Tom Kamphans

No-break dynamic defragmentation of reconfigurable devices

We propose a new method for defragmenting the module layout of a reconfigurable device, enabled by a novel approach for dealing with communication needs between relocated modules and with inhomogeneities found in commonly used FPGAs. Our method is based on dynamic relocation of module positions during runtime, with only very little reconfiguration overhead; the objective is to maximize the length of contiguous free space that is available for new modules. We describe a number of algorithmic aspects of good defragmentation, and present an optimization method based on tabu search. Experimental results indicate that we can improve the quality of module layout by roughly 50% over static layout. Among other benefits, this improvement avoids unnecessary rejection of modules.

An extended bioreaction database that significantly improves reconstruction and analysis of genome-scale metabolic networks

The bioreaction database established by Ma and Zeng (Bioinformatics, 2003, 19, 270-277) for in silico reconstruction of genome-scale metabolic networks has been widely used. Based on more recent information in the reference databases KEGG LIGAND and Brenda, we upgrade the bioreaction database in this work by almost doubling the number of reactions from 3565 to 6851. Over 70% of the reactions have been manually updated/revised in terms of reversibility, reactant pairs, currency metabolites and error correction. For the first time, 41 spontaneous sugar mutarotation reactions are introduced into the biochemical database. The upgrade significantly improves the reconstruction of genome scale metabolic networks. Many gaps or missing biochemical links can be recovered, as exemplified with three model organisms Homo sapiens, Aspergillus niger, and Escherichia coli. The topological parameters of the constructed networks were also largely affected, however, the overall network structure remains scale-free. Furthermore, we consider the problem of computing biologically feasible shortest paths in reconstructed metabolic networks. We show that these paths are hard to compute and present solutions to find such paths in networks of small and medium size.

Dynamic Defragmentation of Reconfigurable Devices

We propose a new method for defragmenting the module layout of a reconfigurable device, enabled by a novel approach for dealing with communication needs between relocated modules and with inhomogeneities found in commonly used FPGAs. Our method is based on dynamic relocation of module positions during runtime, with only very little reconfiguration overhead; the objective is to maximize the length of contiguous free space that is available for new modules. We describe a number of algorithmic aspects of good defragmentation, and present an optimization method based on tabu search. Experimental results indicate that we can improve the quality of module layout by roughly 50% over the static layout. Among other benefits, this improvement avoids unnecessary rejections of modules.

Online Square Packing

We analyze the problem of packing squares in an online fashion: Given a semi-infinite strip of width 1 and an unknown sequence of squares of side length in [0,1] that arrive from above, one at a time. The objective is to pack these items as they arrive, minimizing the resulting height. Just like in the classical game of Tetris, each square must be moved along a collision-free path to its final destination. In addition, we account for gravity in both motion and position. We apply a geometric analysis to establish a competitive factor of 3.5 for the bottom-left heuristic and present a

Exploring and triangulating a region by a swarm of robots

\frac{34}{13} \approx 2.6154

Hallway monitoring: distributed data processing with wireless sensor networks

-competitive algorithm.

Randolphs Robot Game is NP-hard!

We consider online and offline problems related to exploring and surveying a region by a swarm of robots with limited communication range. The minimum relay triangulation problem (MRTP) asks for placing a minimum number of robots, such that their communication graph is a triangulated cover of the region. The maximum area triangulation problem (MATP) aims at finding a placement of n robots such that their communication graph contains a root and forms a triangulated cover of a maximum possible amount of area. Both problems are geometric versions of natural graph optimization problems. The offline version of both problems share a decision problem, which we prove to be NP-hard. For the online version of the MRTP, we give a lower bound of 6/5 for the competitive ratio, and a strategy that achieves a ratio of 3; for different offline versions, we describe polynomial-time approximation schemes. For the MATP we show that no competitive ratio exists for the online problem, and give polynomial-time approximation schemes for offline versions.

ReCoNodes—Optimization Methods for Module Scheduling and Placement on Reconfigurable Hardware Devices

We present a sensor network testbed that monitors a hallway. It consists of 120 load sensors and 29 passive infrared sensors (PIRs), connected to 30 wireless sensor nodes. There are also 29 LEDs and speakers installed, operating as actuators, and enabling a direct interaction between the testbed and passers-by. Beyond that, the network is heterogeneous, consisting of three different circuit boards--each with its specific responsibility. The design of the load sensors is of extremely low cost compared to industrial solutions and easily transferred to other settings. The network is used for in-network data processing algorithms, offering possibilities to develop, for instance, distributed target-tracking algorithms. Special features of our installation are highly correlated sensor data and the availability of miscellaneous sensor types.

Virtual area management: Multitasking on dynamically partially reconfigurable devices

Abstract We introduce a new type of movement constraints for a swarm of robots in a grid environment inspired by Alex Randolphs board game Ricochet Robots . We assume that once a robot starts to drive in a certain direction, it does not stop its movement until it hits an obstacle wall or another robot. (This property can be used to model robots with very limited abilities for self-localization.) We show that the question whether a given cell can be reached is NP-hard for arbitrary environments. A Java applet for simulating robot swarms moving with these constraints can be found in http://www.geometrylab.de/RacingRobots/ .

Inspecting a Set of Strips Optimally

Placement and scheduling are recognized as the most important problems when exploiting the benefit of partially reconfigurable devices such as FPGAs. For example, dynamically loading and unloading modules onto an FPGA causes fragmentation, and—in turn—may decrease performance. To counteract this effect, we use methods from algorithmics and mathematical optimization to increase the performance and present algorithms for placing, scheduling, and defragmenting modules on FPGAs. Taking communication between modules into account, we further present strategies to minimize communication overhead. Finally, we consider scheduling module requests with time-varying resource demands.