Memory Controller Design Under Cloud Workloads
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This work studies the behavior of state-of-the-art memory controller designs when executing scale-out workloads. It considers memory scheduling techniques, memory page management policies, the number of memory channels, and the address mapping scheme used. Experimental measurements demonstrate: 1) Several recently proposed memory scheduling policies are not a good match for these scale-out workloads. 2) The relatively simple First-Ready-First-Come-First-Served (FR-FCFS) policy performs consistently better, and 3) for most of the studied workloads, the even simpler First-Come-First-Served scheduling policy is within 1% of FR-FCFS. 4) Increasing the number of memory channels offers negligible performance benefits, e.g., performance improves by 1.7% on average for 4-channels vs. 1-channel. 5) 77%-90% of DRAM rows activations are accessed only once before closure. These observation can guide future development and optimization of memory controllers for scale-out workloads.
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