TY - GEN
T1 - Persistent Memory Object Storage and Indexing for Scientific Computing
AU - Khan, Awais
AU - Sim, Hyogi
AU - Vazhkudai, Sudharshan S.
AU - Ma, Jinsuk
AU - Oh, Myeong Hoon
AU - Kim, Youngjae
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/11
Y1 - 2020/11
N2 - This paper presents Mosiqs, a persistent memory object storage framework with metadata indexing and querying for scientific computing. We design Mosiqs based on the key idea that memory objects on shared PM pool can live beyond the application lifetime and can become the sharing currency for applications and scientists. Mosiqs provides an aggregate memory pool atop an array of persistent memory devices to store and access memory objects. Mosiqs uses a lightweight persistent memory key-value store to manage the metadata of memory objects such as persistent pointer mappings, which enables memory object sharing for effective scientific collaborations. Mosiqs is implemented atop PMDK. We evaluate the proposed approach on many-core server with an array of real PM devices. The preliminary evaluation confirms a 100% improvement for write and 30% in read performance against a PM-aware file system approach.
AB - This paper presents Mosiqs, a persistent memory object storage framework with metadata indexing and querying for scientific computing. We design Mosiqs based on the key idea that memory objects on shared PM pool can live beyond the application lifetime and can become the sharing currency for applications and scientists. Mosiqs provides an aggregate memory pool atop an array of persistent memory devices to store and access memory objects. Mosiqs uses a lightweight persistent memory key-value store to manage the metadata of memory objects such as persistent pointer mappings, which enables memory object sharing for effective scientific collaborations. Mosiqs is implemented atop PMDK. We evaluate the proposed approach on many-core server with an array of real PM devices. The preliminary evaluation confirms a 100% improvement for write and 30% in read performance against a PM-aware file system approach.
KW - Memory-centric Computing
KW - Persistent Memory Storage
KW - Scientific Metadata Indexing and Search
UR - http://www.scopus.com/inward/record.url?scp=85099530904&partnerID=8YFLogxK
U2 - 10.1109/MCHPC51950.2020.00006
DO - 10.1109/MCHPC51950.2020.00006
M3 - Conference contribution
AN - SCOPUS:85099530904
T3 - Proceedings of MCHPC 2020: Workshop on Memory Centric High Performance Computing, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis
SP - 1
EP - 9
BT - Proceedings of MCHPC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE/ACM Workshop on Memory Centric High Performance Computing, MCHPC 2020
Y2 - 11 November 2020
ER -