{"id":581749,"date":"2019-04-26T14:41:19","date_gmt":"2019-04-26T21:41:19","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=581749"},"modified":"2019-04-26T14:42:53","modified_gmt":"2019-04-26T21:42:53","slug":"getting-more-performance-with-polymorphism-from-emerging-memory-technologies","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/getting-more-performance-with-polymorphism-from-emerging-memory-technologies\/","title":{"rendered":"Getting More Performance with Polymorphism from Emerging Memory Technologies"},"content":{"rendered":"<p>Storage-intensive systems in data centers rely heavily on DRAM and SSDs for the performance of reads and persistent writes, respectively. These applications pose a diverse set of requirements, and are limited by fixed capacity, fixed access latency, and fixed function of these resources as either memory or storage. In contrast, emerging memory technologies like 3D-Xpoint, battery-backed DRAM, and ASIC-based fast memory-compression offer capabilities across several dimensions. However, existing proposals to use such technologies can only improve either read or write performance but not both without requiring extensive changes to the application,and the operating system. We present PolyEMT, a system that employs an emerging memory technology based cache to the SSD, and transparently morphs the capabilities of this cache across several dimensions &#8211; persistence, capacity, latency &#8211; to jointly improve both read and write performance. We demonstrate the benefits of PolyEMT using several large-scale storage-intensive workloads from our data centers.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Storage-intensive systems in data centers rely heavily on DRAM and SSDs for the performance of reads and persistent writes, respectively. These applications pose a diverse set of requirements, and are limited by fixed capacity, fixed access latency, and fixed function of these resources as either memory or storage. In contrast, emerging memory technologies like 3D-Xpoint, [&hellip;]<\/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":"ACM","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":"","msr_copyright":"","msr_conference_name":"International Systems and Storage Conference (SYSTOR)","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":"","msr_release_tracker_id":"","msr_s2_match_type":"","msr_citation_count_updated":"","msr_published_date":"2019-4-28","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":true,"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":[193716],"msr-publisher":[],"msr-focus-area":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-581749","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"ACM","msr_edition":"","msr_affiliation":"","msr_published_date":"2019-4-28","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","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":1,"msr_main_download":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2019\/04\/systor19-final17.pdf","id":"581791","title":"systor19-final17","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":[{"id":581791,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2019\/04\/systor19-final17.pdf"}],"msr-author-ordering":[{"type":"text","value":"Iyswarya Narayanan","user_id":0,"rest_url":false},{"type":"text","value":"Aishwarya Ganesan","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Anirudh Badam","user_id":31008,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Anirudh Badam"},{"type":"user_nicename","value":"Sriram Govindan","user_id":33706,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Sriram Govindan"},{"type":"text","value":"Bikash Sharma","user_id":0,"rest_url":false},{"type":"text","value":"Anand Sivasubramaniam","user_id":0,"rest_url":false}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[],"msr_project":[171456],"publication":[],"video":[],"msr-tool":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":171456,"post_title":"Navamem","post_name":"kamino","post_type":"msr-project","post_date":"2015-04-17 16:53:15","post_modified":"2019-04-26 14:44:40","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/kamino\/","post_excerpt":"The Navamem project explores ways in which systems should adopt new memory technologies including SSDs (NAND-Flash), battery-backed DRAM and emerging non-volatile memory technologies (phase change memory, memristors, spin-torque transfer memory, etc.) for increased performance and efficiency. The project explores how to best leverage such new memory technologies inside systems of all sizes and shapes: from mobile to data center scale. Former Interns: Jian Huang, Georgia Tech (2013, 2014, &amp; 2015) Jing Li, UCSD (2013) Yanqi&hellip;","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/171456"}]}}]},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/581749","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-research-item"}],"version-history":[{"count":1,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/581749\/revisions"}],"predecessor-version":[{"id":581800,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/581749\/revisions\/581800"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=581749"}],"wp:term":[{"taxonomy":"msr-research-highlight","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-highlight?post=581749"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=581749"},{"taxonomy":"msr-publication-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publication-type?post=581749"},{"taxonomy":"msr-publisher","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publisher?post=581749"},{"taxonomy":"msr-focus-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-focus-area?post=581749"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=581749"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=581749"},{"taxonomy":"msr-field-of-study","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-field-of-study?post=581749"},{"taxonomy":"msr-conference","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-conference?post=581749"},{"taxonomy":"msr-journal","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-journal?post=581749"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=581749"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=581749"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}