Two-directional record layout for multiple inheritance
PLDI '90 Proceedings of the ACM SIGPLAN 1990 conference on Programming language design and implementation
Bidirectional object layout for separate compilation
Proceedings of the tenth annual conference on Object-oriented programming systems, languages, and applications
Efficient subtyping tests with PQ-encoding
OOPSLA '01 Proceedings of the 16th ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Space- and Time-Efficient Implementation of the Java Object Model
ECOOP '02 Proceedings of the 16th European Conference on Object-Oriented Programming
Automatic pool allocation for disjoint data structures
Proceedings of the 2002 workshop on Memory system performance
Data size optimizations for java programs
Proceedings of the 2003 ACM SIGPLAN conference on Language, compiler, and tool for embedded systems
The nesC language: A holistic approach to networked embedded systems
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Heap compression for memory-constrained Java environments
OOPSLA '03 Proceedings of the 18th annual ACM SIGPLAN conference on Object-oriented programing, systems, languages, and applications
Improving 64-Bit Java IPF Performance by Compressing Heap References
Proceedings of the international symposium on Code generation and optimization: feedback-directed and runtime optimization
Nonintrusive precision instrumentation of microcontroller software
LCTES '05 Proceedings of the 2005 ACM SIGPLAN/SIGBED conference on Languages, compilers, and tools for embedded systems
Avrora: scalable sensor network simulation with precise timing
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Compressing heap data for improved memory performance: Research Articles
Software—Practice & Experience
An object-aware memory architecture
Science of Computer Programming - Special issue on five perspectives on modern memory management: Systems, hardware and theory
Virgil: objects on the head of a pin
Proceedings of the 21st annual ACM SIGPLAN conference on Object-oriented programming systems, languages, and applications
Offline compression for on-chip ram
Proceedings of the 2007 ACM SIGPLAN conference on Programming language design and implementation
Performance implications of multiple pointer sizes
TCON'95 Proceedings of the USENIX 1995 Technical Conference Proceedings
No bit left behind: the limits of heap data compression
Proceedings of the 7th international symposium on Memory management
Vertical object layout and compression for fixed heaps
Semantics and algebraic specification
From OO to FPGA: fitting round objects into square hardware?
Proceedings of the ACM international conference on Object oriented programming systems languages and applications
Harmonizing classes, functions, tuples, and type parameters in virgil iii
Proceedings of the 34th ACM SIGPLAN conference on Programming language design and implementation
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Research into embedded sensor networks has placed increased focus on the problem of developing reliable and flexible software for microcontroller-class devices. Languages such as nesC [8] and Virgil [14] have brought higher-level programming idioms to this lowest layer of software, thereby adding expressiveness. Both languages are marked by the absence of dynamic memory allocation, which removes the need for a runtime system to manage memory. To provide data structures, nesC offers modules, and Virgil offers the application an opportunity to allocate and initialize objects during compilation. This paper explores techniques for compressing fixed object heaps with the goal of reducing the RAM footprint of a program. We explore table-based compression and introduce a novel form of object layout called vertical object layout. We provide experimental results that measure the impact on RAM size, code size, and execution time for a set of Virgil programs. Our results show that compressed vertical layout has better execution time and code size than table-based compression while achieving more than 20% heap reduction on 6 of 12 benchmark programs.