In this paper we show how PRAM algorithms can be turned into efficient streaming algorithms for several classical combinatorial problems in the W-Stream model. In this model, at each pass one input stream is read and one output stream is written; streams are pipelined in such a way that the output stream produced at pass i is given as input stream at pass i +1. Our techniques yield near-optimal algorithms (up to polylog factors) for several classical problems in this model including sorting, connectivity, minimum spanning tree, biconnected components, and maximal independent set.ou
Thesis (Ph. D.)--University of Rochester. Dept. of Mathematics, 2008.The algorithmic field of Data S...
Streaming algorithms must process a large quantity of small updates quickly to allow queries about t...
For many algorithmic problems, traditional algorithms that optimise on the number of instructions ex...
In this paper we show how parallel algorithms can be turned into efficient streaming algorithms for ...
AbstractIn this paper we show how parallel algorithms can be turned into efficient streaming algorit...
In this paper we show how parallel algorithms can be turned into efficient streaming algorithms for ...
Abstract. In this paper we show how parallel algorithms can be turned into efficient streaming algor...
The need to deal with massive data sets in many practical applications has led to a growing interest...
Streaming algorithms, which process very large datasets received one update at a time, are a key too...
This electronic version was submitted by the student author. The certified thesis is available in th...
AbstractThis paper presents results which improve the efficiency of parallel algorithms for computin...
The field of streaming algorithms has enjoyed a deal of focus from the theoretical computer science ...
The PRAM is a shared memory model of parallel computation which abstracts away from inessential engi...
Over the last few years, there has been considerable amount of study and work on developing algorith...
AbstractWe consider the Block PRAM model of Aggarwal et al. (in "Proceedings, First Annual ACM Sympo...
Thesis (Ph. D.)--University of Rochester. Dept. of Mathematics, 2008.The algorithmic field of Data S...
Streaming algorithms must process a large quantity of small updates quickly to allow queries about t...
For many algorithmic problems, traditional algorithms that optimise on the number of instructions ex...
In this paper we show how parallel algorithms can be turned into efficient streaming algorithms for ...
AbstractIn this paper we show how parallel algorithms can be turned into efficient streaming algorit...
In this paper we show how parallel algorithms can be turned into efficient streaming algorithms for ...
Abstract. In this paper we show how parallel algorithms can be turned into efficient streaming algor...
The need to deal with massive data sets in many practical applications has led to a growing interest...
Streaming algorithms, which process very large datasets received one update at a time, are a key too...
This electronic version was submitted by the student author. The certified thesis is available in th...
AbstractThis paper presents results which improve the efficiency of parallel algorithms for computin...
The field of streaming algorithms has enjoyed a deal of focus from the theoretical computer science ...
The PRAM is a shared memory model of parallel computation which abstracts away from inessential engi...
Over the last few years, there has been considerable amount of study and work on developing algorith...
AbstractWe consider the Block PRAM model of Aggarwal et al. (in "Proceedings, First Annual ACM Sympo...
Thesis (Ph. D.)--University of Rochester. Dept. of Mathematics, 2008.The algorithmic field of Data S...
Streaming algorithms must process a large quantity of small updates quickly to allow queries about t...
For many algorithmic problems, traditional algorithms that optimise on the number of instructions ex...