Results

**1 - 2**of**2**### A Joint Power/Performance Optimization Algorithm for Multiprocessor Systems using a Period Graph Construct

"... A critical challenge in synthesis techniques for iterative applications is the efficient analysis of performance in the presence of communication resource contention. To address this challenge, we introduce the concept of the period graph. The period graph is constructed from the output of a simulat ..."

Abstract
- Add to MetaCart

(Show Context)
A critical challenge in synthesis techniques for iterative applications is the efficient analysis of performance in the presence of communication resource contention. To address this challenge, we introduce the concept of the period graph. The period graph is constructed from the output of a simulation of the system, with idle states included in the graph, and its maximum cycle mean is used to estimate overall system throughput. As an example of the utility of the period graph, we demonstrate its use in a joint power/performance optimization solution that uses either a nested genetic algorithm, or a simulated annealing algorithm. We analyze the fidelity of this estimator, and quantify the speedup and optimization accuracy obtained compared to simulation. 1

### A Joint Power/Performance Optimization Algorithm for Multiprocessor Systems using a Period Graph ConstructAbstract

"... A critical challenge in synthesis techniques for itera-tive applications is the efficient analysis of performance in the presence of communication resource contention. To address this challenge, we introduce the concept of the period graph. The period graph is constructed from the out-put of a simul ..."

Abstract
- Add to MetaCart

(Show Context)
A critical challenge in synthesis techniques for itera-tive applications is the efficient analysis of performance in the presence of communication resource contention. To address this challenge, we introduce the concept of the period graph. The period graph is constructed from the out-put of a simulation of the system, with idle states included in the graph, and its maximum cycle mean is used to esti-mate overall system throughput. As an example of the utility of the period graph, we demonstrate its use in a joint power/performance optimization solution that uses either a nested genetic algorithm, or a simulated annealing algo-rithm. We analyze the fidelity of this estimator, and quantify the speedup and optimization accuracy obtained compared to simulation. 1