Softbank Group Corp. · TSE:9984

Softbank — Arm — Investor Presentation (February 2017)

46 slides from Softbank's investor presentation, February 2017

1. Slide 1: Making progress vs strategy

   Making progress vs strategy Ian Thornton, Head of Investor Relations Arm is a subsidiary of 1 © 2017 Arm Limited

2. Slide 2: Arm update

   Arm update Arm refresher H1 update – Increasing revenues and investments Progress vs strategy • Arm in servers • AI at the edge • Autonomous vehicles 2 © 2017 Arm Limited

3. Slide 3: ARM overview

   ARM overview 33 ©©Arm 2017 2017 Arm Limited

4. Slide 4: Chip design – then and now

   Chip design – then and now 1961 Today Four transistors Two billion transistors One engineer Thousands of engineers 4 © 2017 Arm Limited

5. Slide 5: A system-on-chip contains multiple blocks of IP

   A system-on-chip contains multiple blocks of IP Main processor for running the operating system, applications and user interface Graphics processor for generating images Accelerators for frequently-used compute workloads, e.g. image processing, encryption, vision Radio controllers for mobile, wifi,

6. Slide 6: ARM’s current business

   ARM’s current business ARM develops intellectual property (IP) blocks which are used in silicon chips Our partners combine ARM IP with their own IP to create complete chip designs We earn license fees when we deliver ARM IP to our partners and royalties when our partners ship chips that contain ARM

7. Slide 7: Accelerating investment; mbed Cloud; $500m free cash flow

   Accelerating investment Investing to create to increase share gains new revenue streams mbed Cloud Generating mbed Cloud Partners $500m free cash flow (2017 forecast) and growing 7 © 2017 Arm Limited

8. Slide 8: Technology trends that will redefine all industries

   Technology trends that will redefine all industries Artificial Intelligence in Autonomous Augmented Hyperscale cloud every device machines reality and connectivity Security and Privacy 8 © 2017 Arm Limited

9. Slide 9: Arm’s business model

   Arm’s business model Arm develops technology that is licensed to semiconductor companies Arm receives an upfront license fee and a royalty on every chip that contains its technology Business Development 1) Arm licenses 2) Partners develop technology to chips and ship chip Partners them to OEMs Techn

10. Slide 10: Licensing

    Licensing 10 ©©Arm 10 2017 2017 Arm Limited

11. Slide 11: Q2 Licensing: 26 is the low-end of the normal range

    Q2 Licensing: 26 is the low-end of the normal range Average Historic licensing = 20 60 Q1 Q3 50 Q2 Q3 Q3 40 Q2 Q1 Average 11 Q1 Q4 =8 Q2 30 Q4 7 Average Average =5 Q3 Q4 Q2 =4 Q4 Q1 Q1 Average 4 4 20 Q2 =1 Year 13 14 15 16 17 0 Classic Cortex-A Cortex-R Cortex-M Mali 11 © 2017 Arm Limited

12. Slide 12: Accelerating the next trillion devices

    Accelerating the next trillion lol devices *DesignStart gives companies easy access to Arm IP. There is no upfront license fee, the partner pays royalties once chips enter production.

13. Slide 13: DesignStart – Enabling the entire industry to build chips

    DesignStart – Enabling the entire industry to build chips 92 Cortex-M licenses in >1700 92 days in Q2 Cortex-M downloads to date DesignStart Pro DesignStart Eval Launched end June 2017 Launched end June 2017 License-fee free; royalty bearing No fees. Evaluation only. Optimised for FPGA 13 © 2017 Arm

14. Slide 14: Q2 Licensing: 118 licenses signed

    Q2 103 Q2 Licensing: 118 licenses signed? Average Historic licensing = 20 60 Q1 Q3 50 Q2 Q3 Q3 Q2 40 Q1 Q4 Q1 Average =8 Q2 30 Q4 7 Average Average =5 Q3 Q4 =4 Q4 Q1 Q1 Average 4 4 20 Q2 =1 Year 13 14 15 16 17 0 Classic Cortex-A Cortex-R Cortex-M Mali 14 © 2017 Arm Limited

15. Slide 15: Royalties

    Royalties 15 ©©Arm 15 2017 2017 Arm Limited

16. Slide 16: Industry growth vs Arm growth (for Q2 2017)

    Industry growth vs Arm growth (for Q2 2017) $190bn $80bn $0.5bn Overall Relevant Arm Semiconductor Semiconductor Royalty Industry Industry Revenue +29% +21% +19% +16% +11% +9% Value Volume Value Volume Value Volume ($) # chips ($) # chips ($) # chips Strong growth in memory Strong growth in MCUs; Ar

17. Slide 17: Is declining average royalty revenue per chip a concern?

    Is declining average royalty revenue per chip a concern? Average royalty per chip 10.0c 8.0c 6.0c 4.0c 2.0c 0.0c 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Drivers of average • Chip related: Average sales price of the chip; Arm content per chip • Arm re

18. Slide 18: Is declining average royalty revenue per chip a concern?

    Is declining average royalty revenue per chip a concern? Average royalty per chip 10.0c 8.0c 6.0c 4.0c 2.0c 0.0c 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Cortex-M Cortex-A 8.0bn 8.0bn 7.0bn 7.0bn 6.0bn 6.0bn 5.0bn 5.0bn 4.0bn 4.0bn 3.0bn 3.0bn 2.0bn 2

19. Slide 19: Investments Profitability

    Investments Profitability 19 ©©Arm 19 2017 2017 Arm Limited

20. Slide 20: Investing in engineering to increase productive output

    Investing in engineering to increase productive output Arm recruitment is running at around +1,100 2x previous run rate +586 +608 +488 Focus on retaining quality as well as +329 +388 quantity; and on cultural and organisational integration Will need to sustain this run rate for next 2-3 years 20 © 2

21. Slide 21: Investing in people, infrastructure to create new products

    Investing in people, infrastructure to create new products Costs were higher in H1 2017 as Arm expands R&D capability (£10m) £493m Future cost increases are expected to be £20m consistent with increases in headcount £41m £49m £25m £66m £301m * Share-based compensation was previously included in IFRS

22. Slide 22: Revenues, profits and profitability

    Revenues, profits and profitability Investment strategy H1 £1,400m only 45% Over the past 10 years Arm's Revenue Total Costs 40% revenues grew faster than costs £1,200m IFRS EBIT IFRS Margin 35% £1,000m 30% H1 2017 vs H1 2016 £800m 25% • Revenues +17% • Headcount +24% £600m 20% 15% £400m • Costs +64

23. Slide 23: Progress vs strategy

    Progress vs strategy 23 ©©Arm 23 2017 2017 Arm Limited

24. Slide 24: Arm in servers

    Arm in servers 24 © 2017 Arm Limited

25. Slide 25: Server market is changing

    Server market is changing Server Processor TAM ($) $25bn Standard enterprise $20bn $15bn High-performance computing $10bn $5bn Cloud $0bn 2016 2017 2018 2019 2020 2021 Cloud HPC Standard Server ARM focused on Cloud/HPC 25 © 2017 Arm Limited

26. Slide 26: Arm’s strategy to win share in servers

    Arm’s strategy to win share in servers Partnership and collaboration Arm technology Chip Software End user systems Beta First generation Testing Arm v8.0-A No commercial silicon Proof of concepts support Start date: 2008 2010 2012 2014 Arm technology Chip Software End user systems Arm-based chips av

27. Slide 27: Arm technology

    Arm technology Arm v7-A Arm v8.0-A Arm v8.2-A Arm v8.4-A Cortex-A15 Cortex-A72 Future Future Cortex-A9 Cortex-A57 Cortex-A75 Future Cortex-A7 Cortex-A53 Cortex-A55 Future Cortex-A5 Cortex-A35 Future Future Architecture released 2004 2011 2015 2017 Multi-core processing 64-bit computing Improved mult

28. Slide 28: Arm-based chips available from multiple vendors

    Arm-based chips available from multiple vendors 28 © 2017 Arm Limited

29. Slide 29: Arm silicon is competitive with current technology

    Arm silicon is competitive with current technology Performance Performance per thread https://www.qualcomm.com/media/documents/qualcomm-centriq-2400-media-deck. 29 © 2017 Arm Limited Performance per Watt Performance per dollar Qualcomm Centriq 2400 processors

30. Slide 30: Arm server software is commercially available

    Arm server software is commercially available All the major open source operating systems are now commercially available for Arm-based servers 30 © 2017 Arm Limited

31. Slide 31: Arm servers are being deployed by cloud companies

    Arm servers are being deployed by cloud companies 31 © 2017 Arm Limited

32. Slide 32: Artificial intelligence at the edge

    Artifical intelligence at the edge © 2017 Arm Limited

33. Slide 33: Distributing intelligence everywhere

    Distributing intelligence everywhere Mobile Automotive Robotics Drones Home, surveillance IoT & analytics VR/MR Shipping & logistics 33 © 2017 Arm Limited

34. Slide 34: © 2017 Arm Limited

    34 © 2017 Arm Limited

35. Slide 35: From the cloud to the edge

    From the cloud to the edge Security Privacy Latency Bandwidth Power and Cost 35 © 2017 Arm Limited

36. Slide 36: Heterogeneity is necessary

    Heterogeneity is necessary DSP DSP DSP There is no one size fits all solution DSP DSP DSP Need multiple types of processors to handle this DSP DSP DSP Fixed function works when requirements known in advance, algorithm is well understood, and CPU big CPU big FPGA high performance needed CPU CPU DSP L

37. Slide 37: Arm’s approach to AI

    Arm’s approach to AI Machine Learning applications Domain-specific libraries + ML frameworks: TensorFlow, Caffe, MXNet, etc. Tools and libraries from Arm CPUs + GPUs + ISPs + CV engines DSP FPGA ACC 37 © 2017 Arm Limited

38. Slide 38: ARM DynamIQ – Multicore redefined

    ARM DynamIQ – Multicore redefined Redesigned memory Advanced compute New single cluster design Greater flexibility sub-system capabilities 38 © 2017 Arm Limited

39. Slide 39: Journey of the autonomous automotive

    Journey of the autonomous automotive 39 © 2017 Arm Limited

40. Slide 40: 90% of automotive innovation comes from electronics and software

    “90% of automotive innovation comes from electronics (semiconductors) and software.” – Audi at CES Asia 40 © 2017 Arm Limited

41. Slide 41: Cars run on code

    Cars run on code F-35 24 Windows 10 60 US Army future combat system 63 Facebook 65 Luxury car in 2010 (IVI) 100 Luxury car in 2016 (+ADAS) 150 Luxury car in 2020 (L3 autonomy) 300~ All Google services 2000 Million lines of code 41 © 2017 Arm Limited

42. Slide 42: Automotive compute in 2020

    Automotive compute in 2020 Cockpit Connected Gateways ~50,000 DMIPS ~20,000 DMIPS Audio Visual, Maps, Traffic, Toll LTE 5G, WiFi, Bluetooth High-end smartphone payment, Google services connecting to CAN FD, LIN, Flexray, Body Electronics 30,000-50,000 DMIPS Rear entertainment, Voice recognition, Eth

43. Slide 43: Timeline for autonomous driving

    Timeline for autonomous driving 2016 2018 2020 2025 Advanced HIGHLY AUTOMATED AUTONOMOUS • Start of fully automated • Several control functions • All-round collision avoidance driving • Collision Avoidance Steering • Limited automated driving • High speed all-round collision (Low speed) • Ride shari

44. Slide 44: Powering the world’s first self-driving car

    Powering the Central driver assistance controller “zFAS” world’s first self-driving car * NVIDIA Tegra K1 New Audi A8 44 © 2017 Arm Limited zFAS using NVIDIA Tegra K1 - based on Quad core Arm Cortex-A15 *As a production car (autonomy level 3) 44

45. Slide 45: Denso licenses first ever Arm processor (Cortex-R52)

    Denso licenses first ever Arm processor (Cortex-R52) Targeting advanced driver assistance and safety critical systems Cortex-R52: Highest performance real- Driver assistance time processor First processor with embedded virtualisation to simplify software consolidation Designed for functional safety

46. Slide 46: Thank You!

    Thank You! Danke! Merci! 谢谢! ありがとう! Gracias! Kiitos! 감사합니다 धन्यवाद 46 © 2017 Arm Limited

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