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IPPS
2005
IEEE
15 years 3 months ago
Reducing Power with Performance Constraints for Parallel Sparse Applications
Sparse and irregular computations constitute a large fraction of applications in the data-intensive scientific domain. While every effort is made to balance the computational wor...
Guangyu Chen, Konrad Malkowski, Mahmut T. Kandemir...
ICDT
2001
ACM
147views Database» more  ICDT 2001»
15 years 2 months ago
Parallelizing the Data Cube
This paper presents a general methodology for the efficient parallelization of existing data cube construction algorithms. We describe two different partitioning strategies, one f...
Frank K. H. A. Dehne, Todd Eavis, Susanne E. Hambr...
CF
2009
ACM
15 years 4 months ago
Space-and-time efficient garbage collectors for parallel systems
As multithreaded server applications and runtime systems prevail, garbage collection is becoming an essential feature to support high performance systems. The fundamental issue of...
Shaoshan Liu, Ligang Wang, Xiao-Feng Li, Jean-Luc ...
HPDC
2007
IEEE
15 years 4 months ago
A fast topology inference: a building block for network-aware parallel processing
Adapting to the network is the key to achieving high performance for communication-intensive applications, including scientific computing, data intensive computing, and multicast...
Tatsuya Shirai, Hideo Saito, Kenjiro Taura
CCO
2001
Springer
161views Combinatorics» more  CCO 2001»
15 years 2 months ago
Branch, Cut, and Price: Sequential and Parallel
Branch, cut, and price (BCP) is an LP-based branch and bound technique for solving large-scale discrete optimization problems (DOPs). In BCP, both cuts and variables can be generat...
Laszlo Ladányi, Ted K. Ralphs, Leslie E. Tr...