Fusuma: double-ended threaded compaction

Onozawa, Hiro; Ugawa, Tomoharu; Iwasaki, Hideya

doi:10.1145/3459898.3463903

Cited by 5 publications

(2 citation statements)

References 17 publications

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“…We used the Ubuntu Linux 20.04.5 TLS operating system and GCC 9.4.0 compiler to compile eJSVM. eJSVM was configured for a 64-bit environment and uses the Fusuma sliding compaction GC [14].…”

Section: Discussionmentioning

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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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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Section: Discussionmentioning

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

Self Cite

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“…When generating eJSVMs on the FD, however, we had to disable these capabilities because of the limited RAM size. All of the VMs used the garbage collection with the Fusuma compaction [18].…”

Section: Evaluation 61 Evaluation Setupmentioning

confidence: 99%

Generating Virtual Machine Code of JavaScript Engine for Embedded Systems

Hirasawa

Iwasaki

Ugawa

et al. 2022

Journal of Information Processing

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Virtual machines (VMs) for dynamically managed languages such as JavaScript are generally implemented in C or C++. Implementation of VMs in such low-level languages offers the advantage of high flexibility, but it suffers from problems of descriptiveness and safety. These problems are due to the fact that even though a variety of VM operations are based on the VM's internal datatypes for first-class objects in the target language, the C code typically treats all VM internal datatypes as a single type in C. In addition, VMs implemented in C or C++ have a size problem which is a serious issue for VMs on embedded systems. The reason for this problem is the difficulty of eliminating unnecessary code fragments from the C code for a specific application. To solve these problems, we propose a domain-specific language for describing VM programs and a corresponding compiler to C programs, called VMDL and VMDLC, respectively. We also propose related utility tools. This framework enables generation of C source code for an eJSVM, a JavaScript VM for embedded systems. VMDL's concise syntax enables static VM datatype analysis for optimizations and error detection. We evaluated the framework and confirmed its effectiveness from both qualitative and quantitative viewpoints.

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Using Dynamic Memory Reallocation in GInv

Blinkov

Shchetinin

2023

Program Comput Soft

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Fusuma: double-ended threaded compaction

Cited by 5 publications

References 17 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

Generating Virtual Machine Code of JavaScript Engine for Embedded Systems

Using Dynamic Memory Reallocation in GInv

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