In parallelizing simulated annealing in a multicomputer, maintaining the global state S involves explicit message traffic and is a critical performance bottleneck. One way to mitigate this bottleneck is to amortize the overhead of these state updates over as many parallel state changes as possible. Using this technique introduces errors in the calculated cost C(S) of a particular state S used by the annealing process. Analytically derived bounds are placed on this error in order to assure convergence to the correct result. The resulting parallel simulated annealing algorithm dynamically changes the frequency of global updates as a function of the annealing control parameter, i.e., temperature. Implementation results on the Intel iPSC/2 are ...
Several parallel parallel processing systems exist that can be partitioned and/or can operate in mul...
Current and future multicore architectures can significantly accelerate the performance of test auto...
We experimentally analyze some properties of simulated annealing algorithms (SA) and genetic algorit...
Simulated annealing is an attractive, but expensive, heuristic for approximating the solution to com...
This paper presents a cost error measurement scheme and relaxed synchronization method, for simulate...
Reducing synchronization constraints in parallel simulated annealing algorithms can improve performa...
A common approach to parallelizing simulated annealing to generate several perturbations to the cur...
This thesis describes a new, efficient, and general purpose parallel simulated annealing algorithm....
Variation in performance and power across manufactured parts and their operating conditions is an ac...
Simulated annealing has proven to be a good technique for solving hard combinatorial optimization p...
Simulated annealing (SA) is a stochastic optimization technique which guarantees under certain condi...
Custom integrated circuit design requires an ever increasing number of elements to be placed on a ph...
This paper introduces and analyzes a parallel method of simulated annealing. Borrowing from genetic ...
How can small-scale parallelism best be exploited in the solution of nonstiff initial value problems...
This thesis consists of two parts: performance bounds for scheduling algorithms for parallel progr...
Several parallel parallel processing systems exist that can be partitioned and/or can operate in mul...
Current and future multicore architectures can significantly accelerate the performance of test auto...
We experimentally analyze some properties of simulated annealing algorithms (SA) and genetic algorit...
Simulated annealing is an attractive, but expensive, heuristic for approximating the solution to com...
This paper presents a cost error measurement scheme and relaxed synchronization method, for simulate...
Reducing synchronization constraints in parallel simulated annealing algorithms can improve performa...
A common approach to parallelizing simulated annealing to generate several perturbations to the cur...
This thesis describes a new, efficient, and general purpose parallel simulated annealing algorithm....
Variation in performance and power across manufactured parts and their operating conditions is an ac...
Simulated annealing has proven to be a good technique for solving hard combinatorial optimization p...
Simulated annealing (SA) is a stochastic optimization technique which guarantees under certain condi...
Custom integrated circuit design requires an ever increasing number of elements to be placed on a ph...
This paper introduces and analyzes a parallel method of simulated annealing. Borrowing from genetic ...
How can small-scale parallelism best be exploited in the solution of nonstiff initial value problems...
This thesis consists of two parts: performance bounds for scheduling algorithms for parallel progr...
Several parallel parallel processing systems exist that can be partitioned and/or can operate in mul...
Current and future multicore architectures can significantly accelerate the performance of test auto...
We experimentally analyze some properties of simulated annealing algorithms (SA) and genetic algorit...