Integrated prefetching and caching in single and parallel disk systems

Albers, Susanne; Büttner, Markus

doi:10.1016/j.ic.2005.01.003

Cited by 7 publications

(6 citation statements)

References 21 publications

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“…Another approach uses time series modeling [38] to predict temporal access patterns and issue prefetches during computation intervals. Prefetch algorithms tailored for parallel I/O systems have also been studied [1,20,22].…”

Section: I/o Prefetchingmentioning

confidence: 99%

“…In [7], Cao et al point out the interaction between integrated prefetching and caching and derive an aggressive prefetching policy with excellent competitive performance in the context of complete knowledge of future accesses. The work is followed by many integrated approaches, for example, [1,8,20,22,23,32,37] which are either offline or based on hints of I/O access patterns.…”

Section: Integrated Prefetching and Cachingmentioning

confidence: 99%

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The Performance Impact of Kernel Prefetching on Buffer Cache Replacement Algorithms

Butt

Gniady

2007

IEEE Trans. Comput.

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A fundamental challenge in improving the file system performance is to design effective block replacement algorithms to minimize buffer cache misses. Despite the well-known interactions between prefetching and caching, almost all buffer cache replacement algorithms have been proposed and studied comparatively without taking into account file system prefetching which exists in all modern operating systems. This paper shows that such kernel prefetching can have a significant impact on the relative performance in terms of the number of actual disk I/Os of many well-known replacement algorithms; it can not only narrow the performance gap but also change the relative performance benefits of different algorithms. These results demonstrate the importance for buffer caching research to take file system prefetching into consideration.

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Section: I/o Prefetchingmentioning

confidence: 99%

Section: Integrated Prefetching and Cachingmentioning

confidence: 99%

The Performance Impact of Kernel Prefetching on Buffer Cache Replacement Algorithms

Butt

Gniady

2007

IEEE Trans. Comput.

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“…The final instance of each block must be output to its assigned disk. 3 We prove that the following offline algorithm manyWriting minimizes the number of output operations for the write-many problem: Let Q denote the set of blocks in the buffer pool, so initially Q = ∅. Let Q d = {b ∈ Q : disk(b) = d} denote the blocks queued for disk d. To write block b i , if b i ∈ Q, the old version is overwritten in its existing buffer.…”

Section: Prefetching With Cachingmentioning

confidence: 99%

“…Albers, Garg, and Leonardi [4] gave an optimal polynomial time offline algorithm for the single-disk case in the penalty model, but it does not generalize well to multiple disks. Albers and Büttner [3] overcame this problem by requiring synchronized parallel disk access (as in the I/O model) and by postulating O(D) additional buffer blocks not available to the optimal algorithm. Both these algorithms are based on linear programming and hence are quite complicated and time consuming.…”

mentioning

confidence: 99%

Duality Between Prefetching and Queued Writing with Parallel Disks

Hutchinson¹,

Sanders²,

Vitter³

2005

SIAM J. Comput.

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Parallel disks promise to be a cost effective means for achieving high bandwidth in applications involving massive data sets, but algorithms for parallel disks can be difficult to devise. To combat this problem, we define a useful and natural duality between writing to parallel disks and the seemingly more difficult problem of prefetching. We first explore this duality for applications involving read-once accesses using parallel disks. We get a simple linear time algorithm for computing optimal prefetch schedules and analyze the efficiency of the resulting schedules for randomly placed data and for arbitrary interleaved accesses to striped sequences. Duality also provides an optimal schedule for prefetching plus caching, where blocks can be accessed multiple times. Another application of this duality gives us the first parallel disk sorting algorithms that are provably optimal up to lower-order terms. One of these algorithms is a simple and practical variant of multiway mergesort, addressing a question that had been open for some time.1. Introduction. External memory (EM) algorithms are those for which the problem data set is too large to fit into the high-speed random access memory (RAM) of a computer and therefore must reside on external devices such as disk drives [23]. In order to cope with the high latency of accessing data on disks, efficient EM algorithms exploit locality in their design. In the I/O model, EM algorithms access a large block of B contiguous data elements in one I/O step and perform the necessary algorithmic operations on the elements in the block while in the high-speed memory. The speedup can be significant. However, even with blocked access, a single disk provides much less bandwidth than the internal memory. This problem can be mitigated by using multiple disks in parallel. For each input/output operation, one block is transferred between a fast memory of size M and each of the D disks. The algorithm therefore transfers D blocks at the cost of a single-disk access delay.A simple approach to algorithm design for parallel disks is to employ large logical blocks, or superblocks, of size B · D in the algorithm. This reduces the problem to designing an EM algorithm for one disk with logical block size BD. A superblock is split into D physical blocks-one on each disk. All D physical blocks are accessed *

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“…As a result, the tall/small job scheduling problem and the prefetch/caching problem can be solved in worst case time O(n 3 ) improving over respectively O(n 10 ) [4] and O * (n 18 ) [2]. Implementations are available from the authors home-pages.…”

Section: Introductionmentioning

confidence: 99%

Finding Total Unimodularity in Optimization Problems Solved by Linear Programs

Dürr

Hurand

2009

Algorithmica

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A popular approach in combinatorial optimization is to model problems as integer linear programs. Ideally, the relaxed linear program would have only integer solutions, which happens for instance when the constraint matrix is totally unimodular. Still, sometimes it is possible to build an integer solution with the same cost from the fractional solution. Examples are two scheduling problems [4,6] and the single disk prefetching/caching problem [3]. We show that problems such as the three previously mentioned can be separated into two subproblems: (1) finding an optimal feasible set of slots, and (2) assigning the jobs or pages to the slots. It is straigthforward to show that the latter can be solved greedily. We are able to solve the former with a totally unimodular linear program, from which we obtain simple combinatorial algorithms with improved worst case running time.

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Integrated prefetching and caching in single and parallel disk systems

Cited by 7 publications

References 21 publications

The Performance Impact of Kernel Prefetching on Buffer Cache Replacement Algorithms

The Performance Impact of Kernel Prefetching on Buffer Cache Replacement Algorithms

Duality Between Prefetching and Queued Writing with Parallel Disks

Finding Total Unimodularity in Optimization Problems Solved by Linear Programs

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