Improving cache behavior of dynamically allocated data structures

Truong, Dan; Bodin, François; Seznec, André

doi:10.1109/pact.1998.727268

Cited by 52 publications

(61 citation statements)

References 12 publications

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“…Truong et al propose ialloc to facilitate programmer driven field reorganization and instance interleaving, where frequently used "hot" fields of many instances are interleaved, so that "cold" fields do not occupy the same cache line as hot fields [38]. Chillimbi et al automate this process for Java programs with a profiling and program transformation tool, and automatically generate field reordering recommendations for C programs [6].…”

Section: Related Workmentioning

confidence: 99%

Automatically enhancing locality for tree traversals with traversal splicing

Kulkarni

2012

Proceedings of the ACM International Conference on Object Oriented Programming Systems Languages and Applications

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Generally applicable techniques for improving temporal locality in irregular programs, which operate over pointerbased data structures such as trees and graphs, are scarce. Focusing on a subset of irregular programs, namely, tree traversal algorithms like Barnes-Hut and nearest neighbor, previous work has proposed point blocking, a technique analogous to loop tiling in regular programs, to improve locality. However point blocking is highly dependent on point sorting, a technique to reorder points so that consecutive points will have similar traversals. Performing this a priori sort requires an understanding of the semantics of the algorithm and hence highly application specific techniques.In this work, we propose traversal splicing, a new, general, automatic locality optimization for irregular tree traversal codes, that is less sensitive to point order, and hence can deliver substantially better performance, even in the absence of semantic information. For six benchmark algorithms, we show that traversal splicing can deliver singlethread speedups of up to 9.147 (geometric mean: 3.095) over baseline implementations, and up to 4.752 (geometric mean: 2.079) over point-blocked implementations. Further, we show that in many cases, automatically applying traversal splicing to a baseline implementation yields performance that is better than carefully hand-optimized implementations.

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Section: Related Workmentioning

confidence: 99%

Automatically enhancing locality for tree traversals with traversal splicing

Kulkarni

2012

Proceedings of the ACM International Conference on Object Oriented Programming Systems Languages and Applications

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“…The previous techniques are all based on the frequency of data accesses. In contrast, another approach is to focus on data that is the most cache-conflict prone (Panda et al, 1997), (Truong et al, 1998). In the rest of this paper, we will refer to the strategy BEH as a basis for our memory energy optimizations.…”

Section: Existing Heuristics and Related Workmentioning

confidence: 99%

Genetic Heuristics for Reducing Memory Energy Consumption in Embedded Systems

Aouad

Schott

Zendra

2010

Proceedings of the 5th International Conference on Software and Data Technologies

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Abstract:Nowadays, reducing memory energy has become one of the top priorities of many embedded systems designers. Given the power, cost, performance and real-time advantages of Scratch-Pad Memories (SPMs), it is not surprising that SPM is becoming a common form of SRAM in embedded processors today. In this paper, we focus on heuristic methods for SPMs careful management in order to reduce memory energy consumption. We propose Genetic Heuristics for memory management which are, to the best of our knowledge, new original alternatives to the best known existing heuristic (BEH). Our Genetic Heuristics outperform BEH. In fact, experimentations performed on our benchmarks show that our Genetic Heuristics consume from 76.23% up to 98.92% less energy than BEH in different configurations. In addition they are easy to implement and do not require list sorting (contrary to BEH).

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“…Truong et. al explore field reorganization and instance interleaving techniques along with a specialized memory allocator designed to work with the latter to improve cache locality (30). However, its limitations (manual intervention, no support for arrays of structures, and data structure modifications) limit its practicality for large applications.…”

Section: Related Workmentioning

confidence: 99%

Two memory allocators that use hints to improve locality

Jula¹,

Rauchwerger

2009

Proceedings of the 2009 International Symposium on Memory Management

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Dynamic memory allocators affect an application's performance through their data layout quality. They can use an application's allocation hints to improve the spatial locality of this layout. However, a practical approach needs to be automatic, without user intervention. In this paper we present two locality improving allocators, that use allocation hints provided automatically from the C++ STL library to improve an application's spatial locality. When compared to state-of-the-art allocators on seven real world applications, our allocators run on average 7% faster than the Lea allocator, and 17% faster than the FreeBSD's allocator, with the same memory fragmentation as the Lea allocator, one of the best allocators.While considering locality as an important goal, locality improving allocators must not abandon the existing constraints of fast allocation speed and low fragmentation. These constraints further challenge their design and implementation. We experimentally show that within a memory allocator, allocation speed, memory fragmentation, and spatial locality compete with each other in a game of rock, paper, scissors: when one tries to improve one trait, the others suffer. We conclude that our allocators achieve a good balance of these traits, and they can easily be adjusted to optimize the most important trait for each application.

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Improving cache behavior of dynamically allocated data structures

Cited by 52 publications

References 12 publications

Automatically enhancing locality for tree traversals with traversal splicing

Automatically enhancing locality for tree traversals with traversal splicing

Genetic Heuristics for Reducing Memory Energy Consumption in Embedded Systems

Two memory allocators that use hints to improve locality

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