Region inference for an object-oriented language

Chin, Wei-Ngan; Craciun, Florin; Qin, Shengchao; Rinard, Martin

doi:10.1145/996841.996871

Cited by 31 publications

(17 citation statements)

References 37 publications

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“…Region allocation either manages all of memory based on allocationsite lifetime scoping [12,19,32,37] or adds regions as a special purpose component management [6,22,24]. Regions provide programmability benefits for real-time systems and offer safety features such as thread isolation in server applications, but these features come without the software engineering advantages of garbage collection.…”

Section: Region Allocationmentioning

confidence: 99%

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Free-Me

2006

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Garbage collection has proven benefits, including fewer memoryrelated errors and reduced programmer effort. Garbage collection, however, trades space for time. It reclaims memory only when it is invoked: invoking it more frequently reclaims memory quickly, but incurs a significant cost; invoking it less frequently fills memory with dead objects. In contrast, explicit memory management provides prompt low cost reclamation, but at the expense of programmer effort.This work comes closer to the best of both worlds by adding novel compiler and runtime support for compiler inserted frees to a garbage-collected system. The compiler's free-me analysis identifies when objects become unreachable and inserts calls to free. It combines a lightweight pointer analysis with liveness information that detects when short-lived objects die. Our approach differs from stack and region allocation in two crucial ways. First, it frees objects incrementally exactly when they become unreachable, instead of based on program scope. Second, our system does not require allocation-site lifetime homogeneity, and thus frees objects on some paths and not on others. It also handles common patterns: it can free objects in loops and objects created by factory methods.We evaluate free() variations for free-list and bump-pointer allocators. Explicit freeing improves performance by promptly reclaiming objects and reducing collection load. Compared to marksweep alone, free-me cuts total time by 22% on average, collector time by 50% to 70%, and allows programs to run in 17% less memory. This combination retains the software engineering benefits of garbage collection while increasing space efficiency and improving performance, and thus is especially appealing for real-time and space constrained systems.

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Section: Region Allocationmentioning

confidence: 99%

“…Compared with region [12,24,32,37] and stack [10,13,20,39] allocation, our approach differs in two key ways. First, region and stack allocation require lifetimes to coincide with a particular program scope, whereas our approach frees objects exactly when they become unreachable.…”

Section: Introductionmentioning

confidence: 99%

Free-Me

2006

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“…Note that this may actually eliminate some memory leaks in the program! In the second pass (lines [12][13][14][15][16][17][18][19][20], the algorithm replaces calls to malloc() and free() 3 with calls to poolalloc and poolfree.…”

Section: Analysis: Finding Pool Descriptors For Each H Nodementioning

confidence: 99%

“…There is a rich body of work on automatic region inference as a technique for memory management, for both functional [45,44,1,24] and object-oriented languages [14,10]. Unlike this body of our work, our primary goal is to segregate and control the layout of data structures in the heap for better performance and to enable subsequent compiler techniques that exploit knowledge of these layouts.…”

Section: Related Workmentioning

confidence: 99%

“…An alternative approach for segregating heap objects under compiler control is the work on automatic region inference for ML [45,44,24] and more recently for Java [14,10]. These techniques partition objects into heap regions based on lifetimes, with the primary goal of providing automatic memory management with little or no garbage collection for type-safe languages.…”

Section: Introductionmentioning

confidence: 99%

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Automatic pool allocation

Lattner

Adve

2005

Proceedings of the 2005 ACM SIGPLAN Conference on Programming Language Design and Implementation

124

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This paper describes Automatic Pool Allocation, a transformation framework that segregates distinct instances of heap-based data structures into seperate memory pools and allows heuristics to be used to partially control the internal layout of those data structures. The primary goal of this work is performance improvement, not automatic memory management, and the paper makes several new contributions. The key contribution is a new compiler algorithm for partitioning heap objects in imperative programs based on a context-sensitive pointer analysis, including a novel strategy for correct handling of indirect (and potentially unsafe) function calls. The transformation does not require type safe programs and works for the full generality of C and C++. Second, the paper describes several optimizations that exploit data structure partitioning to further improve program performance. Third, the paper evaluates how memory hierarchy behavior and overall program performance are impacted by the new transformations. Using a number of benchmarks and a few applications, we find that compilation times are extremely low, and overall running times for heap intensive programs speed up by 10-25% in many cases, about 2x in two cases, and more than 10x in two small benchmarks. Overall, we believe this work provides a new framework for optimizing pointer intensive programs by segregating and controlling the layout of heapbased data structures.

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A Relational Static Semantics for Call Graph Construction

Zhuo

Zhang

2019

Formal Methods and Software Engineering

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The problem of resolving virtual method and interface calls in object-oriented languages has been a long standing challenge to the program analysis community. The complexities are due to various reasons, such as increased levels of class inheritance and polymorphism in large programs. In this paper, we propose a new approach called type flow analysis that represent propagation of type information between program variables by a group of relations without the help of a heap abstraction. We prove that regarding the precision on reachability of class information to a variable, our method produces results equivalent to that one can derive from a points-to analysis. Moreover, in practice, our method consumes lower time and space usage, as supported by the experimental results.

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Region inference for an object-oriented language

Cited by 31 publications

References 37 publications

Free-Me

Free-Me

Automatic pool allocation

A Relational Static Semantics for Call Graph Construction

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