1 EE5900 Advanced Embedded System For Smart Infrastructure Energy Efficient Scheduling

Energy consumption is an important issue in embedded systems. –Mobile and portable devices. –Laptops, PDAs. –Mobile and Intelligent systems: Digital camcorders, cellular phones, and portable medical devices. A typical networked embedded system consists of –Computing subsystem - driven by an embedded processor operated by a RTOS. –Communication subsystem - consists of a radio chipset driven by a firmware. Micorprocessor, Digital Signal Processor (DSP) Radio, RF amplifiers, A-to-D & D-to-A ckts A typical Embedded System Battery Computing Subsystem (Driven by RTOS) Communication Subsystem (Driven by Firmware) Introduction 2

3 Important Facts (1) High performance is needed only for a small fraction of time, while for the rest of time, a low- performance, a low-power processor would suffice. Time Work load Peak Computing Rate is needed Average rate would suffice

4 Important Facts (2) Processors are based on CMOS technology where dynamic power is the bottleneck Dynamic power (due to switching activity) P α V 2. f V α f V: voltage; P: power; E: Energy E = P * Tcc Tcc = CC/f E i = K.cc i. f 2 Where Tcc : execution time; CC i : # clock cycles of task T i. f : frequency at which T i is run.

5 Variable Voltage Processors Modern processors operate at multiple frequency levels. –Crusoe Processor: Transmeta Corporation –PowerNow! Technology: AMD –Intel XScale: Intel Higher the frequency level higher the energy consumption

6 Crusoe processor What is the power consumption of a Crusoe processor? [1] The extremely low power consumption delivered on multimedia applications is due to a new feature called LongRun power management. LongRun has the distinct ability to analyze the application workload dynamically and to adjust continuously the processor's speed (MHz) and voltage to provide the necessary performance. This new feature promises to extend the battery life of all applications, most specifically those requiring the constant attention of the processor. This is a dramatic departure from today's ultra-light PCs, which are incapable of delivering over one and a half or two hours of runtime for DVD movies.

7 Dynamic Voltage Scaling (DVS) DVS scales the operating voltage of the processor along with the frequency. Since energy is proportional to f 2, DVS can potentially provide significant energy savings through frequency and voltage scaling.

Case study (iPhone 5) iPhone 5’s power management system 8 Battery 3.8V Wh 1440mAh Computation System (operated by RTOS) Multiprocessor (A6) Computation System (operated by Firmware) Power management ICs DC/DC down converter LDO (Low Drop Out) Memories RF ModemPower amplifier Why we need these? Internal elements needs various types of voltages. -. DC/DC converter provides large capacity power. -. LDO provides small capacity power.

Case study (smart phones) Practical multi-core processors Contemporary multi-core processors have more than 2 cores at about 1 GHz. 9 Device Chip maker Processor name Frequency # cores iPhone 5AppleA61.02GHz2 Galaxy S IIISamsung Exynos GHz4 Motorola RAZR Ti OMAP GHz2 HTC one S Qualcomm MSM8260A 1.2GHz2 Asus transformer NVIDIATegra 31.3GHz4 New iPadAppleA5X1 GHz2

10 Simple DVS-Scheme DVS Next task Over loaded Under loaded f = F/2 f = F Task queue system

11 DVS-example Consider a task with a computation time 20 units. Energy of T i without DVS: –E1 = K * 20 * F 2. Energy of T i with DVS: –E2 = K * 20 * (F/2) 2. Clearly, E2 = (E1)/4 Time taken = t1 (say) Time taken = t2 = 2 * t1 Therefore, if we reduce the frequency we save energy but, we spend more time in performing the same computation

12 Energy-Time Tradeoffs Time Energy Savings

13 Simple DVS scheme handling RT-task Consider a real-time task T1 = (20, 30) Applying the simple DVS scheme –T1 runs at maximum frequency (F) and meets the deadline with no energy savings –T1 runs at half the maximum frequency (F/2) and completes at time = 40 thereby missing its deadline

14 Simple DVS scheme handling RT-task Frequency F 2030 time Frequency F 20 F/2 40time No DVS DVS: Low workload Inference: DVS cannot be blindly applied to real-time embedded systems

15 Energy aware scheduling in RT Systems  Objectives  Minimizing energy consumption  Meeting the deadlines

16 Real Time - DVS schemes  The RT-DVS algorithms can be broadly classified based on the granularity at which voltage scheduling is performed as follows T1T1 T2 T3  Inter-task DVS scheme: Voltage scheduling is done on a task by task basis.  Intra-task DVS scheme: Voltage scheduling is done within a task boundary T1…T1… T2… …T 1 T3 …T2 Voltage scheduling points

17 Inter-task EDF Static voltage scaling EDF Cycle conserving RT-DVS

18 Static Voltage Scaling EDF: Motivation wc1wc2wc3wc4 Holes in the pre-run schedule imply: EDF Test: ∑(wc i /p i ) < 1 at frequency = F max In other words, whenever ∑(wc i /p i ) < 1 there are holes in the EDF schedule Next arrival of T1 Pre-run schedule with holes WC i = worst case computation F max

19 Static Voltage Scaling EDF: exploiting holes wc1wc2wc3wc4 Next arrival of T1 Pre-run schedule with holes WC i = worst case computation F max Processor typically idles during holes. Instead, the holes can be exploited to slowdown the processor to save energy

20 Static Voltage Scaling EDF wc1wc2wc3wc4 K*wc1K *wc2K * wc3K * wc4 EDF Test: ∑(wc i /p i ) < 1 at maximum frequency = F max Static-VS EDF Test: K* [∑(wc i /p i )] = 1 at frequency = F max /K Next arrival of T1

21 Static voltage scaling: Example Task set: T1 = (1, 4) and T2 = (2, 8) U = 1/4 + 2/8 = 0.5 (< F max What is the “k” at which the task set is still (F max / k): –Let K = x –U = (1*x)/4 + (2*x)/8 = x*(0.5) = 1 –X = 2, that is k = 2 –Therefore, we can operate at f = F max / 2 and still meet the deadlines

22 Static voltage scaling: Example Task set: T1 = (1, 4) and T2 = (2, 8) U = 1/4 + 2/8 = 0.5 (< Fmax Frequency FmFm Time Finding the right frequency scaling parameter (say, k) U = (1*k)/4 + (2*k)/8 = 0.5*k = (F max /k) This gives, k = 2. Therefore, operating frequency = F max /2

23 Static voltage scaling: Example Modified Task (Fmax/2): T1 = (2, 4) and T2 = (4, 8) U = 2/4 + 4/8 = (Fmax/2) Frequency FmFm Time Frequency FmFm Time F m / 2 Energy consumption: 1*F^2 + 2*F^2 = 3F^2 Energy consumption: 1*(F/2)^2 + 2*(F/2)^2 = (¾)F^2

24 What if C i < WC i ? K*c1K *c2K * c3K * c4 Next arrival of T1 More holes left unexploited Actual computation time

25 What if C i < WC i ? K*c1K *wc2K * wc3K * wc4 Next arrival of T1 Actual computation time Task T1 completes Slow down all these tasks proportionally Hole of size = (wc1 – c1)

26 What if C i < WC i ? (contd..) K*c1 K’ *wc2K’ * wc3K’ * wc4 Next arrival of T1 CPU Cycles are conserved by slowing down the remaining tasks

27 Cycle conserving EDF: Example Task set: T1 = (3, 6) and T2 = (6, 12) U = 3/6 + 6/12 = F max What is the “k” at which the task set is still (F max / k): –Let K = x –U = (3*x)/6 + (6*x)/12 = x*(1.0) = 1 –X = 1, that is k = 1 –Therefore, we should operate at f = F max in order to meet all the deadlines

28 Cycle conserving EDF: Example Task (Fmax): T1 = (3,6) and T2 = (6,12) U = 3/6 + 6/12 = (Fmax) T Frequency FmFm Time T2T1 12 T Frequency FmFm Time T2T1 12 Task T1 just completes in one unit creating holes

29 Cycle conserving EDF: Example Task (Fmax): T1 = (3,6) and T2 = (6,12) U = 3/6 + 6/12 = (Fmax) T Frequency FmFm Time T2 12 New utilization = 1/6 + 6/12 = 0.67 Finding the right “k” 1/6 + (6*k)/12 = 1 K = 5/3 New freq = (3/5) Fmax T Frequency FmFm Time T2T1 12 Task T1 just completes in one unit creating holes

30 Intra Task Energy Management Intra-task DVS: adjusts the voltage and clock speed within a task. Identifies the slack time generated within a task due to workload variation. Application code is preprocessed to enable the run-time clock/voltage adjustment.

31 Different paths P1: B1, B2. P2: B1, B3, B4. P3: B1, B3, B5. B2 Intra-task DVS B1 B3 B4 B5 Deadline = 200 Voltage scheduling points Intra-task RT-DVS Intra-task DVS algorithms typically work with the control flow graph (CFG) of the real-time programs. Each node in the CFG denotes a basic block of computation. The edges in the CFG indicate the control dependency between the blocks. Objective is to assign proper clock frequency to each of the basic blocks so as to minimize the total energy consumption while meeting the task deadline.

32 Simple Intra-task DVS: example B B1 B3 Deadline = 40 Fmax 40 Fmax At time = 20, We know the exact branch 30

33 Simple Intra-task DVS: example B B1 B3 Deadline = 40 Fmax Fmax At time = 20, We know the exact branch

34 Different paths P1: B1, B2. P2: B1, B3, B4. P3: B1, B3, B5. B2 Worst Case Execution Time (WCET) based scheme B1 B3 B4 B5 Deadline = 200 [150][10] [160] [20] [180] F1 =[ 180/(200 – t) * Fm] F3 =[ 160/(200 – t) * Fm]F2 =[ 20/(200 – t) * Fm] F5 =[ 150/(200 – t)* Fm] F4 =[ 10/(200 – t)* Fm] t = current time

35 Summary DVS schemes can significantly reduce energy in embedded systems.