Optimal Routing-Conscious Dynamic Placement for Reconfigurable Devices

Ahmadinia, Ali; Bobda, Christophe; Fekete, Sándor P.; Teich, Jüergen; Veen, Jan C. van der

doi:10.1007/978-3-540-30117-2_87

Cited by 17 publications

(17 citation statements)

References 4 publications

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“…However, due to the presence of a configuration cache, the rF could switch very quickly (order of tens of clock cycles) between a limited number of CUs. Other approaches target devices that are quickly partially reconfigurable by examining online scheduling and placement techniques [6] [7]. Here, multiple CUs are scheduled dynamically onto the rF, possibly even observing quality-of-service constraints.…”

Section: Introductionmentioning

confidence: 99%

Configuration merging for adaptive computer applications

Kasprzyk

Veen

Koch

International Conference on Field Programmable Logic and Applications, 2005.

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We present experimental evidence that multiple compute-units, compiled from sequential high-level language input programs, can be merged into a reduced number of configurations for a reconfigurable fabric (such as a modern FPGA), thus significantly reducing the reconfiguration overhead. For cases requiring multiple configurations, both heuristical and exact algorithms to solve the configuration merging problem are described.

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Section: Introductionmentioning

confidence: 99%

Configuration merging for adaptive computer applications

Kasprzyk

Veen

Koch

International Conference on Field Programmable Logic and Applications, 2005.

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“…It requires run-time loadable modules that are typically pre-compiled and stored as bitstreams, which will then be used to reconfigure the device, i.e., allocate space for the subsequent execution the module. Several models and algorithms for on-line placement have been developed in the past, see e.g., [7,8,6]. However, these algorithms are limited by two main factors.…”

Section: Introductionmentioning

confidence: 99%

The Erlangen Slot Machine: A Dynamically Reconfigurable FPGA-based Computer

Majer

Teich

Ahmadinia³

et al. 2007

J VLSI Sign Process Syst Sign Image Video Technol

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Abstract. Computer architects have been studying the dynamically reconfigurable computer [1] for a number of years. New capabilities such as on-demand computing power, self-adaptiveness and self-optimization capabilities by restructuring the hardware on the fly at run-time is seen as a driving technology factor for current research initiatives such as autonomic [2,3] and organic computing [4,5]. Much research work is currently devoted to models for partial hardware module relocation [6] and dynamically reconfigurable hardware reconfiguration on e.g., FPGAbased platforms. However, there are many physical restrictions and technical problems limiting the scope or applicability of these approaches. This led us to the development of a new FPGA-based reconfigurable computer called the Erlangen Slot Machine. The architecture overcomes many architectural constraints of existing platforms and allows a user to partially reconfigure hardware modules arranged in so-called slots. The uniqueness of this computer stems from a) a new slot-oriented hardware architecture, b) a set of novel inter-module communication paradigms, and c) concepts for dynamic and partial reconfiguration management.

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“…One possible application for which the average distance is minimized is in the allocation of jobs to nodes in a supercomputer [1][2][3][4][5]. Another possible application is in VLSI layout, where the objective is to cluster nearby components of a circuit on a chip [6]. This class of problems is general enough to model physical problems, where one seeks the lowest-energy state of a set of particles having pairwise attractive or repulsive forces.…”

Section: Introductionmentioning

confidence: 99%

Optimal shape of a blob

Bender

2007

Journal of Mathematical Physics

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This paper presents the solution to the following optimization problem: What is the shape of the two-dimensional region that minimizes the average L p distance between all pairs of points if the area of this region is held fixed? [The L p distance between two points x = (x 1 , x 2 ) andVariational techniques are used to show that the boundary curve of the optimal region satisfies a nonlinear integral equation. The special case p = 2 is elementary and for this case the integral equation reduces to a differential equation whose solution is a circle. Two nontrivial special cases, p = 1 and p = ∞, have already been examined in the literature. For these two cases the integral equation reduces to nonlinear secondorder differential equations, one of which contains a quadratic nonlinearity and the other a cubic nonlinearity.

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Optimal Routing-Conscious Dynamic Placement for Reconfigurable Devices

Cited by 17 publications

References 4 publications

Configuration merging for adaptive computer applications

Configuration merging for adaptive computer applications

The Erlangen Slot Machine: A Dynamically Reconfigurable FPGA-based Computer

Optimal shape of a blob

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