arm research overview › developer › files › stuart_biles… · accelerating investment to...
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© 2019 Arm Limited
Stuart Biles
Arm Research Overview
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History of ArmJoint venture between
Acorn Computers and Apple
1990
Designed into first mobile phones and then smartphones
1993 onwards
Now all electronic devices and systems canuse smart Arm technology
Today
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Arm's current business
Arm primary business is the development of 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 IP
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Accelerating investmentto increase share gains
Generatingprofits and cashto be reinvested
Investing in new processor technology
• Machine learning processors
• Computer vision
• Augmented reality
• Platform security
Investing in new IoT software and services
• Device Management
• Connectivity as a Service
• Data Management as a Service
• Pelion platform
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Introducing Arm Research
Research Collaboration
ResearchEnablement
Research Programs
Arm Education
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© 2019 Arm Limited
Education Collaboration &
Enablement
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Arm EducationHelping to close the education and skills gap in Computer Engineering and STEM
• Empowering learners and communities of practice with evidence-based research and curriculum-linked educational materials and platforms -Enable a lifetime positive engagement in STEM
• Email [email protected]
Arm University Program Arm Education Media Arm School/K-12 Program
• Enabling learning through rich multimedia online courses and digital-first books allowing students, hobbyists, and engineers to learn, up-skill and become work ready
• Email [email protected]
• Free access to academically rigorous education kits using state-of-the-art Arm ecosystem technologies - support Electrical, Electronic and Computer Engineering,and Computer Science curricula
• Email [email protected]
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Director US/North AmericaRaffaella Montelli, PhD.
Director UK/EuropeAndrea Kells, PhD.
Help connect peopleand ideas
Lead outreach and inbound activities
Facilitate execution of agreements
Manage collaborations and partnerships
Help identify funding opportunities
Arm Research Collaboration Team
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Why work with Arm Research?
• Proven IP, tools, platforms and expertise to help strengthen the impact of your research
• Vibrant partner ecosystem to help you successfully develop and tape out your research products
• Talent development opportunities to help your students more easily enter the semiconductor industry
• Credible industry support to improve the success of your research proposals
• Dedicated team to provide you with what you need to meet your research goals
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The Arm Research Ecosystem
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Ecosystem Success: Arm High Performance Computing
Enablement▪ Address gaps in computational
capability and data movement within Architecture
▪ Seed the software ecosystem with open source support for Armv8 and SVE libraries, tools, and optimized workloads
▪ Provide world class tools for compilation, analysis, and debug at large scale.
Co-Design▪ Work with key end-customers in DoE,
DoD, RIKEN, and EU to design balanced architecture, uArchitecture and SoCs based on real-world workloads, not benchmarks.
▪ Develop simulation and modeling tools to support co-design development with end-customers, partners, and academia.
Partnership▪ Work with Architecture partners to
quickly bring optimized solutions to market.
▪ Work with Architecture and uArchitecture design teams to steer future designs to be more relevant for HPC, HPDA, and ML
▪ Work with key ISVs to enable mid-market
MissionEnable the world’s first Arm supercomputer(s)
Enablement + Co-Design + Partnership
Strategy:StrategyEnablement + Co-Design + Partnership
Building Blocks
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High Performance Computing Research
Dibona(MontBlanc)
Astra (SANDIA) Fugaku (RIKEN CCS)
Thunder (LANL) EPI GPP Isambard (U. Bristol)
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Arm Research Enablement Activities
• Arm has always provided our technology for research purposes under various schemes
• Research Enablement team focus on
• Broadening the technology portfolio available to researchers
• Enhancing your experience working with Arm
• Building an academic, collaborative ecosystem focused on Arm SoCs
• Go to "Your Research Enabled by Arm" workshop to find out details about our existing and new enablement initiatives• Tuesday, 11:00- 17:30, Tannehill
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Arm Flexible Access for Research
• Access to a wide range of Arm IP for research purposes
• Complete RTL for cores and subsystems
Wider range of IP
• Sped-up approval process from several weeks or months to two days
• Reduced friction with simple click-through End-User License Agreement (EULA)
Quicker and easier process Simplified legal framework
To be available to academic researchers in early 2020
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© 2019 Arm Limited
Research Programs
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Ever-expanding roles of compute and data drive Arm’s opportunity
Value from dataArm everywhere
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SS
S S
S
C
Compute
CA
CCA
CCA
CCA
Acceleration
Arm is uniquely positioned in “device-to-cloud”
Storage
Edge computing – necessary to handle the massive upstream data
Local Services(Gateways)
IoT Device (Data Source)
Public / Private Cloud
Infrastructure Services
Edge cloud
18
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M0N0 Full System DiagramEvolved to Cortex-M33 with ROM, RAM, peripherals, power management and clocking
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M0N0 is a World Leading Ultra Low Power MCU system• At least 6x lower shutdown power than 16/32b COTS MCUs
• At least 40% better active energy efficiency than COTS MCUs
• Great target for TinyML applications
• Cortex-M33 with 4x8b SIMD
• Always-on keyword spotting for 200 days on coincell (158mAh 1.5V)• M0N0 chip only - excludes microphone/ADC
• Potential for reduced PCB footprint• 6mm2 chip plus only three passives
M0N0
SW DevBoard
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• Evaluating CHERI technology on Cortex-M• Fine grained protection within compartments
• Pointers → Capabilities• Permissions bits
• Data vs code pointer
• Read only vs. read/write pointer
• Base and bounds information
• Hidden 1-bit tag makes Capabilities unforgeable
• Protects against a wide range of vulnerabilities• E.g. Buffer overflows, return orientated programming, and confused deputy attacks
• Addresses core memory safety issue, even on legacy languages (e.g. C/C++)
• Low software porting effort• Especially for well written code (compiler does most/all of the work)
SSITH – Capabilities for Cortex-M
~70%Of security
vulnerabilities due to memory
safety
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TinyMLWhat is it?
• ”Swimming in sensors, drowning in data”
• Model design and optimization for highly constrained hardware platforms
• Can we get 10X+ reduction in ops or memory with minimal accuracy loss?
Near term results
• Hybrid neural and non-neural techniques
• New training approaches for binary/ternary networks
• Compression techniques for recurrent neural networks (RNNs) that operate on time-series data
BBC Micro:Bit (Arm Cortex M0, 16KB RAM)
LPCXpresso 1125 (Arm Cortex M0, 8KB SRAM)
M0N0 (Arm Cortex M33, 16KB SRAM)
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TinyML: HybridNet
• “DS-CNN” is a highly optimized network for the key word spotting (KWS) task
• How do we optimize it further at iso-accuracy?
• Ternarize weight values using Strassen's algorithm
• Overall memory footprint reduced by 30%
• Selectively use decision trees to reduce compute
• Total number of operations reduced by 12%
• Less than 0.3% loss in accuracy for these savings
DS-CNN
ST-HybridNet
90
90.5
91
91.5
92
92.5
93
93.5
94
94.5
95
0 5 10 15 20 25 30 35 40
Acc
ura
cy (
%)
Memory Footprint (KB)
Accuracy vs Overall Memory Footprint
DS-CNN
ST-HybridNet
90
90.5
91
91.5
92
92.5
93
93.5
94
94.5
95
2 2.25 2.5 2.75 3
Acc
ura
cy (
%)
Operations (M)
Accuracy vs #Operations
Published in SysML’19 - https://arxiv.org/abs/1903.01531
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AutoBotWhat is it?
• Automate Neural Architecture Search (NAS) on Arm
• Incorporate information about Arm hardware into the optimization flow
• Reduce search runtime
Near term goal: Top-Down (Optimization)
1. Input a trained model
2. Optimize for Arm IP – reduce latency/energy at iso-accuracy
Long term goal: Bottom-Up (Design)
1. Input a dataset
2. Create a from-scratch model optimized for Arm IP
Optimization Runtime
Mo
del
Qo
R
Top-Down(Model Opt)
Bottom-Up(Global NAS)
MicroBrew(Local-NAS)
Submitted to NeurIPS’19 - https://arxiv.org/abs/1905.12107
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Edge Computing
Unreliable Connectivity
Resource Constraints
Security& Trust
Remotemonitoring
DeviceManagement
Scale
NetworkingProtocols
Containerization Microservices
CI/CDRolling
Updates
Rollbacks
HealthChecks
ServiceDiscovery
LifecycleManagement
SecurityPolicies
Designed and optimized for IoT and edge
Brings server style modern application management to edge computing
Based on Kubernetes and compatible with open source ecosystem, APIs, and tool chains
© 2019 Arm Limited
Edge Computing Cloud Service
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Research Focus Areas
Computer Systems
Computer system architecture
Application and domain specialization
System and circuit implementation
Security
Threat intelligence
Isolation and control mechanisms
Specification, testing and proof
Distributed & Information
Systems
Device commissioning and management
Edge computing and services
Data services
Emerging Technologies &
Materials
Post-Moore materials
Novel memory technologies
New frontiers of compute
Machine Learning
Best in class ML
Big data analytics
Applied ML
Disruptive Technology
Big paradigm shifts
Fundamental enabling technologies
Tracking and analysing
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Careers at ArmJoin the team!
Internships Cloud Services, Silicon Technology, Machine Learning, Processor and Memory System Architecture, Security, IoT Services, Emerging Technologies, Large Scale Systems, Digital Subsystems Design
Established SecurityPrincipal Security Research Engineer, Staff Security Research Engineer, Senior Security Research Engineer
Machine LearningSenior Machine Learning Research Scientist, Machine Learning Researcher
OtherData Systems Researcher, Senior Research Engineer,Staff Research Engineer, Staff Research Tools Engineer
bit.ly/armrshcareers
More Arm Careers
Many more opportunities across Arm beyond Research
arm.com/careers
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Closing Remarks
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The Arm trademarks featured in this presentation are registered trademarks or trademarks of Arm Limited (or its subsidiaries) in
the US and/or elsewhere. All rights reserved. All other marks featured may be trademarks of their respective owners.
www.arm.com/company/policies/trademarks
© 2019 Arm Limited