A Sparsity-Aware Distributed-Memory Algorithm for Sparse-Sparse Matrix Multiplication
Multiplying two sparse matrices (SpGEMM) is a common computational primitive used in many areas including graph algorithms, bioinformatics, algebraic multigrid solvers, and randomized sketching. Distributed-memory parallel algorithms for SpGEMM have mainly focused on sparsity-oblivious approaches th...
Uložené v:
| Vydané v: | SC24: International Conference for High Performance Computing, Networking, Storage and Analysis s. 1 - 14 |
|---|---|
| Hlavní autori: | , |
| Médium: | Konferenčný príspevok.. |
| Jazyk: | English |
| Vydavateľské údaje: |
IEEE
17.11.2024
|
| Predmet: | |
| On-line prístup: | Získať plný text |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
| Abstract | Multiplying two sparse matrices (SpGEMM) is a common computational primitive used in many areas including graph algorithms, bioinformatics, algebraic multigrid solvers, and randomized sketching. Distributed-memory parallel algorithms for SpGEMM have mainly focused on sparsity-oblivious approaches that use 2D and 3D partitioning. Sparsity-aware 1D algorithms can theoretically reduce communication by not fetching nonzeros of the sparse matrices that do not participate in the multiplication. Here, we present a distributed-memory 1D SpGEMM algorithm and implementation. It uses MPI RDMA operations to mitigate the cost of packing/unpacking submatrices for communication, and it uses a block fetching strategy to avoid excessive finegrained messaging. Our results show that our 1D implementation outperforms state-of-the-art 2D and 3D implementations within CombBLAS for many configurations, inputs, and use cases, while remaining conceptually simpler. |
|---|---|
| AbstractList | Multiplying two sparse matrices (SpGEMM) is a common computational primitive used in many areas including graph algorithms, bioinformatics, algebraic multigrid solvers, and randomized sketching. Distributed-memory parallel algorithms for SpGEMM have mainly focused on sparsity-oblivious approaches that use 2D and 3D partitioning. Sparsity-aware 1D algorithms can theoretically reduce communication by not fetching nonzeros of the sparse matrices that do not participate in the multiplication. Here, we present a distributed-memory 1D SpGEMM algorithm and implementation. It uses MPI RDMA operations to mitigate the cost of packing/unpacking submatrices for communication, and it uses a block fetching strategy to avoid excessive finegrained messaging. Our results show that our 1D implementation outperforms state-of-the-art 2D and 3D implementations within CombBLAS for many configurations, inputs, and use cases, while remaining conceptually simpler. |
| Author | Buluc, Aydin Hong, Yuxi |
| Author_xml | – sequence: 1 givenname: Yuxi surname: Hong fullname: Hong, Yuxi email: abuluc@lbl.gov organization: Applied Math & Computational Research Division Lawrence Berkeley National Laboratory,Berkeley,USA – sequence: 2 givenname: Aydin surname: Buluc fullname: Buluc, Aydin organization: Applied Math & Computational Research Division Lawrence Berkeley National Laboratory,Berkeley,USA |
| BookMark | eNotjM1KxDAURiMoqGNfQFzkBTreJE2TLMv4C1NcjLMekvRWA522pBm0b29hXB3Ox-G7JZf90CMh9wzWjIF53G0KVkC55sCLNQBIcUEyo4wWEoTkhqlrkk1TcCCVEkqAuCH7iu5GG6eQ5rz6sRHpU5hSDO6UsMlrPA5xplX3NcSQvo-0HeK5x_wMWtul_qX1qUth7IK3KQz9HblqbTdh9s8V2b88f27e8u3H6_um2uaWyyLlBi0oDVZ78FBY3ygnWKs4oHGIpZfg9aItLzVfBgBtvDHO6ZK5BnwhVuTh_BsQ8TDGcLRxPjBQRjApxR-M6VLv |
| CODEN | IEEPAD |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/SC41406.2024.00053 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Xplore POP ALL IEEE Xplore All Conference Proceedings IEEE/IET Electronic Library (IEL) IEEE Proceedings Order Plans (POP All) 1998-Present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Xplore url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| EISBN | 9798350352917 |
| EndPage | 14 |
| ExternalDocumentID | 10793155 |
| Genre | orig-research |
| GrantInformation_xml | – fundername: Office of Science funderid: 10.13039/100006132 |
| GroupedDBID | 6IE 6IL ACM ALMA_UNASSIGNED_HOLDINGS APO CBEJK LHSKQ RIE RIL |
| ID | FETCH-LOGICAL-a254t-9ea0780a8c0c04acd7b31f720e9bee6c50c8f72f2682bee0089c99bb861bd0c43 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 0 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001414891300034&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| IngestDate | Wed Jan 22 08:32:25 EST 2025 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-a254t-9ea0780a8c0c04acd7b31f720e9bee6c50c8f72f2682bee0089c99bb861bd0c43 |
| PageCount | 14 |
| ParticipantIDs | ieee_primary_10793155 |
| PublicationCentury | 2000 |
| PublicationDate | 2024-Nov.-17 |
| PublicationDateYYYYMMDD | 2024-11-17 |
| PublicationDate_xml | – month: 11 year: 2024 text: 2024-Nov.-17 day: 17 |
| PublicationDecade | 2020 |
| PublicationTitle | SC24: International Conference for High Performance Computing, Networking, Storage and Analysis |
| PublicationTitleAbbrev | SC |
| PublicationYear | 2024 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| SSID | ssib057737303 |
| Score | 1.9048718 |
| Snippet | Multiplying two sparse matrices (SpGEMM) is a common computational primitive used in many areas including graph algorithms, bioinformatics, algebraic multigrid... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 1 |
| SubjectTerms | 1D algorithm 1D SpGEMM algorithm Electric breakdown High performance computing Load management Matrices numerical linear algebra Parallel algorithms parallel computing Partitioning algorithms RDMA Software Software algorithms Sparse matrices sparse matrix-matrix multiplication sparsity-aware 1D SpGEMM algorithm SpGEMM Three-dimensional displays |
| Title | A Sparsity-Aware Distributed-Memory Algorithm for Sparse-Sparse Matrix Multiplication |
| URI | https://ieeexplore.ieee.org/document/10793155 |
| WOSCitedRecordID | wos001414891300034&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEA62ePCkYsU3OXiNZjfZTXIs1eKlpVALvZU8ZlXQttTWx793km3Viwf3sg8WFiazfJnk-74h5FLnztiyAlbl2jMpQDMrIbDMcqGtVqGQLjWbUP2-Ho_NYC1WT1oYAEjkM7iKl2kvP8z8Ki6V4R-O2YQA2CANpVQt1tokT6GUwGwVG2EMN9fDjsTyIfIQ8miRzWMD5F8tVBKCdHf_-e090vrR4tHBN8rsky2YHpBRmw7nNvEpWPvdLoDeRAPc2LsKI9CL7NlP2n5-mGHp__hCcWJavw-sPtFedOb_oL2aTrhet2uRUff2vnPH1g0SmMW6bskMWER4brXnnkvrg3Iiq1TOwTiA0hfca7yt8hKHBADh3nhjnNNl5gL3UhyS5nQ2hSNCpQl4iNJBFmSeB1dkvgwBJxfRrbgIx6QVYzKZ1x4Yk004Tv54fkp2Ytijai9TZ6S5XKzgnGz7t-XT6-IijdwXHTqcEA |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LTwIxEG4UTfSkRoxve_Ba7Xa7u-2RoAQjS0iAhBvpY1ATBYLg49873QX14sG9dLfZZJOZ2Uyn_b75CLlUwmqTjoCNhHJMxqCYkeBZZHisjMp8Im0hNpG122ow0J0lWb3gwgBAAT6Dq3BbnOX7iVuErTL8wzGaMAGuk41EShGVdK1V-CRZFmO8xitqDNfX3brEAiIgEURoks2DBPIvEZUihzR2_vn1XVL9YePRznee2SNrMN4n_RrtTk2BqGC1dzMDehNa4Ab1KrRBHvCzn7T2_DDB4v_xheLStHwfWDnQPPTm_6B5CShc7txVSb9x26s32VIigRms7OZMg8Ecz41y3HFpnM9sHI0ywUFbgNQl3Cl8HIkUnQKACV87ra1VaWQ9dzI-IJXxZAyHhErt8YpTC5GXQnibRC71HpcXoV9x4o9INdhkOC27YAxX5jj-Y_6CbDV7eWvYumvfn5Dt4ILA4YuyU1KZzxZwRjbd2_zpdXZeePELajafVw |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=SC24%3A+International+Conference+for+High+Performance+Computing%2C+Networking%2C+Storage+and+Analysis&rft.atitle=A+Sparsity-Aware+Distributed-Memory+Algorithm+for+Sparse-Sparse+Matrix+Multiplication&rft.au=Hong%2C+Yuxi&rft.au=Buluc%2C+Aydin&rft.date=2024-11-17&rft.pub=IEEE&rft.spage=1&rft.epage=14&rft_id=info:doi/10.1109%2FSC41406.2024.00053&rft.externalDocID=10793155 |