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Conference Papers Year : 2016

Efficient Management for Hybrid Memory in Managed Language Runtime

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Abstract

Hybrid memory, which leverages the benefits of traditional DRAM and emerging memory technologies, is a promising alternative for future main memory design. However popular management policies through memory-access recording and page migration may invoke non-trivial overhead in execution time and hardware space. Nowadays, managed language applications are increasingly dominant in every kind of platform. Managed runtimes provide services for automatic memory management. So it is important to adapt them for the underlying hybrid memory.This paper explores two opportunities, heap partition placement and object promotion, inside managed runtimes for allocating hot data in a fast memory space (fast-space) without any access recording or data migration overhead. For heap partition placement, we quantitatively analyze LLC miss density and performance effect for each partition. Results show that LLC misses especially store misses mostly hit nursery partitions. Placing nursery in fast-space, which is 20 % total memory footprint of tested benchmarks on average, causes only 10 % performance difference from all memory footprint in fast-space. During object promotion, hot objects will be directly allocated to fast-space. We develop a tool to analyze the LLC miss density for each method of workloads, since we have found that the LLC misses are mostly triggered by a small percentage of the total set of methods. The objects visited by the top-ranked methods are recognized as hot. Results show that hot objects do have higher access density, more than 3 times of random distribution for SPECjbb and pmd, and placing them in fast-space further reduces their execution time by 6 % and 13 % respectively.
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Dates and versions

hal-01647992 , version 1 (24-11-2017)

Licence

Attribution - CC BY 4.0

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Cite

Chenxi Wang, Ting Cao, John Zigman, Fang Lv, Yunquan Zhang, et al.. Efficient Management for Hybrid Memory in Managed Language Runtime. 13th IFIP International Conference on Network and Parallel Computing (NPC), Oct 2016, Xi'an, China. pp.29-42, ⟨10.1007/978-3-319-47099-3_3⟩. ⟨hal-01647992⟩
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