Mitigation technique for performance degradation of virtual machine owing to GPU pass-through in fog computing
As the size of data increases and computation becomes complicated in fog computing environments, the need for highperformance computation is increasing. One of the most popular ways to improve the performance of a virtual machine (VM) is to allocate a graphic processing unit (GPU) to the VM for supp...
Uložené v:
| Vydané v: | Journal of communications and networks Ročník 20; číslo 3; s. 257 - 265 |
|---|---|
| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Seoul
Editorial Department of Journal of Communications and Networks
01.06.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 한국통신학회 |
| Predmet: | |
| ISSN: | 1229-2370, 1976-5541 |
| On-line prístup: | Získať plný text |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
| Abstract | As the size of data increases and computation becomes complicated in fog computing environments, the need for highperformance computation is increasing. One of the most popular ways to improve the performance of a virtual machine (VM) is to allocate a graphic processing unit (GPU) to the VM for supporting general purpose computing on graphic processing unit (GPGPU) operations. The direct pass-through, often used for GPUs in VMs, is popular in the cloud because VMs can use the full functionality of the GPU and experience virtually no performance degradation owing to virtualization. Direct pass-through is very useful for improving the performance of VMs. However, since the GPU usage time is not considered in the VM scheduler that operates based on the central processing unit (CPU) usage time of the VM, the VM performing the GPGPU operation degrades the performance of other VMs. In this paper, we analyze the effect of the VM performing the GPGPU operation (GPGPU-intensive VM) on other VMs through experiments. Then, we propose a method to mitigate the performance degradation of other VMs by dynamically allocating the resource usage time of the VM and preventing the priority preemption of the GPGPU-intensive VM. |
|---|---|
| AbstractList | As the size of data increases and computation becomescomplicated in fog computing environments, the need for highperformancecomputation is increasing. One of the most popularways to improve the performance of a virtual machine (VM) is toallocate a graphic processing unit (GPU) to the VM for supportinggeneral purpose computing on graphic processing unit (GPGPU)operations. The direct pass-through, often used for GPUs in VMs,is popular in the cloud because VMs can use the full functionalityof the GPU and experience virtually no performance degradationowing to virtualization. Direct pass-through is very useful forimproving the performance of VMs. However, since the GPU usagetime is not considered in the VM scheduler that operates basedon the central processing unit (CPU) usage time of the VM, theVM performing the GPGPU operation degrades the performanceof other VMs. In this paper, we analyze the effect of the VM performingthe GPGPU operation (GPGPU-intensive VM) on otherVMs through experiments. Then, we propose a method to mitigatethe performance degradation of other VMs by dynamically allocatingthe resource usage time of the VM and preventing the prioritypreemption of the GPGPU-intensive VM. KCI Citation Count: 6 As the size of data increases and computation becomes complicated in fog computing environments, the need for highperformance computation is increasing. One of the most popular ways to improve the performance of a virtual machine (VM) is to allocate a graphic processing unit (GPU) to the VM for supporting general purpose computing on graphic processing unit (GPGPU) operations. The direct pass-through, often used for GPUs in VMs, is popular in the cloud because VMs can use the full functionality of the GPU and experience virtually no performance degradation owing to virtualization. Direct pass-through is very useful for improving the performance of VMs. However, since the GPU usage time is not considered in the VM scheduler that operates based on the central processing unit (CPU) usage time of the VM, the VM performing the GPGPU operation degrades the performance of other VMs. In this paper, we analyze the effect of the VM performing the GPGPU operation (GPGPU-intensive VM) on other VMs through experiments. Then, we propose a method to mitigate the performance degradation of other VMs by dynamically allocating the resource usage time of the VM and preventing the priority preemption of the GPGPU-intensive VM. |
| Author | Jihun Kang Heonchang Yu |
| Author_xml | – sequence: 1 givenname: Jihun surname: Kang fullname: Kang, Jihun organization: Department of Computer Science and Engineering, Korea University – sequence: 2 givenname: Heonchang surname: Yu fullname: Yu, Heonchang organization: Department of Computer Science and Engineering, Korea University |
| BackLink | https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002366209$$DAccess content in National Research Foundation of Korea (NRF) |
| BookMark | eNp9kb9PGzEcxS1EJSDtzMBiianDBf8-34iiNqWiBVVhthyffTEk9tXnK-K_r5OrGDrEy_PweV99v-9dgNMQgwXgEqM5xqi5-b74OScIyzkqj8oTcI6bWlScM3xa_oQ0FaE1OgMXw_CMEMOU4XMQfvjsO519DDBbswn-92ihiwn2NhXZ6WAsbG2XdDtR0cE_PuVRb-FOm40PFsZXHzqYI1w-PsFeD0OVNymO3Qb6UGZ10MRdP-YCfQQfnN4O9tM_nYGnr19Wi2_V_cPybnF7XxnKca7IWrSkca2sHWtIzQRxhnEtBV0L3RLrmEXcON4KgrSg0mFDnKO05WskW2PoDHye5obk1IvxKmp_0C6ql6Ruf63uFCNI0BLVDFxPbJ9iOX7I6jmOKZT1FCWCU0pYCesIRZCUDUfiQPGJMikOQ7JOGZ8PueWk_VZhpPZlqVKW2pelprKK7-Y_X5_8Tqe3I46ryeGtte-0ZLTen_UXg7-gvg |
| CitedBy_id | crossref_primary_10_1049_wss2_12011 crossref_primary_10_1007_s10586_024_04439_x crossref_primary_10_1002_cpe_6048 crossref_primary_10_1007_s11227_020_03460_2 crossref_primary_10_1109_ACCESS_2019_2920325 crossref_primary_10_1016_j_jss_2021_111010 |
| ContentType | Journal Article |
| Copyright | Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2018 |
| Copyright_xml | – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2018 |
| DBID | 97E RIA RIE AAYXX CITATION 7SC 7SP 8FD JQ2 L7M L~C L~D ACYCR |
| DOI | 10.1109/JCN.2018.000038 |
| DatabaseName | IEEE Xplore (IEEE) IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef Computer and Information Systems Abstracts Electronics & Communications Abstracts Technology Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional Korean Citation Index |
| DatabaseTitle | CrossRef Technology Research Database Computer and Information Systems Abstracts – Academic Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Professional |
| DatabaseTitleList | Technology Research Database Technology Research Database |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISSN | 1976-5541 |
| EndPage | 265 |
| ExternalDocumentID | oai_kci_go_kr_ARTI_4206300 10_1109_JCN_2018_000038 8437206 |
| Genre | orig-research |
| GroupedDBID | -~X 29K 4.4 5GY 6IK 97E 9ZL AAIKC AAJGR AAMNW AAWTH ABAZT ABQJQ ABVLG ACGFO ACGFS AENEX AGQYO ALMA_UNASSIGNED_HOLDINGS D-I EBS EJD IFIPE IPLJI JAVBF KVFHK M43 O9- P2P PQQKQ RIA RIE RNS SJN TWZ AAYXX CITATION 7SC 7SP 8FD JQ2 L7M L~C L~D .UV 0B8 0R~ ACYCR ALLEH OCL RIG |
| ID | FETCH-LOGICAL-c351t-2b6d29fd87f4927462fc45a863b6ad2ef4e05cf5d620a638f1c2ff33d5b08dcc3 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 8 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000442356100004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1229-2370 |
| IngestDate | Tue Nov 21 21:44:41 EST 2023 Mon Oct 27 15:59:01 EDT 2025 Fri Jul 25 05:39:35 EDT 2025 Tue Nov 18 19:37:53 EST 2025 Sat Nov 29 02:24:29 EST 2025 Wed Aug 27 06:01:20 EDT 2025 |
| IsPeerReviewed | false |
| IsScholarly | true |
| Issue | 3 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c351t-2b6d29fd87f4927462fc45a863b6ad2ef4e05cf5d620a638f1c2ff33d5b08dcc3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| PQID | 2088950641 |
| PQPubID | 2040494 |
| PageCount | 9 |
| ParticipantIDs | proquest_journals_3265332441 nrf_kci_oai_kci_go_kr_ARTI_4206300 crossref_citationtrail_10_1109_JCN_2018_000038 proquest_journals_2088950641 ieee_primary_8437206 crossref_primary_10_1109_JCN_2018_000038 |
| PublicationCentury | 2000 |
| PublicationDate | 2018-06-01 |
| PublicationDateYYYYMMDD | 2018-06-01 |
| PublicationDate_xml | – month: 06 year: 2018 text: 2018-06-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationPlace | Seoul |
| PublicationPlace_xml | – name: Seoul |
| PublicationTitle | Journal of communications and networks |
| PublicationTitleAbbrev | JCN |
| PublicationYear | 2018 |
| Publisher | Editorial Department of Journal of Communications and Networks The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 한국통신학회 |
| Publisher_xml | – name: Editorial Department of Journal of Communications and Networks – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE) – name: 한국통신학회 |
| SSID | ssj0041341 ssib053388723 ssib030087698 |
| Score | 2.1654813 |
| Snippet | As the size of data increases and computation becomes complicated in fog computing environments, the need for highperformance computation is increasing. One of... As the size of data increases and computation becomescomplicated in fog computing environments, the need for highperformancecomputation is increasing. One of... |
| SourceID | nrf proquest crossref ieee |
| SourceType | Open Website Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 257 |
| SubjectTerms | Central Processing Unit Central processing units Cloud computing CPUs Degradation Edge computing Fog computing general purpose computing on graphic processing unit (GPGPU) Graphics processing units Performance degradation Performance enhancement Performance evaluation performance isolation Virtual environments Virtual machine monitors Virtualization 전자/정보통신공학 |
| Title | Mitigation technique for performance degradation of virtual machine owing to GPU pass-through in fog computing |
| URI | https://ieeexplore.ieee.org/document/8437206 https://www.proquest.com/docview/2088950641 https://www.proquest.com/docview/3265332441 https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002366209 |
| Volume | 20 |
| WOSCitedRecordID | wos000442356100004&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 | |
| ispartofPNX | Journal of Communications and Networks, 2018, 20(3), , pp.257-265 |
| journalDatabaseRights | – providerCode: PRVIEE databaseName: IEEE Electronic Library (IEL) customDbUrl: eissn: 1976-5541 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0041341 issn: 1229-2370 databaseCode: RIE dateStart: 19990101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV07T-QwEB5xKwqu4HFwYmFB1ukKCgKO83JKhHhKt6IAic5K_EARkKzCAn-fGSe7IMEVVLEUx7HyxfY39sw3AH-TIgrLiJugE9XWiQmK0pVBKI1GOpHYoix9solsPJa3t_nVAuzPY2Gstd75zB5Q0Z_lm0Y_01bZoaRDJtLX_pFlaRerNZt1YxImI-NKiDwQUcZ7GZ-Q54eXx2Py4ZJeq5ACUT6sQD6lCq4rdes-zcZ-iTld-V7nVmG5p5LsqMN-DRZs_Qt-fhAYXIf6X9VpaDQ1m6u1MuSpbPIeMMAMCUZ0uZVY49hL1VJQCXv0fpaWNa_YFps27Ozqhk2QbAd9ch9W1djWHdM-MwRW2oCb05Pr4_Ogz7AQ6CgJp4EoUyNyZ2Tm4hzt01Q4HSeFTKMyLYywLrY80S4xqeAFjlQXauFcFJmk5Aimjn7DoG5quwlM6JwLkxqbxi7GgkQmxG2mkVNJtJLCIRzMvrrSvfw4ZcF4UN4M4blCmBTBpDqYhrA3f2DSKW_8v-o64TGv1kMxhD8Iq7rXlSIRbbreNeq-VWgqXKhYeLmxIYxmqKt--D5h21LmJOUXfnkbKS-yZCRG4dbXb96GJepe51I2gsG0fbY7sKhfptVTu-t_3DfpKOsS |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LT9wwEB4higQ9FCigLqVgVT1wIOA4cdY5IlTerDiAxM1K_EARbbIKC_z9zjjZLVLh0FMsxXGsfH58E898A_BDFklcJtxGnai2kTYqSl9GsbIG6YR0RVmGZBPD0Ujd3eXXc7A3i4VxzgXnM7dPxXCWbxvzRL_KDhQdMpG-9geZpoJ30VrTdTclaTIyr4TII5EMeS_kE_P84PxoRF5cKqgVUijKqz0oJFXBnaVu_T_rcdhkjpf_r3sr8Kknk-ywQ38V5lz9GT6-khhcg_qq6lQ0mprN9FoZMlU2_hsywCxJRnTZlVjj2XPVUlgJ-x08LR1rXrAtNmnYyfUtGyPdjvr0Pqyqsa17ZkJuCKy0DrfHP2-OTqM-x0JkEhlPIlFmVuTeqqFPc7RQM-FNKguVJWVWWOF86rg0XtpM8ALnqo-N8D5JrCw5wmmSDZivm9p9ASZMzoXNrMtSn2JBIRfibmiQVSm0k-IB7E-_uja9ADnlwfilgyHCc40waYJJdzANYHf2wLjT3ni_6hrhMavWQzGA7wirfjCVJhltut43-qHVaCycaRxCJDg2gK0p6rqfwI_YtlI5ifnFb95G0os8GalRvPn2m3dg8fTm6lJfno0uvsISdbVzMNuC-Un75L7BgnmeVI_tdhjEfwBG2O5Z |
| 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%3Ajournal&rft.genre=article&rft.atitle=Mitigation+technique+for+performance+degradation+of+virtual+machine+owing+to+GPU+pass-through+in+fog+computing&rft.jtitle=Journal+of+communications+and+networks&rft.au=Jihun+Kang&rft.au=Heonchang+Yu&rft.date=2018-06-01&rft.pub=Editorial+Department+of+Journal+of+Communications+and+Networks&rft.issn=1229-2370&rft.volume=20&rft.issue=3&rft.spage=257&rft.epage=265&rft_id=info:doi/10.1109%2FJCN.2018.000038&rft.externalDocID=8437206 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1229-2370&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1229-2370&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1229-2370&client=summon |