Code size and performance optimization for mobile JavaScript just-in-time compiler

Lee, Seong-Won; Moon, Soo-Mook; Jung, Won-Ki; Oh, Jin-Seok; Oh, Hyeong-Seok

doi:10.1145/1739025.1739034

Cited by 6 publications

(2 citation statements)

References 2 publications

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“…Lee et al 31 optimized the machine code generated by JITC for the SFX JavaScript engine 32 (old version of JSC 10 ). This work focused on ARM Thumb2 architecture, which provides half‐sized encoding (16 bit) for small‐sized machine code.…”

Section: Related Workmentioning

confidence: 99%

Dynamic code compression for JavaScript engine

2023

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Web applications created using web languages such as HTML, CSS, and JavaScript are widely used regardless of execution environments, owing to their portability and popularity. Since JavaScript language is conventionally used for complex computations in large-scale web apps, many optimization techniques have been proposed to accelerate the JavaScript performance. However, most of these optimizations speed up JavaScript engines at the expense of consuming more memory. Hence, memory consumption becomes an additional concern in the JavaScript field. Based on the research on memory status, we unearthed that a substantial portion of the heap memory is allocated for JavaScript source code, particularly in lightweight JavaScript engines, which may range from 13.2% to a maximal 52.5% of the entire heap. To resolve this memory issue, this article suggests a new memory optimization method, called dynamic code compression that dynamically compresses the source code and keeps its compressed form instead of the source string. A novel heuristic is proposed to timely compress the source code. We also re-design the internal structure of the JavaScript engine to efficiently compress the source code without incurring any conflict. Using our code compression method, we could reduce the entire heap memory by up to 43.3% and consistently downsize the overall heap size. From an evaluation of standard benchmarks, our approach showed just 2.7% degradation in performance with negligible compression overhead, proving the feasibility of the code compression technique.

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Section: Related Workmentioning

confidence: 99%

Dynamic code compression for JavaScript engine

2023

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“…However, we assume no knowledge about the underlying JIT compilation mechanism -instead, we expect to draw all necessary conclusions from our collected data. On the other hand, there are several other studies that focus on tuning the underlying JavaScript JIT compilation mechanism to improve performance [12,21,22,23,24] or on selecting the best JavaScript framework to program with [17]. For instance, Lee and Moon [22] study, for mobile web browsers, how the JIT engine can be turned on or off in order to avoid waiting for the compilation of a code that may be not frequently executed enough to pay off the compilation time.…”

Section: Related Workmentioning

confidence: 99%

Addressing JavaScript JIT Engines Performance Quirks: A Crowdsourced Adaptive Compiler

Auler

Borin

Halleux

et al. 2014

Lecture Notes in Computer Science

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Abstract. JavaScript has long outpaced its original target applications, being used not only for coding complex web clients, but also web servers, game development and even desktop applications. The most appealing advantage of moving applications to JavaScript is its capability to run the same code in a large number of different devices. It is not surprising that many compilers target JavaScript as an intermediate language.However, writing optimizations and analyses passes for a compiler that emits JavaScript is challenging: a long time spent in optimizing the code in a certain way can be excellent for some browsers, but a futile effort for others. For example, we show that applying JavaScript code optimizations in a tablet with Windows 8 and Internet Explorer 11 increased performance by, on average, 5 times, while running in a desktop with Windows 7 and Firefox decreased performance by 20%. Such a scenario demands a radical new solution for the traditional compiler optimization flow. This paper proposes collecting web clients performance data to build a crowdsourced compiler flag suggestion system in the cloud that helps the compiler perform the appropriate optimizations for each client platform. Since this information comes from crowdsourcing rather than manual investigations, fruitless or harmful optimizations are automatically discarded. Our approach is based on live measurements done while clients use the application on real platforms, proposing a new paradigm on how optimizations are tested.

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Just-In-Time Push Prefetching: Accelerating the Mobile Web

Armstrong

Ward

2013

2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA)

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Code size and performance optimization for mobile JavaScript just-in-time compiler

Cited by 6 publications

References 2 publications

Dynamic code compression for JavaScript engine

Dynamic code compression for JavaScript engine

Addressing JavaScript JIT Engines Performance Quirks: A Crowdsourced Adaptive Compiler

Just-In-Time Push Prefetching: Accelerating the Mobile Web

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