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175
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PVLDB
2008
182views more  PVLDB 2008»
15 years 4 months ago
SCOPE: easy and efficient parallel processing of massive data sets
Companies providing cloud-scale services have an increasing need to store and analyze massive data sets such as search logs and click streams. For cost and performance reasons, pr...
Ronnie Chaiken, Bob Jenkins, Per-Åke Larson,...
141
Voted
KDD
2005
ACM
170views Data Mining» more  KDD 2005»
16 years 5 months ago
Parallel mining of closed sequential patterns
Discovery of sequential patterns is an essential data mining task with broad applications. Among several variations of sequential patterns, closed sequential pattern is the most u...
Shengnan Cong, Jiawei Han, David A. Padua
ICFP
2007
ACM
16 years 4 months ago
Feedback directed implicit parallelism
In this paper we present an automated way of using spare CPU resources within a shared memory multi-processor or multi-core machine. Our approach is (i) to profile the execution o...
Tim Harris, Satnam Singh
ISPASS
2009
IEEE
15 years 11 months ago
Machine learning based online performance prediction for runtime parallelization and task scheduling
—With the emerging many-core paradigm, parallel programming must extend beyond its traditional realm of scientific applications. Converting existing sequential applications as w...
Jiangtian Li, Xiaosong Ma, Karan Singh, Martin Sch...
140
Voted
SIGCOMM
2009
ACM
15 years 11 months ago
Optimizing the BSD routing system for parallel processing
The routing architecture of the original 4.4BSD [3] kernel has been deployed successfully without major design modification for over 15 years. In the unified routing architectur...
Qing Li, Kip Macy