Difference between revisions of "Open Problems:27"

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{{DISPLAYTITLE:Problem 27: Modeling of Distributed Computation}}
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{{Header
{{Infobox
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|title=Modeling of Distributed Computation
|label1 = Proposed by
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|source=kanpur09
|data1 = Paul Beame
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|who=Paul Beame
|label2 = Source
 
|data2 = [[Workshops:Kanpur_2009|Kanpur 2009]]
 
|label3 = Short link
 
|data3 = http://sublinear.info/27
 
 
}}
 
}}
 
MapReduce has recently inspired two distributed models of computation in the theory community. One is the MUD model of Feldman et al. {{cite|FeldmanMSSS-10}}. In this model they assume that every worker has at most a polylogarithmic amount of space available, which in total gives at most $\tilde O(n)$ space, where $n$ is the input size (in the order of at least terabytes). The other model of computation, due to Karloff et al. {{cite|KarloffSV-10}}, assumes that each of $n^{1-\epsilon}$ workers has at most $n^{1-\epsilon}$ space, where $\epsilon$ is a fixed positive constant. This totals to $n^{2-2\epsilon}$ space in the entire system. Can one design an interesting and practical model that only uses $n^{1+o(1)}$ space/resources?
 
MapReduce has recently inspired two distributed models of computation in the theory community. One is the MUD model of Feldman et al. {{cite|FeldmanMSSS-10}}. In this model they assume that every worker has at most a polylogarithmic amount of space available, which in total gives at most $\tilde O(n)$ space, where $n$ is the input size (in the order of at least terabytes). The other model of computation, due to Karloff et al. {{cite|KarloffSV-10}}, assumes that each of $n^{1-\epsilon}$ workers has at most $n^{1-\epsilon}$ space, where $\epsilon$ is a fixed positive constant. This totals to $n^{2-2\epsilon}$ space in the entire system. Can one design an interesting and practical model that only uses $n^{1+o(1)}$ space/resources?

Revision as of 05:22, 16 November 2012

Suggested by Paul Beame
Source Kanpur 2009
Short link https://sublinear.info/27

MapReduce has recently inspired two distributed models of computation in the theory community. One is the MUD model of Feldman et al. [FeldmanMSSS-10]. In this model they assume that every worker has at most a polylogarithmic amount of space available, which in total gives at most $\tilde O(n)$ space, where $n$ is the input size (in the order of at least terabytes). The other model of computation, due to Karloff et al. [KarloffSV-10], assumes that each of $n^{1-\epsilon}$ workers has at most $n^{1-\epsilon}$ space, where $\epsilon$ is a fixed positive constant. This totals to $n^{2-2\epsilon}$ space in the entire system. Can one design an interesting and practical model that only uses $n^{1+o(1)}$ space/resources?