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Object-Level Memory Allocation and Migration in Hybrid Memory Systems

delete2020-09-01
delete23
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OA
AI
刘海坤 (Haikun Liu)
R
Renshan Liu
X
Xiaofei Liao *
金海 (Hai Jin)
B
Bingsheng He
Y
Yu Zhang
DOI:10.1109/TC.2020.2973134delete
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Abstract

Abstract

En 中文
Hybrid memory systems composed of emerging non-volatile memory (NVM) and DRAM have drawn increasing attention in recent years. To fully exploit the advantages of both NVM and DRAM, a primary goal is to properly place application data on the hybrid memories. Previous studies have focused on page migration schemes to achieve higher performance and energy efficiency. However, those schemes all rely on online page access monitoring (costly), and data migration at the page granularity may cause additional overhead due to DRAM bandwidth contention and maintenance of cache/TLB consistency. In this article, we present Object-level memory Allocation and Migration (OAM) mechanisms for hybrid memory systems. OAM exploits a profiling tool to characterize objects' memory access patterns at different execution phases of applications, and applies a performance/energy model to direct the initial static memory allocation and runtime dynamic object migration between NVM and DRAM. Based on our newly-developed programming interfaces for hybrid memory systems, application source codes can be automatically transformed via static code instrumentation. We evaluate OAM on an emulated hybrid memory system, and experimental results show that OAM can significantly reduce system energy-delay-product by 61 percent on average compared to a page-interleaving data placement scheme. It can also significantly reduce data migration overhead by 83 and 69 percent compared to the state-of-the-art page migration scheme CLOCK-DWF and 2PP, respectively, while improving application performance by up to 22 and 10 percent.
Keywords:
Non-volatile memory (NVM)
hybrid memory systems
object migration
memory allocation
data placement
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Journal

IEEE Transactions on Computers cover
IEEE Transactions on Computers
IF:
3.8
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5.3K
Citations:
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National University of Singapore
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Citations: 11.4W