PSG College of Technology

About: PSG College of Technology is a based out in . It is known for research contribution in the topics: Machining & Thin film. The organization has 3174 authors who have published 3575 publications receiving 40690 citations.

A novel framework for applying multiobjective GA and PSO based approaches for simultaneous area, delay, and power optimization in high level synthesis of datapaths

Abstract: High-Level Synthesis deals with the translation of algorithmic descriptions into an RTL implementation. It is highly multiobjective in nature, necessitating trade-offs between mutually conflicting objectives such as area, power and delay. Thus design space exploration is integral to the High Level Synthesis process for early assessment of the impact of these trade-offs. We propose a methodology for multi-objective optimization of Area, Power and Delay during High Level Synthesis of data paths from Data Flow Graphs (DFGs). The technique performs scheduling and allocation of functional units and registers concurrently. A novel metric based technique is incorporated into the algorithm to estimate the likelihood of a schedule to yield low-power solutions. A truemulti-objective evolutionary technique, "Nondominated Sorting Genetic Algorithm II" (NSGA II) is used in this work. Results on standard DFG benchmarks indicate that the NSGA II based approach is much faster than a weighted sum GA approach. It also yields superior solutions in terms of diversity and closeness to the true Pareto front. In addition a framework for applying another evolutionary technique: Weighted Sum Particle Swarm Optimization (WSPSO) is also reported. It is observed that compared to WSGA, WSPSO shows considerable improvement in execution time with comparable solution quality.

On the single server batch arrival retrial queue with general vacation time under bernoulli schedule and two phases of heterogeneous service

Abstract: We consider a single server retrial queue with batch arrivals, two phases of heterogeneous service and a general vacation time under Bernoulli schedule. We carry out steady state system size distribution of number of customers in retrial group, expected number of customers in retrial group and expected waiting time of the customers in the orbit. We discuss its application of the proposed model to the analysis of a communication protocol.