Daniel Araújo De Medeiros, S. Markidis, Ivy Bo Peng
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In particular, we provide a prototype library called LibCOS that transparently enables MPI applications running on HPC systems to access object storage on remote cloud systems. We evaluated LibCOS on a Ceph object storage system and a traditional HPC system. In addition, we conducted performance characterization of core S3 operations that enable individual and collective MPI I/O. Our evaluation in HACC, IOR, and BigSort shows that enabling diverse data stores on HPC and Cloud storage is feasible and can be transparently achieved through the widely adopted MPI I/O. Also, we show that a native object storage system like Ceph could improve the scalability of I/O operations in parallel applications.","PeriodicalId":314778,"journal":{"name":"Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region","volume":"47 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"LibCOS: Enabling Converged HPC and Cloud Data Stores with MPI\",\"authors\":\"Daniel Araújo De Medeiros, S. Markidis, Ivy Bo Peng\",\"doi\":\"10.1145/3578178.3578236\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, federated HPC and cloud resources are becoming increasingly strategic for providing diversified and geographically available computing resources. However, accessing data stores across HPC and cloud storage systems is challenging. Many cloud providers use object storage systems to support their clients in storing and retrieving data over the internet. One popular method is REST APIs atop the HTTP protocol, with Amazon’s S3 APIs being supported by most vendors. In contrast, HPC systems are contained within their networks and tend to use parallel file systems with POSIX-like interfaces. This work addresses the challenge of diverse data stores on HPC and cloud systems by providing native object storage support through the unified MPI I/O interface in HPC applications. In particular, we provide a prototype library called LibCOS that transparently enables MPI applications running on HPC systems to access object storage on remote cloud systems. We evaluated LibCOS on a Ceph object storage system and a traditional HPC system. In addition, we conducted performance characterization of core S3 operations that enable individual and collective MPI I/O. 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LibCOS: Enabling Converged HPC and Cloud Data Stores with MPI
Recently, federated HPC and cloud resources are becoming increasingly strategic for providing diversified and geographically available computing resources. However, accessing data stores across HPC and cloud storage systems is challenging. Many cloud providers use object storage systems to support their clients in storing and retrieving data over the internet. One popular method is REST APIs atop the HTTP protocol, with Amazon’s S3 APIs being supported by most vendors. In contrast, HPC systems are contained within their networks and tend to use parallel file systems with POSIX-like interfaces. This work addresses the challenge of diverse data stores on HPC and cloud systems by providing native object storage support through the unified MPI I/O interface in HPC applications. In particular, we provide a prototype library called LibCOS that transparently enables MPI applications running on HPC systems to access object storage on remote cloud systems. We evaluated LibCOS on a Ceph object storage system and a traditional HPC system. In addition, we conducted performance characterization of core S3 operations that enable individual and collective MPI I/O. Our evaluation in HACC, IOR, and BigSort shows that enabling diverse data stores on HPC and Cloud storage is feasible and can be transparently achieved through the widely adopted MPI I/O. Also, we show that a native object storage system like Ceph could improve the scalability of I/O operations in parallel applications.