],"research-area":[13547],"msr-publication-type":[193715],"msr-publisher":[],"msr-focus-area":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[246691],"msr-conference":[],"msr-journal":[268788],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-1047165","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us","msr-field-of-study-computer-science"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2019-2-18","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"31","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":0,"msr_main_download":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"doi","viewUrl":"false","id":"false","title":"https:\/\/doi.org\/10.1002\/cpe.5170","label_id":"243106","label":0},{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/dblp.org\/rec\/journals\/concurrency\/PennaGCPFBM19.html","label_id":"243109","label":0},{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/hal.archives-ouvertes.fr\/hal-01986361\/file\/ccpe18.pdf","label_id":"243109","label":0}],"msr_related_uploader":"","msr_citation_count":0,"msr_citation_count_updated":"","msr_s2_paper_id":"","msr_influential_citations":0,"msr_reference_count":0,"msr_arxiv_id":"","msr_s2_author_ids":[],"msr_s2_open_access":false,"msr_s2_pdf_url":null,"msr_attachments":[],"msr-author-ordering":[{"type":"user_nicename","value":"Pedro Henrique Penna","user_id":40522,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Pedro Henrique Penna"},{"type":"text","value":"A. 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