This paper develops a dynamically adaptive stochastic tunneling (DAST) algorithm to avoid the "freezing" problem commonly found when using simulated annealing for circuit placement on field-programmable gate arrays (FPGAs). The main objective is to reduce the placement runtime and improve the quality of final placement. We achieve this by allowing the DAST placer to tunnel energetically inaccessible regions of the potential solution space, adjusting the stochastic tunneling schedule adaptively by performing detrended fluctuation analysis, and selecting move types dynamically by a multi-modal scheme based on Gibbs sampling. A prototype annealing-based placer, called DAST, was developed as part of this paper. It targets the same computer-aide...
This thesis describes a parallel implementation of the timing-driven VPR 5.0 simulated-annealing pla...
imulated Annealing (SA) is a popular placement heuristic used in many commercial and academic FPGA ...
This work presents a new adaptation of the discrete particle swarm optimization method applied to th...
This paper develops a dynamically adaptive stochastic tunneling (DAST) algorithm to avoid the freez...
Placement is one of the most important steps in physical design for VLSI circuits. For field program...
Abstract – Current FPGA placement algorithms estimate the routability of a placement using architect...
To truly exploit FPGAs for rapid turn-around development and prototyping, placement times must be re...
In this paper we introduce a new Simulated Annealing-based timing-driven placement algorithm for FPG...
Current FPGA placement algorithms estimate the routability of a placement using architecture-specifi...
To truly exploit FPGAs for rapid turn-around development and prototyping, placement times must be re...
We present HeAP, an analytical placement algorithm for het-erogeneous FPGAs comprised of LUT-based l...
An FPGA has a finite routing capacity due to which a fair number of highly dense circuits fail to ma...
In recent years, the drastically enhanced architecture and capacity of Field-Programmable Gate Array...
Nowadays, placement problems become more complex since they need to consider standard cells, mixed s...
grantor: University of TorontoAs Field-Programmable Gate Array (FPGA) device capacities ha...
This thesis describes a parallel implementation of the timing-driven VPR 5.0 simulated-annealing pla...
imulated Annealing (SA) is a popular placement heuristic used in many commercial and academic FPGA ...
This work presents a new adaptation of the discrete particle swarm optimization method applied to th...
This paper develops a dynamically adaptive stochastic tunneling (DAST) algorithm to avoid the freez...
Placement is one of the most important steps in physical design for VLSI circuits. For field program...
Abstract – Current FPGA placement algorithms estimate the routability of a placement using architect...
To truly exploit FPGAs for rapid turn-around development and prototyping, placement times must be re...
In this paper we introduce a new Simulated Annealing-based timing-driven placement algorithm for FPG...
Current FPGA placement algorithms estimate the routability of a placement using architecture-specifi...
To truly exploit FPGAs for rapid turn-around development and prototyping, placement times must be re...
We present HeAP, an analytical placement algorithm for het-erogeneous FPGAs comprised of LUT-based l...
An FPGA has a finite routing capacity due to which a fair number of highly dense circuits fail to ma...
In recent years, the drastically enhanced architecture and capacity of Field-Programmable Gate Array...
Nowadays, placement problems become more complex since they need to consider standard cells, mixed s...
grantor: University of TorontoAs Field-Programmable Gate Array (FPGA) device capacities ha...
This thesis describes a parallel implementation of the timing-driven VPR 5.0 simulated-annealing pla...
imulated Annealing (SA) is a popular placement heuristic used in many commercial and academic FPGA ...
This work presents a new adaptation of the discrete particle swarm optimization method applied to th...