Implementing AI: Running AI at the Edge: Embedding low-cost intelligence with xcore.ai - Mark Lippett and Henk Muller, XMOS
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The Implementing AI: Running AI at the Edge, hosted by KTN and eFutures, is the second event of the Implementing AI webinar series. To make products more intelligent, more responsive and to reduce the data generated, it is advantageous to run AI on the product itself, as opposed to in the cloud. The focus of this webinar was the opportunities and challenges of moving the AI processing to “the Edge”. The webinar had four presentations from experts covering overviews of the opportunity, implementation techniques and case studies. Find out more: https://ktn-uk.co.uk/news/just-launched-implementing-ai-webinar-series
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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
- 2. 22 TECHNOLOGY IS WOVEN THOUGHOUT OUR LIVES
- 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