A greedy heuristic using adjoint functions for the optimization of seed and needle configurations in prostate seed implant

2007 ◽  
Vol 52 (3) ◽  
pp. 815-828 ◽  
Author(s):  
Sua Yoo ◽  
Michael E Kowalok ◽  
Bruce R Thomadsen ◽  
Douglass L Henderson
2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Nitish Das ◽  
P. Aruna Priya

The mathematical model for designing a complex digital system is a finite state machine (FSM). Applications such as digital signal processing (DSP) and built-in self-test (BIST) require specific operations to be performed only in the particular instances. Hence, the optimal synthesis of such systems requires a reconfigurable FSM. The objective of this paper is to create a framework for a reconfigurable FSM with input multiplexing and state-based input selection (Reconfigurable FSMIM-S) architecture. The Reconfigurable FSMIM-S architecture is constructed by combining the conventional FSMIM-S architecture and an optimized multiplexer bank (which defines the mode of operation). For this, the descriptions of a set of FSMs are taken for a particular application. The problem of obtaining the required optimized multiplexer bank is transformed into a weighted bipartite graph matching problem where the objective is to iteratively match the description of FSMs in the set with minimal cost. As a solution, an iterative greedy heuristic based Hungarian algorithm is proposed. The experimental results from MCNC FSM benchmarks demonstrate a significant speed improvement by 30.43% as compared with variation-based reconfigurable multiplexer bank (VRMUX) and by 9.14% in comparison with combination-based reconfigurable multiplexer bank (CRMUX) during field programmable gate array (FPGA) implementation.


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