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Investigating the Effect of Voltage-Switching on Low-Energy Task Scheduling in Hard Real-Time Systems. Paper review Presented by Chung-Fu Kao. What’s the Problem ?. The relationship between voltage-switching and energy consumption.
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Investigating the Effect of Voltage-Switching on Low-Energy Task Scheduling in Hard Real-Time Systems Paper review Presented by Chung-Fu Kao
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 ?
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
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.
Preliminaries • A set of n periodic tasks • Notation: • Each task has the following parameters • A release (or arrival) time ai, • A deadline di, • A length li (# of instruction cycle), and • A period pi • CPU can operate at one of two voltage: v1 or v2, e.g. 1.3v or 2.5v
Preliminaries (contd.) • Each task ri may be executed at a voltage vi, • The system uses up C units of energy • The relation between power consumption and CPU voltage • Equation: • So, power (energy) consumption Ei consumed by task ri of length li is * * Reference “Logic Synthesis for Low Power VLSI Designs”
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 Ci • Goal:
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 ai, bi are binary variables • Goal:
The E-LEDF Algorithm • E-LEDF: Extend-Low-energy Earliest Deadline First
Task Set Task ti Configuration Release ai LEDF Deadline di E-LEDF Length li (x 106) % increase Li / 300 (x 106) Li / 400 (x 106) 24 tasks ts=5, vs=200 ts=5, vs=10 ts=1, vs=200 ts=1, vs=10 199418.76 213376.26 212236.26 201771.65 200631.65 6.99 6.42 1.17 0.60 t1 t2 t3 t4 3 9 0 18 7 21 5 25 800 750 1600 1000 2.66 2.5 5.33 3.33 2.0 1.875 4.0 2.5 39 tasks ts=5, vs=200 ts=5, vs=10 ts=1, vs=200 ts=1, vs=10 309338.65 380317.625 378987.625 345221.25 342751.25 22.90 22.50 11.59 10.80 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) E-LEDF
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.