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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
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9/18/2000 2 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 ?
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9/18/2000 3 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
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9/18/2000 4 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.
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9/18/2000 5 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
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9/18/2000 6 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”
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9/18/2000 7 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:
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9/18/2000 8 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:
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9/18/2000 9 The E-LEDF Algorithm E-LEDF: Extend-Low-energy Earliest Deadline First
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9/18/2000 10 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 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 Task SetConfigurationLEDFE-LEDF% increase 24 tasksts=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 39 tasksts=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 E-LEDF
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9/18/2000 11 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.
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