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A comprehensive study of hardware/software approaches to improve TLB performance for java applications on embedded systems
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Source Memory System Performance archive
Proceedings of the 2006 workshop on Memory system performance and correctness table of contents
San Jose, California
SESSION: Cache and TLB design table of contents
Pages: 102 - 111  
Year of Publication: 2006
ISBN:1-59593-578-9
Authors
Jinzhan Peng  Intel Corporation
Guei-Yuan Lueh  Intel Corporation
Gansha Wu  Intel Corporation
Xiaogang Gou  Intel Corporation
Ryan Rakvic  United States Naval Academy
Sponsor
SIGPLAN: ACM Special Interest Group on Programming Languages
Publisher
ACM  New York, NY, USA
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ABSTRACT

The working set size of Java applications on embedded systems has recently been increasing, causing the Translation Lookaside Buffer (TLB) to become a serious performance bottleneck. From a thorough analysis of the SPECjvm98 benchmark suite executing on a commodity embedded system, we find TLB misses attribute from 24% to 50% of the total execution time. We explore and evaluate a wide spectrum of TLB-enhancing techniques with different combinations of software/hardware approaches, namely superpage for reducing TLB miss rates, two-level TLB and TLB prefetching for reducing both TLB miss rates and TLB miss latency, and even a no-TLB design for removing TLB overhead completely. We adapt and then in a novel way extend these approaches to fit the design space of embedded systems executing Java code. We compare these approaches, discussing their performance behavior, software/hardware complexity and constraints, especially the design implications for the application, runtime and OS.We first conclude that even with the aggressive approaches presented, there remains a performance bottleneck with the TLB. Second, in addition to facing very different design considerations and constraints for embedded systems, proven hardware techniques, such as TLB prefetching have different performance implications. Third, software based solutions, no-TLB design and superpaging, appear to be more effective in improving Java application performance on embedded systems. Finally, beyond performance, these approaches have their respective pros and cons; it is left to the system designer to make the appropriate engineering tradeoff.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Gansha Wu, Xin Zhou, Biao Chen, Peng Guo, Jinzhan Peng, Victor Ying. Memory Management for Multitasking Java on Resource-Constrained Devices. Submitted to HiPEAC'07.
 
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Gansha Wu, Xin Zhou, Guei-Yuan Lueh, Jesse Z. Fang, Peng Guo, Jinzhan Peng, Victor Ying. XAMM: A High-performance Automatic Memory Management System with Memory-Constrained Designs. In the proceeding of HiPEAC 2005:130--149
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Zhen Fang and Lixin Zhang. A Comparison of Online Superpage Promotion Mechanisms. www2.cs.utah.edu/impulse/papers/UUCS-99-021.ps.gz
 
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SpecJVM98, http://www.spec.org/jvm98/
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Collaborative Colleagues:
Jinzhan Peng: colleagues
Guei-Yuan Lueh: colleagues
Gansha Wu: colleagues
Xiaogang Gou: colleagues
Ryan Rakvic: colleagues