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31
Cacheoblivious Btrees
, 2000
"... Abstract. This paper presents two dynamic search trees attaining nearoptimal performance on any hierarchical memory. The data structures are independent of the parameters of the memory hierarchy, e.g., the number of memory levels, the blocktransfer size at each level, and the relative speeds of me ..."
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Cited by 145 (23 self)
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Abstract. This paper presents two dynamic search trees attaining nearoptimal performance on any hierarchical memory. The data structures are independent of the parameters of the memory hierarchy, e.g., the number of memory levels, the blocktransfer size at each level, and the relative speeds of memory levels. The performance is analyzed in terms of the number of memory transfers between two memory levels with an arbitrary blocktransfer size of B; this analysis can then be applied to every adjacent pair of levels in a multilevel memory hierarchy. Both search trees match the optimal search bound of Θ(1+logB+1 N) memory transfers. This bound is also achieved by the classic Btree data structure on a twolevel memory hierarchy with a known blocktransfer size B. The first search tree supports insertions and deletions in Θ(1 + logB+1 N) amortized memory transfers, which matches the Btree’s worstcase bounds. The second search tree supports scanning S consecutive elements optimally in Θ(1 + S/B) memory transfers and supports insertions and deletions in Θ(1 + logB+1 N + log2 N) amortized memory transfers, matching the performance of the Btree for B = B Ω(log N log log N).
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 41 (8 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 35 (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
Scanning and traversing: maintaining data for traversals in a memory hierarchy
 In Proceedings of the 10th Annual European Symposium on Algorithms
, 2002
"... Abstract. We study the problem of maintaining a dynamic ordered set subject to insertions, deletions, and traversals of k consecutive elements. This problem is trivially solved on a RAM and on a simple twolevel memory hierarchy. We explore this traversal problem on more realistic memory models: the ..."
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Cited by 33 (12 self)
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Abstract. We study the problem of maintaining a dynamic ordered set subject to insertions, deletions, and traversals of k consecutive elements. This problem is trivially solved on a RAM and on a simple twolevel memory hierarchy. We explore this traversal problem on more realistic memory models: the cacheoblivious model, which applies to unknown and multilevel memory hierarchies, and sequentialaccess models, where sequential block transfers are less expensive than random block transfers. 1
CacheOblivious String Btrees
 IN: PROC. OF PRINCIPLES OF DATABASE SYSTEMS
, 2006
"... Btrees are the data structure of choice for maintaining searchable data on disk. However, Btrees perform suboptimally • when keys are long or of variable length, • when keys are compressed, even when using front compression, the standard Btree compression scheme, • for range queries, and • with r ..."
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Cited by 28 (5 self)
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Btrees are the data structure of choice for maintaining searchable data on disk. However, Btrees perform suboptimally • when keys are long or of variable length, • when keys are compressed, even when using front compression, the standard Btree compression scheme, • for range queries, and • with respect to memory effects such as disk prefetching. This paper presents a cacheoblivious string Btree (COSBtree) data structure that is efficient in all these ways: • The COSBtree searches asymptotically optimally and inserts and deletes nearly optimally. • It maintains an index whose size is proportional to the frontcompressed size of the dictionary. Furthermore, unlike standard frontcompressed strings, keys can be decompressed in a memoryefficient manner. • It performs range queries with no extra disk seeks; in contrast, Btrees incur disk seeks when skipping from leaf block to leaf block. • It utilizes all levels of a memory hierarchy efficiently and makes good use of disk locality by using cacheoblivious layout strategies.
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
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 (9 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 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 (2 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.
Worstcase optimal tree layout in a memory hierarchy
, 2004
"... Consider laying out a fixedtopology tree of N nodes into external memory with block size B so as to minimize the worstcase number of block memory transfers required to traverse a path from the root to a node of depth D. We prove that the optimal number of memory transfers is D ..."
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Cited by 6 (0 self)
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Consider laying out a fixedtopology tree of N nodes into external memory with block size B so as to minimize the worstcase number of block memory transfers required to traverse a path from the root to a node of depth D. We prove that the optimal number of memory transfers is D
HATtrie: A Cacheconscious Triebased Data Structure for Strings
, 2007
"... Tries are the fastest treebased data structures for managing strings inmemory, but are spaceintensive. The bursttrie is almost as fast but reduces space by collapsing triechains into buckets. This is not however, a cacheconscious approach and can lead to poor performance on current processors. ..."
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Cited by 4 (1 self)
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Tries are the fastest treebased data structures for managing strings inmemory, but are spaceintensive. The bursttrie is almost as fast but reduces space by collapsing triechains into buckets. This is not however, a cacheconscious approach and can lead to poor performance on current processors. In this paper, we introduce the HATtrie, a cacheconscious triebased data structure that is formed by carefully combining existing components. We evaluate performance using several realworld datasets and against other highperformance data structures. We show strong improvements in both time and space; in most cases approaching that of the cacheconscious hash table. Our HATtrie is shown to be the most efficient triebased data structure for managing variablelength strings inmemory while maintaining sort order.