MTM: Rethinking Memory Profiling and Migration for Multi-Tiered Large Memory
Jie Ren, Dong Xu, Junhee Ryu, Kwangsik Shin, Daewoo Kim, Dong Li
Abstract
Multi-terabyte large memory systems are often characterized by more than two memory tiers with different latency and bandwidth. Multi-tiered large memory systems call for rethinking of memory profiling and migration because of the unique problems unseen in the traditional memory systems with smaller capacity and fewer tiers. We develop MTM, an application-transparent Multi-Tiered Memory management framework, based on three principles: (1) connecting the control of profiling overhead with the profiling mechanism for high-quality profiling; (2) building a universal page migration policy on the complex multi-tiered memory for high performance; and (3) introducing huge page awareness. We evaluate MTM using common big-data applications with realistic working sets (hundreds of GB to 1 TB). MTM outperforms seven solutions by up to 42% (17% on average).
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Install the CLIlune papers fulltext e7934b07-74ac-4905-b560-d692624e0b7eCited by top-tier papers14
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