{"title":"使用容器迁移实现HPC工作负载弹性","authors":"Mohamad Sindi, John R. Williams","doi":"10.1109/HPEC.2019.8916436","DOIUrl":null,"url":null,"abstract":"We share experiences in implementing a containerbased HPC environment that could help sustain running HPC workloads on clusters. By running workloads inside containers, we are able to migrate them from cluster nodes anticipating hardware problems, to healthy nodes while the workloads are running. Migration is done using the CRIU tool with no application modification. No major interruption or overhead is introduced to the workload. Various real HPC applications are tested. Tests are done with different hardware node specs, network interconnects, and MPI implementations. We also benchmark the applications on containers and compare performance to native. Results demonstrate successful migration of HPC workloads inside containers with minimal interruption, while maintaining the integrity of the results produced. We provide several YouTube videos demonstrating the migration tests. Benchmarks also show that application performance on containers is close to native. We discuss some of the challenges faced during implementation and solutions adopted. To the best of our knowledge, we believe this work is the first to demonstrate successful migration of real MPI-based HPC workloads using CRIU and containers.","PeriodicalId":184253,"journal":{"name":"2019 IEEE High Performance Extreme Computing Conference (HPEC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Using Container Migration for HPC Workloads Resilience\",\"authors\":\"Mohamad Sindi, John R. Williams\",\"doi\":\"10.1109/HPEC.2019.8916436\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We share experiences in implementing a containerbased HPC environment that could help sustain running HPC workloads on clusters. By running workloads inside containers, we are able to migrate them from cluster nodes anticipating hardware problems, to healthy nodes while the workloads are running. Migration is done using the CRIU tool with no application modification. No major interruption or overhead is introduced to the workload. Various real HPC applications are tested. Tests are done with different hardware node specs, network interconnects, and MPI implementations. We also benchmark the applications on containers and compare performance to native. Results demonstrate successful migration of HPC workloads inside containers with minimal interruption, while maintaining the integrity of the results produced. We provide several YouTube videos demonstrating the migration tests. Benchmarks also show that application performance on containers is close to native. We discuss some of the challenges faced during implementation and solutions adopted. To the best of our knowledge, we believe this work is the first to demonstrate successful migration of real MPI-based HPC workloads using CRIU and containers.\",\"PeriodicalId\":184253,\"journal\":{\"name\":\"2019 IEEE High Performance Extreme Computing Conference (HPEC)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE High Performance Extreme Computing Conference (HPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPEC.2019.8916436\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE High Performance Extreme Computing Conference (HPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPEC.2019.8916436","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using Container Migration for HPC Workloads Resilience
We share experiences in implementing a containerbased HPC environment that could help sustain running HPC workloads on clusters. By running workloads inside containers, we are able to migrate them from cluster nodes anticipating hardware problems, to healthy nodes while the workloads are running. Migration is done using the CRIU tool with no application modification. No major interruption or overhead is introduced to the workload. Various real HPC applications are tested. Tests are done with different hardware node specs, network interconnects, and MPI implementations. We also benchmark the applications on containers and compare performance to native. Results demonstrate successful migration of HPC workloads inside containers with minimal interruption, while maintaining the integrity of the results produced. We provide several YouTube videos demonstrating the migration tests. Benchmarks also show that application performance on containers is close to native. We discuss some of the challenges faced during implementation and solutions adopted. To the best of our knowledge, we believe this work is the first to demonstrate successful migration of real MPI-based HPC workloads using CRIU and containers.