Cut Power Consumption by 5x Without Losing Performance

Transcription

1 Cut Power Consumption by 5x Without Losing Performance A big.little Software Strategy Klaas van Gend FAE, Trainer & Consultant

2 The mandatory Klaas-in-a-Plane picture 2 October 10, 2014 LINUXCON EUROPE 2014

3 Quad Core vs. Dual Core Why isn t it Twice as Fast? VS 3 October 10, 2014 LINUXCON EUROPE 2014

4 The GHz race 4 October 10, 2014 LINUXCON EUROPE 2014

5 Why GHz++ cost power^2 5 October 10, 2014 LINUXCON EUROPE 2014

6 ARM big.little OK, heavy work costs power. Let s not waste power on light work

7 ARM playing it cool: big.little Source: 7 October 10, 2014 LINUXCON EUROPE 2014

8 A7 vs A15 Cortex A7: Less silicon area Less optimal cycles Less cycles/second More power efficient 8 October 10, 2014 LINUXCON EUROPE 2014

9 How to use big.little today Source: 9 October 10, 2014 LINUXCON EUROPE 2014

10 Some available big.little hardware AllWinner A80 Renesas automotive silicon Samsung Galaxy S4 for South-Korean market Samsung Galaxy S5 for South-Korean market Hardkernel ODROID-XU board Exynos5 Built-in Power Measurement 10 October 10, 2014 LINUXCON EUROPE 2014

11 Use Case: Chromium

12 Chrome / Chromium / ChromeShell Chromium: Google Chrome: open source browser based on KHTML Webkit Blink closed-source browser based on Chromium ChromeShell: open source Chromium browser for Android Chrome for Android:closed-source browser for Android 12 October 10, 2014 LINUXCON EUROPE 2014

13 Chromium workload Visualized Loading Parsing Layouting/Rendering Painting JavaScript Canvas 13 October 10, 2014 LINUXCON EUROPE 2014

14 HTML5 Canvas graphics device for JavaScript 14 October 10, 2014 LINUXCON EUROPE 2014

15 HTML5 Canvas graphics device for JavaScript 15 October 10, 2014 LINUXCON EUROPE 2014

16 Parallelizing Canvas not as easy as it looks 16 October 10, 2014 LINUXCON EUROPE 2014

17 Canvas Parallelization - Performance Results Benchmark on quad-core Standard Blink Parallelized Blink Flashcanvas perf 1,69 score 2,44 score 44% Fc perf w/ alpha 1,04 score 1,52 score 50% Guimark2 Vector 9,5 fps 13,3 fps 40% Canvasmark score 4116 score 53% Average improvement 47% Performance improvement With parallelism you can improve performance of even the most complex applications! 17 October 10, 2014 LINUXCON EUROPE 2014

18 Google Chrome 18 October 10, 2014 LINUXCON EUROPE 2014

19 Google Chrome on Odroid-XU+E Using Google s Chome (version 33 for Android) 2 cores active: 54% and 84% Power use A15+A7 cores: Watts Test average: 9.44 fps 19 October 10, 2014 LINUXCON EUROPE 2014

20 Our ChromeShell on Odroid-XU+E Using our optimized ChromeShell: 3 A15 cores active: 59%, 63% and 38% Power use A15+A7 cores: Watts Test average: around 14 fps 20 October 10, 2014 LINUXCON EUROPE 2014

21 Canvas Parallelization - works even on normal silicon like Qualcomm Snapdragon 800 Default Chrome Average: 7.12 fps Our ChromeShell: Average: fps LG s NEXUS 5 phone Quad core Qualcomm Snapdragon 800 Phone heating up similarly in both cases 21 October 10, 2014 LINUXCON EUROPE 2014

22 Canvas Parallelization - Power Consumption on Flashcanvas perf Benchmark Standard Blink on A15+GPU Parallelized Blink on quad-a7 No optimization 29 fps 17 fps -40% Performance 29 fps 26 fps -10% Power consumption Performance / Watt Difference 2,2W 0,4W 550% 1, % With parallelism and right chip choices you can get 5x power savings without losing performance! 22 October 10, 2014 LINUXCON EUROPE 2014

23 Comparing performance / watt: Using Google s Chome (version 33 Android) 2 cores active: 54% and 84% Power use A15+A7 cores: Watts Test average: 9.44 fps Using our optimized ChromeShell: 3 A7 cores active: 73%, 80% and 44% Power use A15+A7 cores: Watts Test average: fps 23 October 10, 2014 LINUXCON EUROPE 2014

24 1x A15 or 4x A7? 24 October 10, 2014 LINUXCON EUROPE 2014

25 1x A15 < 4x A7! Less W MIPS More than twice the performance 25 October 10, 2014 LINUXCON EUROPE 2014

26 Back to big.little Making these results work outside a lab

27 State of big.little in Linux - 1 What s in the kernel today? 27 October 10, 2014 LINUXCON EUROPE 2014

28 State of big.little in Linux - 2 What else is relevant? IKS (In-kernel-Switcher) Firstly available in Linaro kernel trees Merged in 3.11 kernel Qualcomm / LG / etc powerdaemons Throttle performance if cores overheat Usually secret Not-in-mainline Schedulers: Linaro s GTS (Global Task Scheduler), a.k.a. HMP (Heterogeneous Multi-Processing) Kernel Summit 2014 Energy-Aware Scheduling Workship 28 October 10, 2014 LINUXCON EUROPE 2014

29 Feedback loop Setpoint We know when we want to have 4xA7 or 1xA15 If we can tell the kernel, it can anticipate instead of noticing an increase in workload and by accident turning on the A15s 29 October 10, 2014 LINUXCON EUROPE 2014

30 Where to go? Qualcomm MARE Research project Framework to aid parallelization Should assist kernel in scheduling/cpufreq Feedback loop (in user space) Deadline scheduler Merged in Linux 3.14 Application sets SCHED_DEADLINE Application sets scheduling attributes Task repetition in microseconds Task start within repetition Task completion deadline within repetition Feedback loop (in kernel space) 30 October 10, 2014 LINUXCON EUROPE 2014

31 Is parallelism going to stay? Actually, is big.little going to stay??? The GHz race has come to an end Now also for ARM The speed of light limits clock domain size Thus many clock islands on a die Multicore is just an easy way to improve performance At the cost of the programmer Who needs extra training ARM big.little Is a mechanism to skip heavy power consumption At the cost of more mm 2 silicon Is it worth it??? 31 October 10, 2014 LINUXCON EUROPE 2014

32 My ideal ARM-based design: big: 1x A57 LITTLE: 4x A53 Why is no-one designing this chip? 32 October 10, 2014 LINUXCON EUROPE 2014

33 Conclusions

34 Conclusion big.little works IFF Short bursts can be handled by one big core Heavier workloads are parallelizable and run on clusters of LITTLEs APIs become available: Programs must indicate what the workload will be BTW: Chromium is parallelizable we did it. 34 October 10, 2014 LINUXCON EUROPE 2014

35 Conclusion big.little works IFF Short bursts can be handled by one big core Heavier workloads are parallelizable and run on clusters of LITTLEs APIs become available: Programs must indicate what the workload will be BTW: Chromium is parallelizable we did it. 35 October 10, 2014 LINUXCON EUROPE 2014

36 Vector Fabrics the Company Founded February 2007 Founding team Strong in SoC design and multi-core software Currently 15 FTE: 6 PhD, 7 MSc Protected technology 3 patents filed in US & Europe Recognition Hot Startup in EE Times Silicon 60, since 2011 Selected by Gartner as Cool vendor in Embedded Systems & Software 2013 Global Semiconductors Alliance award, March October 10, 2014 LINUXCON EUROPE 2014

37 Contact Information Web: Tel: Address: Vector Fabrics B.V. Vonderweg RM Eindhoven The Netherlands 37 October 10, 2014 LINUXCON EUROPE 2014

38 Thank You! (drop your business card if you want the slides and the to-be-released whitepaper) Klaas van Gend FAE, Trainer & Consultant