IEEE SPS - MIVisionX Inference Tutorial

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IEEE Signal Processing Society Chapter Santa Clara Valley

Hands-on OpenVX Inference Tutorial
In this tutorial, we will learn how to run inference efficiently using OpenVX and OpenVX Extensions. <A HREF="https://www.khronos.org/openvx/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">OpenVX</A> is an open, royalty-free standard for cross platform acceleration of computer vision applications. It is designed by the Khronos Group to facilitate portable, optimized and power-efficient processing of methods for vision algorithms.
<A HREF="https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/raw/master/docs/images/modelCompilerWorkflow.png" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer"><IMG STYLE="vertical-align: middle; display: block; margin-left: auto; margin-right: auto;" ALT="" SRC="https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/raw/master/docs/images/modelCompilerWorkflow.png" HEIGHT="173" WIDTH="600"></IMG></A>
 
The tutorial will go over each step required to convert a pre-trained neural net model into an OpenVX Graph and run this graph efficiently on any target hardware.
 
<A HREF="https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/raw/master/docs/images/frameworks.png" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer"><IMG STYLE="display: block; margin-left: auto; margin-right: auto;" ALT="" SRC="https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/raw/master/docs/images/frameworks.png" WIDTH="600"></IMG></A>
In this tutorial, we will also learn about AMD MIVisionX which delivers open source implementation of OpenVX and OpenVX Extensions along with Neural Net Model Compiler & Optimizer.
 
<IMG STYLE="vertical-align: middle; display: block; margin-left: auto; margin-right: auto;" ALT="" SRC="https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/raw/master/docs/images/MIVisionX.png" WIDTH="300">
<IMG ALT="" SRC="https://github.com/kiritigowda/MIVisionX/raw/kg/release-1.3.0/docs/images/MIVisionX.png">
<A HREF="https://gpuopen-professionalcompute-libraries.github.io/MIVisionX/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">MIVisionX</A> toolkit is a set of comprehensive computer vision and machine intelligence libraries, utilities, and applications bundled into a single toolkit. AMD MIVisionX delivers highly optimized open source implementation of the Khronos OpenVX™ and OpenVX™ Extensions along with Convolution Neural Net Model Compiler & Optimizer supporting ONNX, and Khronos NNEF™ exchange formats. The toolkit allows for rapid prototyping and deployment of optimized workloads on a wide range of computer hardware, including small embedded x86 CPUs, APUs, discrete GPUs, and heterogeneous servers.
The tutorial will give the attendees hands-on experience with neural nets and help them create an inference engine.
 
<H2>Agenda</H2>
When: Friday 14th June 2019
Where: AMD 2485 Augustine Dr, Santa Clara, CA 95054
Start Time: 2:30 PM
<UL>
<LI>2:30 pm - Register and network</LI>
<LI>3:00 pm - Tutorial starts
<UL>
<LI>Machine Learning & Industry Trends: Ajit Mathews - Corporate Vice President, AMD</LI>
<LI>OpenVX & Machine learning with MIVisionX: Mike Schmit - Director of Software Engineering, AMD</LI>
<LI>OpenVX Hands-on Inference: Kiriti & Rajy, AMD</LI>
</UL>
</LI>
<LI>5:30 PM - Wrap up and adjourn</LI>
</UL>
<SPAN STYLE="font-weight: bold; padding-top: 0px; color: #6f7287; font-family: 'Neue Plak', -apple-system, BlinkMacSystemFont, Roboto, 'Helvetica Neue', Helvetica, Tahoma, Arial, sans-serif; font-size: small; letter-spacing: 0.5px;">*** Bring PHOTO ID (passport, driver license, etc.) ***
<H2>Tutorial Requirements:</H2>
Install the appropriate terminal program on your laptop:
<UL>
<LI>Windows laptop - install MobaXterm - <A HREF="https://mobaxterm.mobatek.net/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">https://mobaxterm.mobatek.net/</A></LI>
<LI>Linux Laptop - install SSH - sudo apt install openssh-server</LI>
<LI>Mac - install Xquartz - <A HREF="https://www.xquartz.org/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">https://www.xquartz.org/</A></LI>
</UL>
<H2>Tickets</H2>
<UL>
<LI>Only limited seats are available for the tutorial. Book your tickets now at <A HREF="https://www.eventbrite.com/e/ieee-sps-mivisionx-inference-tutorial-tickets-62540630710" TARGET="_blank">Eventbrite</A></LI>
<LI>Limited free tickets are available for students. Please email yang.lei@ieee.org with your .edu email account to reserve your free ticket.</LI>
</UL>
 
Event sponsored and organized by:
<A HREF="https://ewh.ieee.org/r6/scv/sps/" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">IEEE </A><A HREF="https://ewh.ieee.org/r6/scv/sps/" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Signal Processing Society (SPS)</A><A HREF="https://ewh.ieee.org/r6/scv/sps/" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer"> </A>
 
Co-sponsors:
<UL STYLE="margin: 0px; padding: 10px 0px 0px 2em; list-style-position: initial; list-style-image: initial; color: #6f7287; font-family: 'Neue Plak', -apple-system, BlinkMacSystemFont, Roboto, 'Helvetica Neue', Helvetica, Tahoma, Arial, sans-serif; font-size: 14.933333396911621px; letter-spacing: 0.5px;">
<LI>
<A STYLE="color: var(--eds-control,#3659e3); text-decoration: none; cursor: pointer; background-color: transparent; padding-top: 0px;" HREF="https://ieee-region6.org/scv-cis/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Computational Intelligence Society (CIS)</A>
</LI>
<LI><A HREF="https://www.ieee-cas.org/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Circuits and Systems Society (CASS)</A></LI>
<LI><A STYLE="font-family: arial, helvetica, sans-serif; font-size: small; letter-spacing: 0.5px; background-color: transparent; text-decoration-line: none; cursor: pointer;" HREF="http://computer.ieeesiliconvalley.org/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Computer Society (CS)</A></LI>
<LI><A HREF="https://www.valleyml.ai/" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">ValleyML.ai</A></LI>
</UL>

AMD Santa Clara Media Room

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IEEE SPS - MIVisionX Inference Tutorial

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