subproject 3 large scale optimization participants cti, cuni, mpii, rwth, tu wroclaw, ucy, upb...
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Subproject 3
Large Scale Optimization
Participants
CTI, CUNI, MPII, RWTH, TU Wroclaw, UCY, UPB
presented by Burkhard Monien (UPB)
Burkhard Monien (UPB)
Large Scale OptimizationSubproject 3
Goals of SP3 „Large Scale Optimization“
Long term new approximation theory, methodological framework and software
implementations for large-scale optimization problems.Short term Identification of key problems, initial modellings, approximation
algorithms for large-scale optimization problems.
Approximation theory
Algorithms
Implementations
Documentation
Large-scale wired networks, network problems, wireless networks
Introduction
Burkhard Monien (UPB)
Large Scale OptimizationSubproject 3
Structure of SP3 „Large Scale Optimization“
WP 3.1Approximation Techniques forLarge-Scale Optimization
WP 3.2Optimization Methods
for Large-Scale Communication and
Transportation Networks and the Web
WP 3.3Foundations
Of WirelessNetworks
WP 3.4A Compendium of Large-Scale Optimization Problems
Introduction
Burkhard Monien (UPB)
Large Scale OptimizationSubproject 3
Publications
Total??? conference / journal papers, ??? reports under submission
Last 12 Month??? conference / journal papers, ??? reports under submission
Introduction
Burkhard Monien (UPB)
Large Scale OptimizationSubproject 3
Deliverables due at month 24
D3.1.3: Establishment of Basic Methodological Framework of Nonlinear Optimization Approaches for Large-Scale Optimization Problems
D3.2.2: Initial Modeling of Selected Problems for Communication/Transportation Networks
D3.3.3: Assessment of Developed Algorithmic Techniques
D3.4.3: Initial Experimental Studies of Selected Problems
Introduction
Burkhard Monien (UPB)
Large Scale OptimizationSubproject 3
External Memory (Meyer & Ajwani, MPII)
x
• main memory size << problem size• external memory = D disks• data is transferred in blocks of size B• up to D · B data per I/O operation• Goal: minimize number of I/O operations
scan(x) = O( x / (D · B) )sort(x) = O( x / (D · B) · logM/B (x/B) )
Burkhard Monien (UPB)
Large Scale OptimizationSubproject 3
External BFS — Motivation
Solving real world optimization problem often boils down to structured graph traversal
Crawling, analyzing the WWW Generalizations: Shortest Paths, A* Route planning using small navigation devices with
flash memory cards State space exploration
Burkhard Monien (UPB)
Large Scale OptimizationSubproject 3
External BFS — Experimental Study
A computational study of three BFS-algorithms from the literature
D. Ajwani, R. Dementiev, U. Meyer, SODA'05 (DELIS-TR-0276)
Internal-memory algorithm
Munagala, Ranade SODA'99
Mehlhorn, Meyer ESA'02