Paging for multi-core shared caches

López-Ortíz, Alejandro; Salinger, Alejandro

doi:10.1145/2090236.2090246

Cited by 17 publications

(9 citation statements)

References 38 publications

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“…Katti and Ramachandran consider page replacement polices for multicore shared-cache environments [29]. Several authors have considered other aspects of paging where the size of internal memory or the pages themselves vary [2,25,27,32,33,46] e.g., because several processes share the same cache. For example, [32] considers a model where the application itself adjusts the cache-size, and [27,46] consider a model where the page sizes vary.…”

Section: Related Workmentioning

confidence: 99%

Cache-Adaptive Algorithms

Bender¹,

Ebrahimi²,

Fineman³

et al. 2013

Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms

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We introduce the cache-adaptive model, which generalizes the external-memory model to apply to environments in which the amount of memory available to an algorithm can fluctuate. The cache-adaptive model applies to operating systems, databases, and other systems where the allocation of memory to processes changes over time. We prove that if an optimal cache-oblivious algorithm has a particular recursive structure, then it is also an optimal cache-adaptive algorithm. Cache-oblivious algorithms having this form include Floyd-Warshall all pairs shortest paths, naïve recursive matrix multiplication, matrix transpose, and Gaussian elimination. While the cache-oblivious sorting algorithm Lazy Funnel Sort does not have this recursive structure, we prove that it is nonetheless optimally cache-adaptive. We also establish that if a cache-oblivious algorithm is optimal on "square" (well-behaved) memory profiles then, given resource augmentation it is optimal on all memory profiles. We give paging algorithms for the case where the cache size changes dynamically. We prove that LRU with 4memory and 4-speed augmentation is competitive with optimal. Moreover, Belady's algorithm remains optimal even when the cache size changes. Cache-obliviousness is distinct from cache-adaptivity. We exhibit a cache-oblivious algorithm that is not cacheadaptive and a cache-adaptive algorithm for a problem having no optimal cache-oblivious solution.

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Section: Related Workmentioning

confidence: 99%

Cache-Adaptive Algorithms

Bender¹,

Ebrahimi²,

Fineman³

et al. 2013

Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms

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“…We refer to this type of interleaving as free interleaving. Hassidim [15] and Lopez-Ortiz and Salinger [18] considered free interleaving while analyzing cache replacement algorithms at the shared cache.…”

Section: Disjoint and Shared Memory Frameworkmentioning

confidence: 99%

Competitive Cache Replacement Strategies for Shared Cache Environments

Katti

Ramachandran

2012

2012 IEEE 26th International Parallel and Distributed Processing Symposium

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“…Cache partitioning has emerged as a technique to increase run time predictability and increase performance on multi-core processors [8,14]. Theoretic research on online multi-core caching shows that the cache partition (which may be dynamic) has more influence on the performance than the eviction policy [5,12]. To obtain effective cache partitions, methods have been developed to estimate the running time of jobs as a function of allocated cache, that is the functions T j (x) (see for example the cache locking technique of [10]).…”

Section: Introductionmentioning

confidence: 99%

“…Related Work: Theoretic study of multi-core caching have shown that traditional online paging algorithms are not competitive in the multi-core scenario [5,12]. Both papers [5,12] show that the offline decision version of the caching problem is NP-complete, in slightly different models. Much of the difficulty in designing competitive online algorithms for multi-core caching stems from the fact that the way in which the request sequences of the different cores interleave is dependent on the algorithm.…”

Section: Introductionmentioning

confidence: 99%

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Joint Cache Partition and Job Assignment on Multi-core Processors

Hassidim

Kaplan

Tuval

2013

Lecture Notes in Computer Science

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Multicore shared cache processors pose a challenge for designers of embedded systems who try to achieve minimal and predictable execution time of workloads consisting of several jobs. To address this challenge the cache is statically partitioned among the cores and the jobs are assigned to the cores so as to minimize the makespan. Several heuristic algorithms have been proposed that jointly decide how to partition the cache among the cores and assign the jobs. We initiate a theoretical study of this problem which we call the joint cache partition and job assignment problem.By a careful analysis of the possible cache partitions we obtain a constant approximation algorithm for this problem. For some practical special cases we obtain a 2-approximation algorithm, and show how to improve the approximation factor even further by allowing the algorithm to use additional cache. We also study possible improvements that can be obtained by allowing dynamic cache partitions and dynamic job assignments.We define a natural special case of the well known scheduling problem on unrelated machines in which machines are ordered by "strength". Our joint cache partition and job assignment problem generalizes this scheduling problem which we think is of independent interest. We give a polynomial time algorithm for this scheduling problem for instances obtained by fixing the cache partition in a practical case of the joint cache partition and job assignment problem where job loads are step functions.

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Paging for multi-core shared caches

Cited by 17 publications

References 38 publications

Cache-Adaptive Algorithms

Cache-Adaptive Algorithms

Competitive Cache Replacement Strategies for Shared Cache Environments

Joint Cache Partition and Job Assignment on Multi-core Processors

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