A Competitive Strategy for Distance-Aware Online Shape Allocation

Fekete, Sándor P.; Schweer, Nils; Reinhardt, Jan-Marc

doi:10.1007/978-3-642-36065-7_6

Cited by 2 publications

(1 citation statement)

References 13 publications

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“…Particularly interesting for methods for online packing into a single container may be the work by Bansal et al [43], who show that for any complicated packing of rectangular items into a rectangular container, there is a simpler packing with almost the same value of items. For another variant of online allocation, see [44], which extends previous work on optimal shapes for allocation [45].…”

Section: Related Workmentioning

confidence: 72%

An efficient data structure for dynamic two-dimensional reconfiguration

Fekete

Reinhardt

Scheffer

2017

Journal of Systems Architecture

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In the presence of dynamic insertions and deletions into a partially reconfigurable FPGA, fragmentation is unavoidable. This poses the challenge of developing efficient approaches to dynamic defragmentation and reallocation. One key aspect is to develop efficient algorithms and data structures that exploit the two-dimensional geometry of a chip, instead of just one. We propose a new method for this task, based on the fractal structure of a quadtree, which allows dynamic segmentation of the chip area, along with dynamically adjusting the necessary communication infrastructure. We describe a number of algorithmic aspects, and present different solutions. We also provide a number of basic simulations that indicate that the theoretical worst-case bound may be pessimistic.

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Section: Related Workmentioning

confidence: 72%

An efficient data structure for dynamic two-dimensional reconfiguration

Fekete

Reinhardt

Scheffer

2017

Journal of Systems Architecture

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A competitive strategy for distance-aware online shape allocation

Fekete

Reinhardt

Schweer

2014

Theoretical Computer Science

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We consider the following online allocation problem: Given a unit square S, and a sequence of numbers n i ∈ {0, 1} with i j=0 n j ≤ 1; at each step i, select a region C i of previously unassigned area n i in S. The objective is to make these regions compact in a distance-aware sense: minimize the maximum (normalized) average Manhattan distance between points from the same set C i . Related location problems have received a considerable amount of attention; in particular, the problem of determining the "optimal shape of a city", i.e., allocating a single n i has been studied. We present an online strategy, based on an analysis of space-filling curves; for continuous shapes, we prove a factor of 1.8092, and 1.7848 for discrete point sets.

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A Competitive Strategy for Distance-Aware Online Shape Allocation

Cited by 2 publications

References 13 publications

An efficient data structure for dynamic two-dimensional reconfiguration

An efficient data structure for dynamic two-dimensional reconfiguration

A competitive strategy for distance-aware online shape allocation

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