Reusable inline caching for JavaScript performance

JavaScript is increasingly used for the Internet of Things (IoT) on embedded systems. However, JavaScript's memory footprint is a challenge, because normal JavaScript virtual machines (VMs) do not fit into the small memory of IoT devices. In part this is because a significant amount of memory is used by hidden classes, which are used to represent JavaScript's dynamic objects efficiently.In this research, we optimize the hidden class graph to minimize their memory use. Our solution collects the hidden class graph and related information for an application in a profiling run, and optimizes the graph offline. We reduce the number of hidden classes by avoiding introducing intermediate ones, for instance when properties are added one after another. Our optimizations allow the VM to assign the most likely final hidden class to an object at its creation. They also minimize re-allocation of storage for property values, and reduce the polymorphism of inline caches.We implemented these optimizations in a JavaScript VM, eJSVM, and found that offline optimization can eliminate 61.9% of the hidden classes on average. It also improves execution speed by minimizing the number of hidden class transitions for an object and reducing inline cache misses.CCS Concepts: • Software and its engineering → Virtual machines.

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“…Choi et al [5] reuse inline caches in the V8 JavaScript VM. Inline caches depend on the hidden classes.…”

Section: Related Workmentioning

confidence: 99%

“…V8 mitigates this problem by a technique called slack tracking, 5 which guesses the final size of the object being allocated from past behaviour of the program. V8 first allocates a large amount of extra space for an object.…”

Section: Introductionmentioning

confidence: 99%

Profile Guided Offline Optimization of Hidden Class Graphs for JavaScript VMs in Embedded Systems

Ugawa

Marr

Jones

2022

Proceedings of the 14th ACM SIGPLAN International Workshop on Virtual Machines and Intermediate Languages

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“…The basic idea of hidden classes is similar to the map in Self [Chambers et al 1989] and more introductions can be found in literature [Artoul 2015;Bevenius 2018;Chambers et al 1989;Choi et al 2019;Serrano and Feeley 2019]. Here we briefly describe the idea of hidden classes.…”

Section: Hidden Classesmentioning

confidence: 99%

“…However, their approach does not mention how to generate efficient ICs for OO-style JavaScript / TypeScript programs, where the highly polymorphic behaviors degrade the performance of conventional ICs. Choi et al [Choi et al 2019] propose a reusable IC design (RIC) to improve JavaScript performance, which saves the IC information in an execution in a context-independent way. Comparing with RIC, our HI technique focuses on leveraging class hierarchy information to statically generate enhanced hidden classes and ICs, which can't be generated and saved from the profiling runs of the RIC design.…”

Section: Related Workmentioning

confidence: 99%

Hidden inheritance: an inline caching design for TypeScript performance

Sun

Gong

et al. 2020

Proc. ACM Program. Lang.

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TypeScript is a dynamically typed language widely used to develop large-scale applications nowadays. These applications are usually designed with complex class or interface hierarchies and have highly polymorphic behaviors. These object-oriented (OO) features will lead to inefficient inline caches (ICs) or trigger deoptimizations, which impact the performance of TypeScript applications.To address this problem, we introduce an inline caching design called hidden inheritance (HI). The basic idea of HI is to cache the static information of class or interface hierarchies into hidden classes, which are leveraged to generate efficient inline caches for improving the performance of OO-style TypeScript programs. The HI design is implemented in a TypeScript engine STSC (Static TypeScript Compiler) including a static compiler and a runtime system. STSC statically generates hidden classes and enhanced inline caches, which are applied to generate specialized machine code via ahead-of-time compilation (AOTC) or just-in-time compilation (JITC). To evaluate the efficiency of this technique, we implement STSC on a state-of-the-art JavaScript virtual machine V8 and demonstrate its performance improvements on industrial benchmarks and applications.CCS Concepts: • Software and its engineering → Classes and objects; Dynamic compilers; Polymorphism.

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Os noise mitigations for benchmarking web browser execution environment performance

Toufie,

Kabaso

2024

Discov Computing

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Web browsers have almost since birth sought to host and run feature-rich, compute-intensive and complex applications, within their execution environments (EEs), thereby achieving performance akin to native desktop applications. Studies that have proposed performance improvements to these Web browser EEs together with their respective benchmarks have endeavoured to use proven methodologies with which they confirmed the scientific rigour of those benchmarks, but have often overlooked operating system (OS) noise and the negative impact that it has on benchmarks. This paper identifies the various types of OS noise that exist within a typical Intel-based computer system that utilises a Linux-based OS. While also reviewing what related studies have done to mitigate against them. A series of mitigations were then proposed for the Linux-based system that was then benchmarked using the PolyBench/C benchmarking suite. Whilst not all OS noise was mitigated against, our results confirm that the OS noise mitigations that were provided, significantly reduced OS noise. Further significance of this study is that a more controlled benchmarking environment is made available, due to focusing the CPU processing almost entirely on the benchmarks only, while also enhancing the precision and accuracy of the benchmarks. In this study, we lay down a foundation that will make future Web browser EE as well as any other type of computer software benchmarking more precise and accurate, thereby improving the scientific rigour of those benchmarks.

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Reusable inline caching for JavaScript performance

Cited by 7 publications

References 9 publications

Profile Guided Offline Optimization of Hidden Class Graphs for JavaScript VMs in Embedded Systems

Profile Guided Offline Optimization of Hidden Class Graphs for JavaScript VMs in Embedded Systems

Hidden inheritance: an inline caching design for TypeScript performance

Os noise mitigations for benchmarking web browser execution environment performance

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