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27
On the limits of cacheobliviousness
 IN PROC. 35TH ANNUAL ACM SYMPOSIUM ON THEORY OF COMPUTING
, 2003
"... In this paper, we present lower bounds for permuting and sorting in the cacheoblivious model. We prove that (1) I/O optimal cacheoblivious comparison based sorting is not possible without a tall cache assumption, and (2) there does not exist an I/O optimalcacheoblivious algorithm for permuting, ..."
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Cited by 40 (7 self)
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In this paper, we present lower bounds for permuting and sorting in the cacheoblivious model. We prove that (1) I/O optimal cacheoblivious comparison based sorting is not possible without a tall cache assumption, and (2) there does not exist an I/O optimalcacheoblivious algorithm for permuting, not even in the presence of a tall cache assumption.Our results for sorting show the existence of an inherent tradeoff in the cacheoblivious model between the strength of the tall cache assumption and the overhead for the case M >> B, and show that Funnelsort and recursive binary mergesort are optimal algorithms in the sense that they attain this tradeoff.
Funnel heap  a cache oblivious priority queue
 In Proc. 13th Annual International Symposium on Algorithms and Computation, volume 2518 of LNCS
, 2002
"... Abstract The cache oblivious model of computation is a twolevel memory model with the assumption that the parameters of the model are unknown to the algorithms. A consequence of this assumption is that an algorithm efficient in the cache oblivious model is automatically efficient in a multilevel m ..."
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Cited by 34 (8 self)
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Abstract The cache oblivious model of computation is a twolevel memory model with the assumption that the parameters of the model are unknown to the algorithms. A consequence of this assumption is that an algorithm efficient in the cache oblivious model is automatically efficient in a multilevel memory model. Arge et al. recently presented the first optimal cache oblivious priority queue, and demonstrated the importance of this result by providing the first cache oblivious algorithms for graph problems. Their structure uses cache oblivious sorting and selection as subroutines. In this paper, we devise an alternative optimal cache oblivious priority queue based only on binary merging. We also show that our structure can be made adaptive to different usage profiles. 1
CacheOblivious Data Structures and Algorithms for Undirected BreadthFirst Search and Shortest Paths
 IN PROCEEDINGS OF THE 9TH SCANDINAVIAN WORKSHOP ON ALGORITHM THEORY
, 2004
"... We present improved cacheoblivious data structures and algorithms for breadthfirst search and the singlesource shortest path problem on undirected graphs with nonnegative edge weights. Our results close the performance gap between the currently best cacheaware algorithms for these problems and ..."
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Cited by 25 (9 self)
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We present improved cacheoblivious data structures and algorithms for breadthfirst search and the singlesource shortest path problem on undirected graphs with nonnegative edge weights. Our results close the performance gap between the currently best cacheaware algorithms for these problems and their cacheoblivious counterparts. Our shortestpath algorithm relies on a new data structure, called bucket heap, which is the first cacheoblivious priority queue to efficiently support a weak DecreaseKey operation.
Engineering a cacheoblivious sorting algorithm
 In Proc. 6th Workshop on Algorithm Engineering and Experiments
, 2004
"... The cacheoblivious model of computation is a twolevel memory model with the assumption that the parameters of the model are unknown to the algorithms. A consequence of this assumption is that an algorithm efficient in the cache oblivious model is automatically efficient in a multilevel memory mod ..."
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Cited by 25 (1 self)
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The cacheoblivious model of computation is a twolevel memory model with the assumption that the parameters of the model are unknown to the algorithms. A consequence of this assumption is that an algorithm efficient in the cache oblivious model is automatically efficient in a multilevel memory model. Since the introduction of the cacheoblivious model by Frigo et al. in 1999, a number of algorithms and data structures in the model has been proposed and analyzed. However, less attention has been given to whether the nice theoretical proporities of cacheoblivious algorithms carry over into practice. This paper is an algorithmic engineering study of cacheoblivious sorting. We investigate a number of implementation issues and parameters choices for the cacheoblivious sorting algorithm Lazy Funnelsort by empirical methods, and compare the final algorithm with Quicksort, the established standard for comparison based sorting, as well as with recent cacheaware proposals. The main result is a carefully implemented cacheoblivious sorting algorithm, which we compare to the best implementation of Quicksort we can find, and find that it competes very well for input residing in RAM, and outperforms Quicksort for input on disk. 1
Cacheoblivious data structures for orthogonal range searching
 IN PROC. ACM SYMPOSIUM ON COMPUTATIONAL GEOMETRY
, 2003
"... We develop cacheoblivious data structures for orthogonal range searching, the problem of finding all T points in a set of N points in Rd lying in a query hyperrectangle. Cacheoblivious data structures are designed to be efficient in arbitrary memory hierarchies. We describe a dynamic linearsize ..."
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Cited by 23 (6 self)
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We develop cacheoblivious data structures for orthogonal range searching, the problem of finding all T points in a set of N points in Rd lying in a query hyperrectangle. Cacheoblivious data structures are designed to be efficient in arbitrary memory hierarchies. We describe a dynamic linearsize data structure that answers ddimensional queries in O((N/B)11/d + T/B) memory transfers, where B is the block size of any two levels of a multilevel memory hierarchy. A point can be inserted into or deleted from this data structure in O(log2B N) memory transfers. We also develop a static structure for the twodimensional case that answers queries in O(logB N + T /B) memory transfers using O(N log22 N) space. The analysis of the latter structure requires that B = 22 c for some nonnegative integer constant c.
The cost of cacheoblivious searching
 IN PROC. 44TH ANN. SYMP. ON FOUNDATIONS OF COMPUTER SCIENCE (FOCS
, 2003
"... This paper gives tight bounds on the cost of cacheoblivious searching. The paper shows that no cacheoblivious search structure can guarantee a search performance of fewer than lgelog B N memory transfers between any two levels of the memory hierarchy. This lower bound holds even if all of the bloc ..."
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Cited by 18 (8 self)
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This paper gives tight bounds on the cost of cacheoblivious searching. The paper shows that no cacheoblivious search structure can guarantee a search performance of fewer than lgelog B N memory transfers between any two levels of the memory hierarchy. This lower bound holds even if all of the block sizes are limited to be powers of 2. The paper gives modified versions of the van Emde Boas layout, where the expected number of memory transfers between any two levels of the memory hierarchy is arbitrarily close to [lge+O(lglgB/lgB)]log B N +O(1). This factor approaches lge ≈ 1.443 as B increases. The expectation is taken over the random placement in memory of the first element of the structure. Because searching in the diskaccess machine (DAM) model can be performed in log B N+O(1) block transfers, thisresultestablishes aseparation between the (2level) DAM model and cacheoblivious model. The DAM model naturally extends to k levels. The paper also shows that as k grows, the search costs of the optimal klevel DAM search structure and the optimal cacheoblivious search structure rapidly converge. This result demonstrates that for a multilevel memory hierarchy, a simple cacheoblivious structure almost replicates the performance of an optimal parameterized klevel DAM structure.
CacheOblivious Planar Orthogonal Range Searching and Counting
 In Proc. ACM Symposium on Computational Geometry
, 2005
"... We present the first cacheoblivious data structure for planar orthogonal range counting, and improve on previous results for cacheoblivious planar orthogonal range searching. Our range counting structure uses O(N log2 N) space and answers queries using O(logB N) memory transfers, where B is the bl ..."
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Cited by 15 (4 self)
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We present the first cacheoblivious data structure for planar orthogonal range counting, and improve on previous results for cacheoblivious planar orthogonal range searching. Our range counting structure uses O(N log2 N) space and answers queries using O(logB N) memory transfers, where B is the block size of any memory level in a multilevel memory hierarchy. Using bit manipulation techniques, the space can be further reduced to O(N). The structure can also be modified to support more general semigroup range sum queries in O(logB N) memory transfers, using O(N log2 N) space for threesided queries and O(N log 2 2 N / log2 log2 N)
Cacheaware and cacheoblivious adaptive sorting
 In Proc. 32nd International Colloquium on Automata, Languages, and Programming, Lecture Notes in Computer Science
, 2005
"... Abstract. Two new adaptive sorting algorithms are introduced which perform an optimal number of comparisons with respect to the number of inversions in the input. The first algorithm is based on a new linear time reduction to (nonadaptive) sorting. The second algorithm is based on a new division pr ..."
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Cited by 11 (4 self)
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Abstract. Two new adaptive sorting algorithms are introduced which perform an optimal number of comparisons with respect to the number of inversions in the input. The first algorithm is based on a new linear time reduction to (nonadaptive) sorting. The second algorithm is based on a new division protocol for the GenericSort algorithm by EstivillCastro and Wood. From both algorithms we derive I/Ooptimal cacheaware and cacheoblivious adaptive sorting algorithms. These are the first I/Ooptimal adaptive sorting algorithms. 1
Cacheoblivious algorithms and data structures
 IN SWAT
, 2004
"... Frigo, Leiserson, Prokop and Ramachandran in 1999 introduced the idealcache model as a formal model of computation for developing algorithms in environments with multiple levels of caching, and coined the terminology of cacheoblivious algorithms. Cacheoblivious algorithms are described as stand ..."
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Cited by 10 (1 self)
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Frigo, Leiserson, Prokop and Ramachandran in 1999 introduced the idealcache model as a formal model of computation for developing algorithms in environments with multiple levels of caching, and coined the terminology of cacheoblivious algorithms. Cacheoblivious algorithms are described as standard RAM algorithms with only one memory level, i.e. without any knowledge about memory hierarchies, but are analyzed in the twolevel I/O model of Aggarwal and Vitter for an arbitrary memory and block size and an optimal offline cache replacement strategy. The result are algorithms that automatically apply to multilevel memory hierarchies. This paper gives an overview of the results achieved on cacheoblivious algorithms and data structures since the seminal paper by Frigo et al.