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EMBEDDING LOW-COST INTELLIGENCE
WITH XCORE.AI
12 JUNE 2020
22
TECHNOLOGY IS WOVEN
THOUGHOUT OUR LIVES
3
THE AIOT IS APPLICABLE ACROSS MARKETS
ENABLING HIGH PERFORMANCE, ACROSS VERTICALS, ECONOMICALLY
Smart speaker
Audio visual
Appliances
Lighting
Security
Fitness
Care
Diagnostics &
monitoring
MHealth
Traffic &
parking
Environmental
Utilities
Public safety &
security
TAM
Operations
Tracking
Safety
Maintenance
Energy
management
Asset tracking &
predictive
maintenance
In car people
tracking
Autonomous L1
driving & safety
500M
UNITS
500M
UNITS
650M
UNITS
450M
UNITS
90M
UNITS
44
CHALLENGES OF THE AIoT REVOLUTION
45% DATA SECURITY AND AUTONOMY
38% BANDWIDTH
32% LATENCY
24% SCALABILITY
24% CLOUD INFRASTRUCTURE LIMITATIONS
BASED ON PRIMARY RESEARCH WITH ELECTRONICS ENGINEERS
WHAT’S NEEDED?
AIoT devices demand a processor with
high-performance compute, efficient energy
usage and a low eBOM.
A NEW KIND OF PROCESSOR
Fast, flexible and economical, xcore.ai puts
intelligence at the core of smart products,
combining AI, DSP, control and IO compute
in a one dollar device.
77
FAST, FLEXIBLE AND ECONOMICAL
32 x 16 x
15 x 21 x
ARM Cortex M7 @ 600MHzxcore.ai
AI performance faster I/O processing
DSP performance more 16-bit MACs
Benchmarked 18 Nov 2019. Preliminary information subject to change without notice
DELIVERING STANDOUT PERFORMANCE
88
FLEXIBLE & SCALABLE ARCHITECTURE
DRIVING FAST TIME TO MARKET, ENABLING COST EFFECTIVE SOLUTIONS
xcore device families
xcore Tools
xcore Libraries
3rd Party
Libraries
xcore LibrariesFreeRTOS
Custom platform solutions
xcore Libraries
USB
Audio
Voice
Human
Presence
Smart
Home
Connect
Health
Smart
Mobility
IndustryIoT
SmartCities
Solutions
99
STATE OF THE ART ARCHITECTURE
HIGH PERFORMANCE AND ENERGY EFFICIENCY CONVERGE IN A LOW eBOM CLASS LEADER
c
hardware ports
IO pins
switch
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xtime scheduler
hardware ports
xtime scheduler IO pins
SRAMSRAM
ALU (FP + int)
vector unit
ALU (FP + int)
vector unit
High-Speed USB PHY MIPI D-PHY
external
LPDDR
interface
JTAG
core PLL
app
PLL
OTP OTP
oscillator reset16 real-time logical cores,
with support for scalar /
float / vector instructions
Vector processing unit,
supports 8-bit and binarised
neural network inferences
Extended memory support
for large applications
Flexible IO ports with
nano-second latency;
create interfaces in software
High performance instruction
set for DSP, ML and
cryptographic functions
Integrated MIPI interface
for imaging support
Example software tasks
1010
MAPPING REAL-TIME TASKS, APP TASKS, AND INFERENCING TASKS
Neuralnetmodel
c
Hardware Ports
IO pins
Switch
xTIME scheduler
Hardware Ports
xTIME scheduler IO pins
High speed USB PHY MIDI D-PHY
External
LPDDR
interface
JTAG
Core PLL App PLL
Oscillator Reset
FreeRTOS and app
tasks dynamically
share fixed number of
thread contexts
Inferencing and real time tasks
allocated fixed threads at compile time
I2SLEDdrivers
PDMPDM
c
Far-fieldmicrophone
processing
Applicationtask
Applicationtask
…
Applicationtask
Keyworddetection
FreeRTOS
I2C
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
xcore logical core
Internal
SRAM
Internal
SRAM
ALU (FP + int)
Vector unit
ALU (FP + int)
Vector unit
OTP OTP
PDM
Far-field microphone
processing
Keyword detection
Free
RTOS
I2S, I2C, LED drivers
Apptask
PDM
Apptask
Apptask
Apptask
Neural net model
1111
FOUR CLASSES OF COMPUTE, ONE DEVELOPMENT PLATFORM
“USING XMOS WE WERE ABLE TO REPLACE THREE SEPARATE DEVELOPMENT SYSTEMS”
Richard Hollinshead, Meridian
Embedded
code
DSP
code
NN
Model
Cortex-M DSP core NPU Hardware
gates
IO &
accelerators
Cortex SoC development
Embedded
code
DSP
code
NN
Model
xcore
IO &
accelerators
xcore development
1212
PROGRAMMABLE USING INDUSTRY STANDARD TOOLS
ENABLING RAPID DEPLOYMENT AND SHORTENING TIME TO MARKET
Example software tasks
• Industry-standard TensorFlow Lite
workflow
• Automatic model translation
• Community support
Applicationtask
Applicationtask
…
Applicationtask
FreeRTOS
• Familiar, real-time, industry-standard
development environment
• Community support
• Wide variety of third party applications
FFT
FFT
QSPI
Filter
Filter
• High performance, predictable DSP
• Accessed using industry standard tools
• Highly optimised library kernels access
xcore.ai processing
CONTROL AI DSP
1313
AI USER WORKFLOW
Trained floating
point network
Lite convertor
(python API)
Run TFL to
xcore.ai
convertor
Key
TensorFlow component
XMOS component
User component
Key
TensorFlow component
XMOS component
User component
ONNX componentAlternative framework flow
trained network
my_model.tflite to TensorFlow
convertor
xcore.ai
micro Runtime
my_model.tflite
lib_xs3_ai
1414
PROGRAMMING – PULLING IT ALL TOGETHER
xmos
compiler
3rd party
Libraries
Executable
Control
source code
Neural net
model
Dataflow
source code
XMOS
Libraries
TensorFlowLite
to xcore.ai
convertor
Applicationtask
Applicationtask
…
Applicationtask
FreeRTOS
FFT
FFT
QSPI
Filter
Filter
1515
IN SUMMARY
• The AIoT industry has reached a tipping point that will
radically transform our way of life
• Success depends on being able to drive one of the most
impressive feats of electronics engineering
• xcore.ai is that feat
THANK YOU
XCORE.AI

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Implementing AI: Running AI at the Edge: Embedding low-cost intelligence with xcore.ai - Mark Lippett and Henk Muller, XMOS

  • 1. EMBEDDING LOW-COST INTELLIGENCE WITH XCORE.AI 12 JUNE 2020
  • 3. 3 THE AIOT IS APPLICABLE ACROSS MARKETS ENABLING HIGH PERFORMANCE, ACROSS VERTICALS, ECONOMICALLY Smart speaker Audio visual Appliances Lighting Security Fitness Care Diagnostics & monitoring MHealth Traffic & parking Environmental Utilities Public safety & security TAM Operations Tracking Safety Maintenance Energy management Asset tracking & predictive maintenance In car people tracking Autonomous L1 driving & safety 500M UNITS 500M UNITS 650M UNITS 450M UNITS 90M UNITS
  • 4. 44 CHALLENGES OF THE AIoT REVOLUTION 45% DATA SECURITY AND AUTONOMY 38% BANDWIDTH 32% LATENCY 24% SCALABILITY 24% CLOUD INFRASTRUCTURE LIMITATIONS BASED ON PRIMARY RESEARCH WITH ELECTRONICS ENGINEERS
  • 5. WHAT’S NEEDED? AIoT devices demand a processor with high-performance compute, efficient energy usage and a low eBOM.
  • 6. A NEW KIND OF PROCESSOR Fast, flexible and economical, xcore.ai puts intelligence at the core of smart products, combining AI, DSP, control and IO compute in a one dollar device.
  • 7. 77 FAST, FLEXIBLE AND ECONOMICAL 32 x 16 x 15 x 21 x ARM Cortex M7 @ 600MHzxcore.ai AI performance faster I/O processing DSP performance more 16-bit MACs Benchmarked 18 Nov 2019. Preliminary information subject to change without notice DELIVERING STANDOUT PERFORMANCE
  • 8. 88 FLEXIBLE & SCALABLE ARCHITECTURE DRIVING FAST TIME TO MARKET, ENABLING COST EFFECTIVE SOLUTIONS xcore device families xcore Tools xcore Libraries 3rd Party Libraries xcore LibrariesFreeRTOS Custom platform solutions xcore Libraries USB Audio Voice Human Presence Smart Home Connect Health Smart Mobility IndustryIoT SmartCities Solutions
  • 9. 99 STATE OF THE ART ARCHITECTURE HIGH PERFORMANCE AND ENERGY EFFICIENCY CONVERGE IN A LOW eBOM CLASS LEADER c hardware ports IO pins switch xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xtime scheduler hardware ports xtime scheduler IO pins SRAMSRAM ALU (FP + int) vector unit ALU (FP + int) vector unit High-Speed USB PHY MIPI D-PHY external LPDDR interface JTAG core PLL app PLL OTP OTP oscillator reset16 real-time logical cores, with support for scalar / float / vector instructions Vector processing unit, supports 8-bit and binarised neural network inferences Extended memory support for large applications Flexible IO ports with nano-second latency; create interfaces in software High performance instruction set for DSP, ML and cryptographic functions Integrated MIPI interface for imaging support Example software tasks
  • 10. 1010 MAPPING REAL-TIME TASKS, APP TASKS, AND INFERENCING TASKS Neuralnetmodel c Hardware Ports IO pins Switch xTIME scheduler Hardware Ports xTIME scheduler IO pins High speed USB PHY MIDI D-PHY External LPDDR interface JTAG Core PLL App PLL Oscillator Reset FreeRTOS and app tasks dynamically share fixed number of thread contexts Inferencing and real time tasks allocated fixed threads at compile time I2SLEDdrivers PDMPDM c Far-fieldmicrophone processing Applicationtask Applicationtask … Applicationtask Keyworddetection FreeRTOS I2C xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core xcore logical core Internal SRAM Internal SRAM ALU (FP + int) Vector unit ALU (FP + int) Vector unit OTP OTP PDM Far-field microphone processing Keyword detection Free RTOS I2S, I2C, LED drivers Apptask PDM Apptask Apptask Apptask Neural net model
  • 11. 1111 FOUR CLASSES OF COMPUTE, ONE DEVELOPMENT PLATFORM “USING XMOS WE WERE ABLE TO REPLACE THREE SEPARATE DEVELOPMENT SYSTEMS” Richard Hollinshead, Meridian Embedded code DSP code NN Model Cortex-M DSP core NPU Hardware gates IO & accelerators Cortex SoC development Embedded code DSP code NN Model xcore IO & accelerators xcore development
  • 12. 1212 PROGRAMMABLE USING INDUSTRY STANDARD TOOLS ENABLING RAPID DEPLOYMENT AND SHORTENING TIME TO MARKET Example software tasks • Industry-standard TensorFlow Lite workflow • Automatic model translation • Community support Applicationtask Applicationtask … Applicationtask FreeRTOS • Familiar, real-time, industry-standard development environment • Community support • Wide variety of third party applications FFT FFT QSPI Filter Filter • High performance, predictable DSP • Accessed using industry standard tools • Highly optimised library kernels access xcore.ai processing CONTROL AI DSP
  • 13. 1313 AI USER WORKFLOW Trained floating point network Lite convertor (python API) Run TFL to xcore.ai convertor Key TensorFlow component XMOS component User component Key TensorFlow component XMOS component User component ONNX componentAlternative framework flow trained network my_model.tflite to TensorFlow convertor xcore.ai micro Runtime my_model.tflite lib_xs3_ai
  • 14. 1414 PROGRAMMING – PULLING IT ALL TOGETHER xmos compiler 3rd party Libraries Executable Control source code Neural net model Dataflow source code XMOS Libraries TensorFlowLite to xcore.ai convertor Applicationtask Applicationtask … Applicationtask FreeRTOS FFT FFT QSPI Filter Filter
  • 15. 1515 IN SUMMARY • The AIoT industry has reached a tipping point that will radically transform our way of life • Success depends on being able to drive one of the most impressive feats of electronics engineering • xcore.ai is that feat