Platform independent dynamic Java virtual machine analysis

Daly, Charles A.; Horgan, Jane M.; Power, James F.; Waldron, John

doi:10.1145/376656.376826

Cited by 33 publications

(33 citation statements)

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“…On average 9 , the ratio of immutable classes ranges from 23.5% for JRuby, through 31.7% and 58.8% for Jython and Java, respectively, to 77.5% for Clojure. These systematic differences can be attributed both to different coding styles typical for the particular languages, 9 Calculated from the total number of classes. Figure 9.…”

Section: Field Object and Class Immutabilitymentioning

confidence: 99%

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Characteristics of dynamic JVM languages

Sarimbekov

Podzimek

Bulej

et al. 2013

Proceedings of the 7th ACM Workshop on Virtual Machines and Intermediate Languages

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The Java Virtual Machine (JVM) has become an execution platform targeted by many programming languages. However, unlike with Java, a statically-typed language, the performance of the JVM and its Just-In-Time (JIT) compiler with dynamically-typed languages lags behind purpose-built language-specific JIT compilers. In this paper, we aim to contribute to the understanding of the workloads imposed on the JVM by dynamic languages. We use various metrics to characterize the dynamic behavior of a variety of programs written in three dynamic languages (Clojure, Python, and Ruby) executing on the JVM. We identify the differences with respect to Java, and briefly discuss their implications.

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Section: Field Object and Class Immutabilitymentioning

confidence: 99%

“…In the case of statically-typed languages such as Java and Scala, the execution charateristics have become rather well understood, thanks to established metrics, benchmarks, and studies [9,11,[21][22][23]. In contrast, the execution characteristics of various dynamically-typed JVM languages have so far not been studied very extensively.…”

Section: Introductionmentioning

confidence: 99%

Characteristics of dynamic JVM languages

Sarimbekov

Podzimek

Bulej

et al. 2013

Proceedings of the 7th ACM Workshop on Virtual Machines and Intermediate Languages

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“…The detail of each test is exposed in Figure 6. Using JGrande 2.0 benchmark [6], the KVM speed slowdown is 6.46% as illustrated in Figure 7 The JOlden [3] benchmark shows a time execution increase of 9.86% as illustrated in Figure 8. For comparison, the averaged performance slowdown introduced by bytecode selfaccounting [1], that is for accounting bytecodes only, is centered around 20% [1] and 40% [10], depending on the publication.…”

Section: A Profilermentioning

confidence: 99%

The Weight-Watcher Service and its Lightweight Implementation

Garbinato

Guerraoui

Hulaas

et al. 2007

2007 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation

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Abstract-This paper presents the Weight-Watcher service. This service aims at providing resource consumption measurements and estimations for software executing on resourceconstrained devices. By using the Weight-Watcher, software components can continuously adapt and optimize their quality of service with respect to resource availability. The interface of the service is composed of a Profiler and a Predictor. We present an implementation that is lightweight in terms of CPU and memory. We also performed various experiments that convey (a) the tradeoff between the memory consumption of the service and the accuracy of the prediction, as well as (b) a maximum overhead of 10% on the execution speed of the VM for the Profiler to provide accurate measurements.

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“…4. Apache Commons, CarrotSearch for byte and string, and FastUtil, 4 do not provide internal sorting algorithms; thus, they are excluded from those results. For these measures, UPC modified is limited to sort for non-string types.…”

Section: Listsmentioning

confidence: 99%

UPC: Large-Scale Memory Efficient Java Primitive Collections

Hylock¹

2016

JSW

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Abstract:The Java programming language is versatile and robust, however, for large-scale applications with memory intensive processes, much is still to be desired. The public Java Development Kit (JDK) supports neither forcible object destruction nor large collection sizes (limited to 231-1) as found in choice computational languages such as Fortran and C/C++. Within Java's Hotspot, however, the non-public sun.misc.Unsafe class allows such features through basic off-heap functionality. The submitted UPC collections are fully integrated with Unsafe to provide large (i.e., 263-1), destructible arrays, lists, hash sets, hash maps, and matrices, consistent with advanced computational needs. Additionally, a customized version of OpenJDK 1.9 with bulk-operation Unsafe support and companion collections are provided. These tools are compared to Java and extent third-party primitive collections. Testing indicates UPC performs in a consistent to superior manner compared to the state-of-the-art, with greater improvements realized by way of the modified virtual machine.

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Platform independent dynamic Java virtual machine analysis

Cited by 33 publications

References 0 publications

Characteristics of dynamic JVM languages

Characteristics of dynamic JVM languages

The Weight-Watcher Service and its Lightweight Implementation

UPC: Large-Scale Memory Efficient Java Primitive Collections

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