Title :
Variable voltage task scheduling algorithms for minimizing energy/power
Author :
Manzak, Ali ; Chakrabarti, Chaitali
Author_Institution :
Lattice Semicond. Corp., San Jose, CA, USA
fDate :
4/1/2003 12:00:00 AM
Abstract :
In this paper, we propose variable voltage task scheduling algorithms that minimize energy or minimize peak power for the case when the task arrival times, deadline times, execution times, periods, and switching activities are given. We consider aperiodic (earliest due date, earliest deadline first), as well as periodic (rate monotonic, earliest deadline first) scheduling algorithms. We use the Lagrange multiplier method to theoretically determine the relation between the task voltages such that the energy or peak power is minimum, and then develop an iterative algorithm that satisfies the relation. The asymptotic complexity of the existing scheduling algorithms change very mildly with the application of the proposed algorithms. We show experimentally (random experiments as well as real-life cases), that the voltage assignment obtained by the proposed low-complexity algorithm is very close to that of the optimal energy (0.1% error) and optimal peak power (1% error) assignment.
Keywords :
VLSI; circuit CAD; computational complexity; integrated circuit design; iterative methods; low-power electronics; minimisation; scheduling; Lagrange multiplier method; aperiodic scheduling algorithms; asymptotic complexity; deadline times; dynamic voltage scaling; energy minimization; execution times; iterative algorithm; low power; low-complexity algorithm; peak power minimization; periodic scheduling algorithms; switching activities; task arrival times; variable voltage task scheduling algorithms; voltage assignment; Dynamic voltage scaling; Energy consumption; Iterative algorithms; Job shop scheduling; Lagrangian functions; Measurement; Minimization methods; Processor scheduling; Scheduling algorithm; Threshold voltage;
Journal_Title :
Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
DOI :
10.1109/TVLSI.2003.810801