Abstract- Simulated Annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinatorial optimization problems. However, depending on the size of the problem,it may have large run-time requirements. One practical approach to speed up its execution is to parallelize it. In this paper we develop parallel SA schemes based on the Asynchronous Multiple-Markov Chain model (AMMC) described in [1] and applied to standard-cell placement in [2]. The schemes are applied to solve the multi-objective standard cell placement problem using an inexpensive cluster-of-workstations environment. This problem requires the optimization of conflicting objectives (interconnect wire-length, power dissipation, and timing performance), and Fu...
Simulated annealing is a general purpose Monte Carlo optimization technique that was applied to the ...
Simulated Evolution (SimE) is an evolutionary metaheuristic that has produced results comparable to ...
Simulated annealing based standard cell placement for VLSI designs has long been acknowledged as a c...
Simulated Annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinator...
Simulated annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinator...
Simulated Annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinator...
Simulated Annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinator...
Simulated Evolution (SimE) is a sound stochastic approximation algorithm based on the principles of ...
As modern VLSI designs have become larger and more complicated, the computational requirements for d...
Simulated annealing based standard cell placement for VLSI designs has long been acknowledged as a c...
Abstract-Parallel algorithms with quality equivalent to the simu-lated annealing placement algorithm...
Abstract — Simulated Evolution (SimE) is a sound stochastic approximation algorithm based on the pri...
Simulated annealing is a general purpose Monte Carlo optimization technique that was applied to the ...
Simulated Evolution (SimE) is an evolutionary metaheuristic that has produced results comparable to ...
Simulated annealing based standard cell placement for VLSI designs has long been acknowledged as a c...
Simulated Annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinator...
Simulated annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinator...
Simulated Annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinator...
Simulated Annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinator...
Simulated Evolution (SimE) is a sound stochastic approximation algorithm based on the principles of ...
As modern VLSI designs have become larger and more complicated, the computational requirements for d...
Simulated annealing based standard cell placement for VLSI designs has long been acknowledged as a c...
Abstract-Parallel algorithms with quality equivalent to the simu-lated annealing placement algorithm...
Abstract — Simulated Evolution (SimE) is a sound stochastic approximation algorithm based on the pri...
Simulated annealing is a general purpose Monte Carlo optimization technique that was applied to the ...
Simulated Evolution (SimE) is an evolutionary metaheuristic that has produced results comparable to ...
Simulated annealing based standard cell placement for VLSI designs has long been acknowledged as a c...