Simulated annealing based standard cell placement for VLSI designs has long been acknowledged as a compute-intensive process, and as a result several research efforts have been undertaken to parallelize this algorithm. Most previous parallel approaches to cell placement annealing have used a parallel moves approach. In this paper we investigate two new approaches that have been proposed for generalized parallel simulated annealing but have not been applied to the cell placement problem. Results are presented on the effectiveness of implementations of these algorithms when applied to the cell placement problem. We find that the first, multiple Markov chains, appears to be promising since it uses parallelism to obtain near linear speedups wit...
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 ...
Simulated annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinator...
As modern VLSI designs have become larger and more complicated, the computational requirements for d...
Abstract-Parallel algorithms with quality equivalent to the simu-lated annealing placement algorithm...
Simulated annealing is a general purpose Monte Carlo optimization technique that was applied to the ...
Simulated annealing based standard cell placement for VLSI designs has long been acknowledged as a c...
Abstract Simulated Evolution (SimE) is an evolutionary metaheuristic that has pro-duced results comp...
We introduce the new optimization method of Simulated Evolution (SE), which is designed to find near...
Simulated Annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinator...
Simulated evolution (SimE) is an evolutionary metaheuristic that has produced results comparable to ...
Abstract- Simulated Annealing (SA) is a popular iterative heuristic used to solve a wide variety of ...
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 ...
Simulated annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinator...
As modern VLSI designs have become larger and more complicated, the computational requirements for d...
Abstract-Parallel algorithms with quality equivalent to the simu-lated annealing placement algorithm...
Simulated annealing is a general purpose Monte Carlo optimization technique that was applied to the ...
Simulated annealing based standard cell placement for VLSI designs has long been acknowledged as a c...
Abstract Simulated Evolution (SimE) is an evolutionary metaheuristic that has pro-duced results comp...
We introduce the new optimization method of Simulated Evolution (SE), which is designed to find near...
Simulated Annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinator...
Simulated evolution (SimE) is an evolutionary metaheuristic that has produced results comparable to ...
Abstract- Simulated Annealing (SA) is a popular iterative heuristic used to solve a wide variety of ...
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 ...
Simulated annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinator...