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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸°úÇÐȸ ³í¹®Áö > Á¤º¸°úÇÐȸ ÄÄÇ»ÆÃÀÇ ½ÇÁ¦ ³í¹®Áö (KIISE Transactions on Computing Practices)

Á¤º¸°úÇÐȸ ÄÄÇ»ÆÃÀÇ ½ÇÁ¦ ³í¹®Áö (KIISE Transactions on Computing Practices)

Current Result Document : 471 / 472

ÇѱÛÁ¦¸ñ(Korean Title) Ŭ¶ó¿ìµå-³×ÀÌƼºê ±â¹Ý SmartX AI Ŭ·¯½ºÅÍÀÇ ¸ÖƼ Ŭ·¯½ºÅ͸µ ¹× ¸ÖƼ Å׳ͽà ±â´É °³¼±
¿µ¹®Á¦¸ñ(English Title) Improving Multi-clustering and Multi-tenancy of the Cloud-native SmartX AI Cluster
ÀúÀÚ(Author) À±±Ý¼º   ÇÑÁ¤¼ö   È«À¯Áø   ±èÁ¾¿ø   GeumSeong Yoon   Jungsu Han   Yujin Hong   JongWon Kim  
¿ø¹®¼ö·Ïó(Citation) VOL 39 NO. 07 PP. 0295 ~ 0308 (2021. 07)
Çѱ۳»¿ë
(Korean Abstract)
Ãֱ٠Ŭ¶ó¿ìµå ¼­ºñ½º¿¡ ´ëÇÑ ¼ö¿ä Áõ°¡¿¡ µû¶ó °æ·®È­µÈ °¡»ó ȯ°æÀ» ±â¹ÝÀ¸·Î ÄÄÇ»Æà ȯ°æÀ» ±¸¼ºÇÏ´Â ÄÁÅ×ÀÌ³Ê ±â¼úÀÇ »ç¿ëÀÌ Å©°Ô Áõ°¡ÇÏ¿´´Ù. ÀÌ¿¡ µû¶ó È®À强 ¹× °¡¿ë¼º Ư¡À» °®´Â Ŭ¶ó¿ìµå-³×ÀÌƼºê(Cloud-native) ÄÄÇ»Æà ±â¹Ý ±â¼úÀÎ Äí¹ö³×Ƽ½º(Kubernetes, K8S)¸¦ äÅÃÇÏ´Â »ç·Ê°¡ ¸¹¾ÆÁ³´Ù. ¶ÇÇÑ, ÀÌ¿Í ¿¬°èµÇ¾î ´Ù¾çÇÑ ºÐ¾ß¿¡¼­ È°¿ëµÇ°í ÀÖ´Â AI ±â¼ú Áö¿ø µµ±¸µéÀÌ Á¡Â÷ ´Ã¾î³ª°Ô µÇ¾úÀ¸¸ç À¯¿¬ÇÑ ¹èÆ÷ ¹× ¿î¿ëÀÌ °¡´ÉÇÏ°Ô µÇ¾ú´Ù. ±×·¯³ª »ó±â µµ±¸µéÀ» È¿À²ÀûÀ¸·Î »ç¿ëÇϱâ À§ÇÏ¿© ƯÁ¤ ¿öÅ©·Îµå¸¦ ´ë»óÀ¸·Î ƯȭµÈ ÀÚ¿ø ±¸¼º¿¡ ´ëÇÑ Çʿ伺ÀÌ ´ëµÎµÇ¾ú´Ù. ÀÌ¿¡ ¸ÖƼ Ŭ·¯½ºÅÍÀÇ °³³äÀÌ Á¦¾ÈµÇ¾úÀ¸³ª ¸ÖƼ Ŭ·¯½ºÅÍ(Multi-cluster)ÀÇ ±¸Ãà°ú ÇÔ²² ÇØ´ç ±¸Á¶¸¦ °ü¸®ÇÏ´Â ±¸¼º ¿ä¼Ò ¹× °³³äÀÌ ÇÊ¿äÇÏ´Ù. ÀÌ¿¡ ´ëÀÀÇÏ¿© º» ³í¹®¿¡¼­´Â K8S ±â¹ÝÀ¸·Î ±¸ÃàµÈ SmartX AI ClusterÀÇ È®Àå°ú ´õºÒ¾î Tenants PortalÀ» ¼Ò°³ÇÑ´Ù. È®ÀåµÈ SmartX AI Cluster´Â ½Ì±Û K8S Ŭ·¯½ºÅÍ·Î ¿î¿µÇß´ø ±âÁ¸ÀÇ ¹æ½Ä°ú´Â ´Ù¸£°Ô ´Ù¸¥ Á¾·ùÀÇ ÀÚ¿øÀ» Æ÷ÇÔÇÏ´Â ´ÜÀÏ K8S Ŭ·¯½ºÅ͵éÀ» °áÇÕÇÑ ¸ÖƼ K8S Ŭ·¯½ºÅÍ È¯°æÀ» Á¦°øÇÑ´Ù. ¶ÇÇÑ, Tenants PortalÀº º°µµÀÇ K8S ȯ°æÀ» ±¸ÃàÇÏÁö ¾Ê¾Æµµ µ¿½Ã¿¡ ¿©·¯ »ç¿ëÀÚ°¡ »ó±â ȯ°æÀ» ÀÌ¿ëÇÒ ¼ö ÀÖµµ·Ï Áö¿øÇÏ´Â °³Ã¼(Entity)ÀÌ´Ù. ÃÖÁ¾ÀûÀ¸·Î Á¦¾ÈÇÑ È¯°æ¿¡¼­ º´·Ä ¹× ºÐ»ê ó¸®, Ãß·Ð ¼­ºñ½º »ç·Ê¸¦ ÅëÇØ ¸Ó½Å·¯´×(Machine Learning, ML) ¿öÅ©·Îµå °ËÁõÀ» ¼öÇàÇÔ°ú µ¿½Ã¿¡ Àû¿ëµÈ °³³äÀÇ °³¼± ¹× °ü·Ã ¿¬±¸¸¦ ³íÀÇÇÑ´Ù.
¿µ¹®³»¿ë
(English Abstract)
The recent increase in demand for cloud services has led to a significant increase in the use of container technologies that create a computing environment based on lightweight virtual environment. This has led to the adoption of Kubernetes (K8S), a cloud-native computing-based technology that features scalability and availability. In addition, the number of artificial intelligence(AI) technology support tools that are being utilized in various areas has gradually increased and flexible distribution and operation has become possible. However, in order to efficiently use the above-mentioned tools, there is a need for a resource configuration specialized for a specific workload. In response, the concept of a multi-cluster has been proposed, but it requires a component and a concept that manages the structure along with the construction of a multi-cluster. This paper introduces Tenants Portal along with extension of the SmartX AI Cluster built on K8S. The extended SmartX AI Cluster provides a multi-K8S cluster environment that combines single K8S clusters with different types of resources, unlike the previous method that operated as a single K8S cluster. In addition, Tenants Portal is an entity that supports multiple users to use the environment at the same time without building a separate K8S environment. Finally, in the proposed environment, machine learning (ML) workload verification is performed through parallel and distributed processing and inference service cases, and related studies are discussed.
Å°¿öµå(Keyword) Ŭ¶ó¿ìµå-³×ÀÌƼºê ÄÄÇ»Æà  ¸Ó½Å ·¯´×   ÄÁÅ×ÀÌ³Ê ±â¹Ý Ŭ·¯½ºÅÍ   ¸ÖƼ Ŭ·¯½ºÅÍ   ¸ÖƼ Å׳ͽà  cloud-native computing   machine learning   container-based clusters   multi-cluster   multitenancy  
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