TY - GEN
T1 - Hybrid Storage System to Achieve Efficient Use of Fast Memory Area
AU - Oe, Kazuichi
AU - Nanri, Takeshi
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - Hybrid storage techniques are useful methods to improve the cost performance for input-output (IO) intensive workloads. These techniques choose areas of concentrated IO accesses and migrate them to an upper tier to extract as much performance as possible through greater use of upper tier areas. Automated tiered storage with fast memory and slow flash storage (ATSMF) is a hybrid storage system situated between non-volatile memories (NVMs) and solid-state drives (SSDs). ATSMF aims to reduce the average response time for IO accesses by migrating areas of concentrated IO access from an SSD to an NVM. When a concentrated IO access finishes, the system migrates these areas from the NVM back to the SSD. Unfortunately, the published ATSMF implementation temporarily consumes much NVM capacity upon migrating concentrated IO access areas to NVM, because its algorithm executes NVM migration with high priority. As a result, it often delays evicting areas in which IO concentrations have ended to the SSD. Therefore, to reduce the consumption of NVM while maintaining the average response time, we developed new techniques for making ATSMF more practical. The first is a queue handling technique based on the number of IO accesses for NVM migration and eviction. The second is an eviction method that selects only write-accessed partial regions in finished areas. The third is a technique for variable eviction timing to balance the NVM consumption and average response time. Experimental results indicate that the average response times of the proposed ATSMF are almost the same as those of the published ATSMF, while the NVM consumption is drastically lower.
AB - Hybrid storage techniques are useful methods to improve the cost performance for input-output (IO) intensive workloads. These techniques choose areas of concentrated IO accesses and migrate them to an upper tier to extract as much performance as possible through greater use of upper tier areas. Automated tiered storage with fast memory and slow flash storage (ATSMF) is a hybrid storage system situated between non-volatile memories (NVMs) and solid-state drives (SSDs). ATSMF aims to reduce the average response time for IO accesses by migrating areas of concentrated IO access from an SSD to an NVM. When a concentrated IO access finishes, the system migrates these areas from the NVM back to the SSD. Unfortunately, the published ATSMF implementation temporarily consumes much NVM capacity upon migrating concentrated IO access areas to NVM, because its algorithm executes NVM migration with high priority. As a result, it often delays evicting areas in which IO concentrations have ended to the SSD. Therefore, to reduce the consumption of NVM while maintaining the average response time, we developed new techniques for making ATSMF more practical. The first is a queue handling technique based on the number of IO accesses for NVM migration and eviction. The second is an eviction method that selects only write-accessed partial regions in finished areas. The third is a technique for variable eviction timing to balance the NVM consumption and average response time. Experimental results indicate that the average response times of the proposed ATSMF are almost the same as those of the published ATSMF, while the NVM consumption is drastically lower.
UR - http://www.scopus.com/inward/record.url?scp=85078938397&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85078938397&partnerID=8YFLogxK
U2 - 10.1109/CANDAR.2019.00016
DO - 10.1109/CANDAR.2019.00016
M3 - Conference contribution
AN - SCOPUS:85078938397
T3 - Proceedings - 2019 7th International Symposium on Computing and Networking, CANDAR 2019
SP - 63
EP - 72
BT - Proceedings - 2019 7th International Symposium on Computing and Networking, CANDAR 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Symposium on Computing and Networking, CANDAR 2019
Y2 - 26 November 2019 through 29 November 2019
ER -