{"created":"2020-09-01T10:06:07.943445+00:00","id":3407,"links":{},"metadata":{"_buckets":{"deposit":"9831dcc8-a69a-4924-977c-e4bd70561aa6"},"_deposit":{"id":"3407","owners":[],"pid":{"revision_id":0,"type":"recid","value":"3407"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/3407","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Job Scheduling for High Performance Computing and Cloud Environment","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"High performance computing (HPC) is famousand latest trend in current research era. User requestmany jobs and they want to get accurate results andquick time within eye blink. There are so manyprocessors running large data centers and largesystems. So many processes will work large datacenter and large system. Many jobs within highperformance scheduling environment is preparing thejob to understand and calculate to get the improveresult and to reduce the processing time in a system.Requests for greater capacity were met by buildingmore powerful systems with more compute nodes,scalability and higher processor operatingfrequencies for business applications, education, andscientific application. There are various ways toschedule parallel jobs but in this paper discussessome of the technical challenges ,methods ofscheduling and one of proposed system in cloud(HPC) environment."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value_mlt":[{"interim":"HPC"},{"interim":"preparing jobs"},{"interim":"technical challenges"},{"interim":"scheduling methods"}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-07-22"}],"displaytype":"preview","filename":"ICCA 2019 Proceedings Book-pages-59-63.pdf","filesize":[{"value":"246 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/3407/files/ICCA 2019 Proceedings Book-pages-59-63.pdf"},"version_id":"708c98eb-2a96-44c5-96b6-8c5fd208b465"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Seventeenth International Conference on Computer Applications(ICCA 2019)","subitem_pages":"","subitem_volume":""}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"","subitem_c_date":"","subitem_conference_title":"","subitem_part":"","subitem_place":"","subitem_session":"","subitem_website":""}]},"item_1583103211336":{"attribute_name":"Books/reports/chapters","attribute_value_mlt":[{"subitem_book_title":"","subitem_isbn":"","subitem_pages":"","subitem_place":"","subitem_publisher":""}]},"item_1583103233624":{"attribute_name":"Thesis/dissertations","attribute_value_mlt":[{"subitem_awarding_university":"","subitem_supervisor(s)":[{"subitem_supervisor":""}]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Kyaw, Lett Yi"},{"subitem_authors_fullname":"Phyu, Sabai"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Article"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2019-02-27"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/1161"},"item_title":"Job Scheduling for High Performance Computing and Cloud Environment","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-07-22","publish_status":"0","recid":"3407","relation_version_is_last":true,"title":["Job Scheduling for High Performance Computing and Cloud Environment"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T00:57:06.900806+00:00"}