TY - GEN
T1 - GreenDIMM
T2 - 54th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2021
AU - Lee, Seunghak
AU - Kang, Ki Dong
AU - Lee, Hwanjun
AU - Park, Hyungwon
AU - Son, Younghoon
AU - Kim, Nam Sung
AU - Kim, Daehoon
N1 - Funding Information:
This work was partly supported by Samsung Electronics, National Research Foundation of Korea (NRF) grants funded by the Korean government (MSIT) (NRF-2020R1C1C1013315, NRF-2018R1A5A1060 031), Samsung Research Funding Incubation Center of Samsung Electronics under Project Number SRFC-IT1902-03, Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No.2014-3-00065, Resilient Cyber-Physical Systems Research), and National Science Foundation grant (CNS-1705047). Daehoon Kim is the corresponding author.
Publisher Copyright:
© 2021 Association for Computing Machinery.
PY - 2021/10/18
Y1 - 2021/10/18
N2 - Power and energy consumed byDRAMcomprising main memory of data-center servers have increased substantially as the capacity and bandwidth of memory increase. Especially, the fraction of DRAM background power in DRAM total power is already high, and it will continue to increase with the decelerating DRAM technology scaling as we will have to plug more DRAM modules in servers or stack more DRAM dies in a DRAM package to provide necessary DRAM capacity in the future. To reduce the background power, we may exploit low average utilization of the DRAM capacity in data-center servers (i.e., 40 C60%) for DRAM power management. Nonetheless, the current DRAM power management supports lowpower states only at the rank granularity, which becomes ineffective with memory interleaving techniques devised to disperse memory requests across ranks. That is, ranks need to be frequently woken up from low-power states with aggressive power management, which can significantly degrade system performance, or they do not get a chance to enter low-power states with conservative power management. To tackle such limitations of the current DRAM power management, we propose GreenDIMM, OS-assisted DRAM power management. Specifically, GreenDIMM first takes a memory block in physical address space mapped to a group of DRAM sub-arrays across every channel, rank, and bank as a unit of DRAM power management. This facilitates fine-grained DRAM power management while keeping the benefit of memory interleaving techniques. Second, GreenDIMM exploits memory on-/off-lining operations of the modern OS to dynamically remove/add memory blocks from/to the physical address space, depending on the utilization of memory capacity at run-time. Third, GreenDIMM implements a deep powerdown state at the sub-array granularity to reduce the background power of the off-lined memory blocks. As the off-lined memory blocks are removed from the physical address space, the sub-arrays will not receive any memory request and stay in the power-down state until the memory blocks are explicitly on-lined by the OS. Our evaluation with a commercial server running diverse workloads shows that GreenDIMM can reduce DRAM and system power by 36% and 20%, respectively, with ~1% performance degradation.
AB - Power and energy consumed byDRAMcomprising main memory of data-center servers have increased substantially as the capacity and bandwidth of memory increase. Especially, the fraction of DRAM background power in DRAM total power is already high, and it will continue to increase with the decelerating DRAM technology scaling as we will have to plug more DRAM modules in servers or stack more DRAM dies in a DRAM package to provide necessary DRAM capacity in the future. To reduce the background power, we may exploit low average utilization of the DRAM capacity in data-center servers (i.e., 40 C60%) for DRAM power management. Nonetheless, the current DRAM power management supports lowpower states only at the rank granularity, which becomes ineffective with memory interleaving techniques devised to disperse memory requests across ranks. That is, ranks need to be frequently woken up from low-power states with aggressive power management, which can significantly degrade system performance, or they do not get a chance to enter low-power states with conservative power management. To tackle such limitations of the current DRAM power management, we propose GreenDIMM, OS-assisted DRAM power management. Specifically, GreenDIMM first takes a memory block in physical address space mapped to a group of DRAM sub-arrays across every channel, rank, and bank as a unit of DRAM power management. This facilitates fine-grained DRAM power management while keeping the benefit of memory interleaving techniques. Second, GreenDIMM exploits memory on-/off-lining operations of the modern OS to dynamically remove/add memory blocks from/to the physical address space, depending on the utilization of memory capacity at run-time. Third, GreenDIMM implements a deep powerdown state at the sub-array granularity to reduce the background power of the off-lined memory blocks. As the off-lined memory blocks are removed from the physical address space, the sub-arrays will not receive any memory request and stay in the power-down state until the memory blocks are explicitly on-lined by the OS. Our evaluation with a commercial server running diverse workloads shows that GreenDIMM can reduce DRAM and system power by 36% and 20%, respectively, with ~1% performance degradation.
KW - DRAM power management
KW - Memory off-lining
UR - http://www.scopus.com/inward/record.url?scp=85118853339&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85118853339&partnerID=8YFLogxK
U2 - 10.1145/3466752.3480089
DO - 10.1145/3466752.3480089
M3 - Conference contribution
AN - SCOPUS:85118853339
T3 - Proceedings of the Annual International Symposium on Microarchitecture, MICRO
SP - 131
EP - 142
BT - MICRO 2021 - 54th Annual IEEE/ACM International Symposium on Microarchitecture, Proceedings
PB - IEEE Computer Society
Y2 - 18 October 2021 through 22 October 2021
ER -