Object-Aware Memory Compression for Smartphones

Memory compression is vitally important in controlling the memory consumption of smartphones. Unfortunately, mainstream compression schemes like zRAM do not work well with garbage collection (GC) in managed language runtimes. When GC is triggered, it traces objects in the heap and thus causes frequent swapping and repetitive memory compression/decompression, which introduces significant performance overhead and user experience degradation. To this end, we propose an object-aware compressed memory scheme named oaRAM , which allows GC algorithms to directly interpret compressed memory and thus eliminates the need for decompression during GC. Furthermore, we build swap-less memory reclamation by further bridging the semantic gap between the memory compression module in OS and the garbage collector in the language runtime. On the OS side, we provide an object-aware memory compression module, which leverages object semantics from language runtimes to compress and manage data in the kernel. On the language runtime side, we propose shadow heap, which allows GC threads to directly access compressed contents in the kernel. We have implemented oaRAM on Android, and the evaluation results show that it significantly reduces the number of swapping operations under memory-hungry scenarios, which results in improvements in application performance, the system’s application caching capability and device lifespan.

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Publication Details

Journal
ACM Transactions on Architecture and Code Optimization
Published
2025-10-08
DOI
https://doi.org/10.1145/3771285
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
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article

Object-Aware Memory Compression for Smartphones

Binyu Zang, Mingyu Wu, Xinrui Li, Haibo Chen et al.
ACM Transactions on Architecture and Code Optimization
Parallel Computing and Optimization Techniques
article

Object-Aware Memory Compression for Smartphones

Binyu Zang, Mingyu Wu, Xinrui Li, Haibo Chen, Zhenyu Yang
article en

Abstract

Memory compression is vitally important in controlling the memory consumption of smartphones. Unfortunately, mainstream compression schemes like zRAM do not work well with garbage collection (GC) in managed language runtimes. When GC is triggered, it traces objects in the heap and thus causes frequent swapping and repetitive memory compression/decompression, which introduces significant performance overhead and user experience degradation. To this end, we propose an object-aware compressed memory scheme named oaRAM , which allows GC algorithms to directly interpret compressed memory and thus eliminates the need for decompression during GC. Furthermore, we build swap-less memory reclamation by further bridging the semantic gap between the memory compression module in OS and the garbage collector in the language runtime. On the OS side, we provide an object-aware memory compression module, which leverages object semantics from language runtimes to compress and manage data in the kernel. On the language runtime side, we propose shadow heap, which allows GC threads to directly access compressed contents in the kernel. We have implemented oaRAM on Android, and the evaluation results show that it significantly reduces the number of swapping operations under memory-hungry scenarios, which results in improvements in application performance, the system’s application caching capability and device lifespan.

ACM Transactions on Architecture and Code OptimizationVol. 22(4)
Shanghai Jiao Tong University (CN), Institute of Natural Science (KP)
Openalex Percentile: Top 70%
Parallel Computing and Optimization Techniques
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Object-Aware Memory Compression for Smartphones — Binyu Zang, Mingyu Wu, et al. · ACM Transactions on Architecture and Code Optimization (2025) | TGRS Research Map | TGRS