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Arm Ethos-U System Design

Delivery method: Face-to-face (Private)
Location: Any location
Course Length: 3-4 days face to face or 6-8 1/2 days virtual classroom
Technology Focus: Combined Hardware and Software
Cost: Contact us for pricing
Provider: Arm

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Summary

The Arm Ethos-U processor series training courses are designed to help embedded engineers working on new or existing Arm Ethos-U designs. Whether you’re working on design, verification or validation, for an Arm Ethos-U system, the course can be configured according to your team’s needs.

Courses include fundamental topics to enable a solid platform of understanding. The rest of the course then builds on from this with optional topics and can be tailored appropriately. Some key topics are delivered via pre course on-demand video.

A pre course call with the engineer delivering the training will help you discuss your team’s individual training requirements.

At the end of this course, delegates will be able to

Describe the Ethos-U Neural Processor Unit (NPU) main functions and supported API
Explain the Ethos-U data flow and block architecture
Describe the physical model integration and the interface signals
Configure and integrate the Ethos-U into their SoC
Run the supplied test cases
Describe the Ethos-U NPU functional model
Describe Arm Machine Leaning SW architecture
Understand Ethos-U driver stack, Tensorflow Lite Micro and CMSIS-NN
Describe the Embedded "Offline" tooling and Online Memory Management

Course Length	Delivery Method	Location
3-4 Days	Classroom	Virtual or Onsite

Audience

Engineers working on a SoC project using Ethos-U NPU and carrying out System Design or verification.

Prerequisites

A working knowledge of RTL design
Machine Learning using Arm Online Training Module
Background knowledge about Machine Learning

Related Products

Arm Ethos-U55, Ethos-U65

Topics

Agendas will be created from the following list of fundamental and optional topics

SW Topics	HW Topics
Ethos SW Flow Software stack overview Integration with subsystem Cortex-A interfacing (Cortex U65 only) Device flow (offline and online) Integration overview with TFLu Inference Flow for Cortex-A --> Cortex-M/Yoda Sub-system (Cortex U65 only) Tensorflow Lite Micro and CMSIS-NN Overview of Tensorflow Lite micro Tensorflow Lite micro Architecture Overview of CMSIS-NN TFLµ integration with CMSIS-NN and Ethos-U Building process of Tensorflow lite micro for Ethos-U Ethos Offline/Online Memory Management Vela Memory management Memory management in depth Model Conditioning Model Development Flow Post-training optimizations Training-time optimizations Vela In depth Understand Vela internals Vela CLI options Vela output options Ethos Driver: Repositories Building Architecture Upstream process Model integration into a fast model environment*	Ethos Hardware Overview Endpoint devices Embedded ML software and tools Ethos-U55 hardware and configurations Typical Ethos-U55 data flow Ethos-U55 performance A use-case analysis Ethos-U55 evaluation platform targets Ethos Architecture Functional Block Computation units of work Control and Data flow Programmers model Debug and Trace Security Ethos HW integration Getting Started Implementation process flow Configuration Physical Model integration Clock and resets Interface signals Memory system considerations Testbenches and Integration Kit Ethos-U NPU Functional Model

SW Topics

HW Topics

Ethos SW Flow

Software stack overview
Integration with subsystem
Cortex-A interfacing (Cortex U65 only)
Device flow (offline and online)
Integration overview with TFLu
Inference Flow for Cortex-A --> Cortex-M/Yoda Sub-system (Cortex U65 only)

Tensorflow Lite Micro and CMSIS-NN

Overview of Tensorflow Lite micro
Tensorflow Lite micro Architecture
Overview of CMSIS-NN
TFLµ integration with CMSIS-NN and Ethos-U
Building process of Tensorflow lite micro for Ethos-U

Ethos Offline/Online Memory Management

Vela Memory management
Memory management in depth

Model Conditioning

Model Development Flow
Post-training optimizations
Training-time optimizations

Vela In depth

Understand Vela internals
Vela CLI options
Vela output options

Ethos Driver:

Repositories
Building
Architecture
Upstream process

Model integration into a fast model environment*

Ethos Hardware Overview

Endpoint devices
Embedded ML software and tools
Ethos-U55 hardware and configurations
Typical Ethos-U55 data flow
Ethos-U55 performance
A use-case analysis
Ethos-U55 evaluation platform targets

Ethos Architecture

Functional Block
Computation units of work
Control and Data flow
Programmers model
Debug and Trace
Security

Ethos HW integration

Getting Started
Implementation process flow
Configuration
Physical Model integration
Clock and resets
Interface signals
Memory system considerations
Testbenches and Integration Kit

Ethos-U NPU Functional Model

Optional Topics
Difference between Ethos-U processors Machine Learning using Arm*, Online introduction to Machine Learning using Arm Products ArmNN – How to build and structure ArmNN and how to run Caffe Model Compute Library Introduction, Compiling, structuring as well as Gaussian Pyramid, Integral Image, SGEMM and Winograd optimisation

Optional Topics

Difference between Ethos-U processors
Machine Learning using Arm*, Online introduction to Machine Learning using Arm Products
ArmNN – How to build and structure ArmNN and how to run Caffe Model
Compute Library Introduction, Compiling, structuring as well as Gaussian Pyramid, Integral Image, SGEMM and Winograd optimisation

* = Online and on-demand.

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