{"_buckets": {"deposit": "4475dc19-1cca-4b4e-b90a-e1d7e6841b2d"}, "_deposit": {"created_by": 7, "id": "6401", "owners": [7], "pid": {"revision_id": 0, "type": "depid", "value": "6401"}, "status": "published"}, "_oai": {"id": "oai:nied-repo.bosai.go.jp:00006401", "sets": []}, "author_link": [], "item_10001_biblio_info_7": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2018", "bibliographicIssueDateType": "Issued"}, "bibliographicPageEnd": "23", "bibliographicPageStart": "12", "bibliographic_titles": [{"bibliographic_title": "PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING IN ASIA-PACIFIC REGION (HPC ASIA 2018)", "bibliographic_titleLang": "en"}]}]}, "item_10001_description_5": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "MPI-IO has been used in an internal I/O interface layer of HDF5 or PnetCDF, where collective MPI-IO plays a big role in parallel I/O to manage a huge scale of scientific data. However, existing collective MPI-IO optimization named two-phase I/O has not been tuned enough for recent supercomputers consisting of mesh/torus interconnects and a huge scale of parallel file systems due to lack of topology-awareness in data transfers and optimization for parallel file systems. In this paper, we propose I/O throttling and topology-aware stepwise data aggregation in two-phase I/O of ROMIO, which is a representative MPI-IO library, in order to improve collective MPI-IO performance even if we have multiple processes per compute node. Throttling I/O requests going to a target file system mitigates I/O request contention, and consequently I/O performance improvements are achieved in file access phase of two-phase I/O. Topology-aware aggregator layout with paying attention to multiple aggregators per compute node alleviates contention in data aggregation phase of two-phase I/O. In addition, stepwise data aggregation improves data aggregation performance. HPIO benchmark results on the K computer indicate that the proposed optimization has achieved up to about 73% and 39% improvements in write performance compared with the original implementation using 12,288 and 24,576 processes on 3,072 and 6,144 compute nodes, respectively.", "subitem_description_language": "en", "subitem_description_type": "Other"}]}, "item_10001_publisher_8": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "ASSOC COMPUTING MACHINERY", "subitem_publisher_language": "en"}]}, "item_10001_relation_14": {"attribute_name": "DOI", "attribute_value_mlt": [{"subitem_relation_type_id": {"subitem_relation_type_id_text": "10.1145/3149457.3149464"}}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Yuichi Tsujita", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Atsushi Hori", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Toyohisa Kameyama", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Atsuya Uno", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Fumiyoshi Shoji", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Yutaka Ishikawa", "creatorNameLang": "en"}]}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_title": "Improving Collective MPI-IO Using Topology-Aware Stepwise Data Aggregation with I/O Throttling", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "Improving Collective MPI-IO Using Topology-Aware Stepwise Data Aggregation with I/O Throttling", "subitem_title_language": "en"}]}, "item_type_id": "40001", "owner": "7", "path": ["1670839190650"], "permalink_uri": "https://nied-repo.bosai.go.jp/records/6401", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2023-09-20"}, "publish_date": "2023-09-20", "publish_status": "0", "recid": "6401", "relation": {}, "relation_version_is_last": true, "title": ["Improving Collective MPI-IO Using Topology-Aware Stepwise Data Aggregation with I/O Throttling"], "weko_shared_id": -1}