Investigating the Effect of Voltage- Switching on Low-Energy Task Scheduling in Hard Real-Time Systems Paper review Presented by Chung-Fu Kao

9/18/ What’s the Problem ?  The relationship between voltage-switching and energy consumption.  Switching times have a significant effect on the energy consumed in hard real-time systems.  How to reduce the voltage switching time ?

9/18/ Introduction  Energy consumption is becoming an important design parameter for portable and embedded systems. – Battery cost  One approach to conserve energy is to employ low-power design methodology.  Scheduling algorithm is proposed. – To minimize the energy consumed by a periodic task set

9/18/ Idea & Assumption  The algorithm is based on “earliest-deadline- first (EDF)” algorithm.  The voltage of the CPU may be switched between two or more values dynamically at run-time through OS system call.  Voltage switching takes time and consumes energy.  Find the minimum voltage of entire set of tasks.

9/18/ Preliminaries  A set of n periodic tasks – Notation:  Each task has the following parameters – A release (or arrival) time a i, – A deadline d i, – A length l i (# of instruction cycle), and – A period p i  CPU can operate at one of two voltage: v1 or v2, e.g. 1.3v or 2.5v

9/18/ Preliminaries (contd.)  Each task r i may be executed at a voltage v i,  The system uses up C units of energy  The relation between power consumption and CPU voltage – Equation:  So, power (energy) consumption E i consumed by task r i of length l i is * * Reference “Logic Synthesis for Low Power VLSI Designs”

9/18/ MILP Goal  MILP: Mixed-Integer Linear Programming  Minimize a linear objective function on a set of integer and/or real variables, while satisfying a set of linear constraints  Task set – A release time – A deadline – A length – An operating voltage – A corresponding execution speed – A cost to switch C i  Goal:

9/18/ MILP Method  Assume a linear relationship between the operating voltage v and its execution speed x  The execution speed of task i, to be either s1 or s2 (CPU speed), and a i, b i are binary variables  Goal:

9/18/ The E-LEDF Algorithm  E-LEDF: Extend-Low-energy Earliest Deadline First

9/18/ Experimental Results  Assume that the two processor speeds to be 300 MIPS at 2.47V and 400MIPS at 3.3V  Assume that the switching time is 0.4 units(milliseconds) and switching power is 50 units(mW) Task ti Release ai Deadline di Length li (x 10 6 ) Li / 300 (x 10 6 ) Li / 400 (x 10 6 ) t1 t2 t3 t Task SetConfigurationLEDFE-LEDF% increase 24 tasksts=5, vs=200 ts=5, vs=10 ts=1, vs=200 ts=1, vs= tasksts=5, vs=200 ts=5, vs=10 ts=1, vs=200 ts=1, vs= E-LEDF

9/18/ Conclusions  Energy consumption is becoming an increasingly important design issue.  The need for algorithms that attempt to minimize energy usage both at the system synthesis/design level, as well as the run-time/ operating system level are being increasingly felt.