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 compa...
Abstract:- The coordinated tuning of power system stabilizers (PSS) consists of an optimization prob...
This paper presents a novel approach to estimating and predicting the system-wide utilisation of com...
A compile-time prediction technique is outlined that yields approximate, yet low-cost, analytical pe...
In this paper, we describe our work to investigate how much cyclic graph based Genetic Programming (...
this paper we present a genetic algorithm that determines the schedule of an application and the top...
Three optimization methods derived from natural sciences are considered for allocating data to multi...
The programming complexity of increasingly parallel processors calls for new tools to assist program...
Synchronous Dataflow (SDF) is a widely-used model-of-computation for signal processing and multimedi...
Efficient multiprocessor task scheduling is a long-studied and difficult problem that continues to b...
Supercomputers have reached a massive energy consumption due to computational demand, so there is an...
The overarching goal of this thesis is to provide an algorithm-centric approach to analyzing the rel...
Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes...
A review of current computer performance and evaluation tech-niques reveals a lack of an acceptable ...
The development of a new graph theoretic model for describing the relation between a decomposed algo...
The paper presents the problems related to reduction of the duration of technical problems optimizat...
Abstract:- The coordinated tuning of power system stabilizers (PSS) consists of an optimization prob...
This paper presents a novel approach to estimating and predicting the system-wide utilisation of com...
A compile-time prediction technique is outlined that yields approximate, yet low-cost, analytical pe...
In this paper, we describe our work to investigate how much cyclic graph based Genetic Programming (...
this paper we present a genetic algorithm that determines the schedule of an application and the top...
Three optimization methods derived from natural sciences are considered for allocating data to multi...
The programming complexity of increasingly parallel processors calls for new tools to assist program...
Synchronous Dataflow (SDF) is a widely-used model-of-computation for signal processing and multimedi...
Efficient multiprocessor task scheduling is a long-studied and difficult problem that continues to b...
Supercomputers have reached a massive energy consumption due to computational demand, so there is an...
The overarching goal of this thesis is to provide an algorithm-centric approach to analyzing the rel...
Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes...
A review of current computer performance and evaluation tech-niques reveals a lack of an acceptable ...
The development of a new graph theoretic model for describing the relation between a decomposed algo...
The paper presents the problems related to reduction of the duration of technical problems optimizat...
Abstract:- The coordinated tuning of power system stabilizers (PSS) consists of an optimization prob...
This paper presents a novel approach to estimating and predicting the system-wide utilisation of com...
A compile-time prediction technique is outlined that yields approximate, yet low-cost, analytical pe...