Utilizing field usage patterns for Java heap space optimization

Guo, Zhuang; Amaral, José Nelson; Szafron, Duane; Wang, Yan

doi:10.1145/1188966.1188974

Cited by 4 publications

(4 citation statements)

References 17 publications

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“…Chen et al consider the lifetime of object fields, rather than whole objects, since a field may not be active for the duration of its enclosing object's life; thus, fields with disjoint lifetimes can occupy the same memory, thereby reducing object footprint [32]. Similar work studied field lifetimes for the SpecJVM98 benchmark suite, and found on average a 14% reduction in heap space was possible [33]. Shankar et al profiled Java programs in an effort to identify short-live objects suitable for stack allocation [34].…”

Section: Profilingmentioning

confidence: 99%

Understanding the Impact of Collection Contracts on Design

Nelson

Pearce

Noble

2010

Objects, Models, Components, Patterns

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Abstract. Java provides a specification for a user-defined general purpose equivalence operator for objects, but collections such as Set have more stringent requirements. This inconsistency breaks polymorphism: programmers must take care to follow Set's contract rather than the more general Object contract if their object could enter a Set. We have dynamically profiled 30 Java applications to better understand the way programmers design their objects, to determine whether they program with collections in mind. Our results indicate that objects which enter collections behave very differently to objects which do not. Our findings should help developers understand the impact of design choices they make, and guide future language designers when adding support for collections and/or equality.

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Section: Profilingmentioning

confidence: 99%

Understanding the Impact of Collection Contracts on Design

Nelson

Pearce

Noble

2010

Objects, Models, Components, Patterns

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“…Kunkle and Cooperman [2008] [Bacon et al, 2002;Bonny and Henkel, 2007;Chen et al, 2005Chen et al, , 2003Clausen et al, 2000;Lekatsas et al, 2000;Lekatsas and Wolf, 1999;Rizzo, 1997;Shaham et al, 2001;Venstermans et al, 2007], heap sharing [Choi and Han, 2008], bytecode optimization [Vallée-Rai et al, 1999, prolific types [Shuf et al, 2002], colocation [Yu et al, 2008] and many other optimization/reduction techniques [Ananian and Rinard, 2003;Guo et al, 2006;McDowell et al, 1998;Tip et al, 1999].…”

Section: External Memory Algorithmsmentioning

confidence: 99%

JDiet: Footprint Reduction for Memory-constrained Systems

Huffman¹

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Main memory remains a scarce computing resource. Even though main memory is becoming more abundant, software applications are inexorably engineered to consume as much memory as is available. For example, expert systems, scientific computing, data mining, and embedded systems commonly suffer from the lack of main memory availability. This thesis introduces JDiet, an innovative memory management system for Java applications. The goal of JDiet is to provide the developer with a highly configurable framework to reduce the memory footprint of a memory-constrained system, enabling it to operate on much larger working sets. Inspired by buffer management techniques common in modern database management systems, JDiet frees main memory by evicting non-essential data to a disk-based store. A buffer retains a fixed amount of managed objects in main memory. As non-resident objects are accessed, they are swapped from the store to the buffer using an extensible replacement policy.While the Java virtual machine naïvely delegates virtual memory management to the operating system, JDiet empowers the system designer to select both the managed data and replacement policy.

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“…Chen et al consider the lifetime of object fields, rather than whole objects, since a field may not be active for the duration of its enclosing object's life; thus, fields with disjoint lifetimes can occupy the same memory, thereby reducing object footprint [25]. Similar work studied field lifetimes for the SpecJVM98 benchmark suite, and found on average a 14% reduction in heap space was possible [44]. Shankar et al profiled Java programs in an effort to identify short-live objects suitable for stack allocation [97].…”

Section: Object Lifecycle Profilingmentioning

confidence: 99%

Profiling Initialisation Behaviour in Java

Nelson¹

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<p>Freshly created objects are a blank slate: their mutable state and their constant properties must be initialised before they can be used. Programming languages like Java typically support object initialisation by providing constructor methods. This thesis examines the actual initialisation of objects in real-world programs to determine whether constructor methods support the initialisation that programmers actually perform. Determining which object initialisation techniques are most popular and how they can be identified will allow language designers to better understand the needs of programmers, and give insights that VM designers could use to optimise the performance of language implementations, reduce memory consumption, and improve garbage collection behaviour. Traditional profiling typically either focuses on timing, or uses sampling or heap snapshots to approximate whole program analysis. Classifying the behaviour of objects throughout their lifetime requires analysis of all program behaviour without approximation. This thesis presents two novel whole-program object profilers: one using purely class modification (#prof ), and a hybrid approach utilising class modification and JVM support (rprof ). #prof modifies programs using aspect-oriented programming tools to generate and aggregate data and examines objects that enter different collections to determine whether correlation exists between initialisation behaviour and the use of equality operators and collections. rprof confirms the results of an existing static analysis study of field initialisation using runtime analysis, and provides a novel study of object initialisation behaviour patterns.</p>

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Utilizing field usage patterns for Java heap space optimization

Cited by 4 publications

References 17 publications

Understanding the Impact of Collection Contracts on Design

Understanding the Impact of Collection Contracts on Design

JDiet: Footprint Reduction for Memory-constrained Systems

Profiling Initialisation Behaviour in Java

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