Intel DevCloud for the Edge hands-on workshop contents (Japanese, 日本語版)
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Updated
May 30, 2020 - Jupyter Notebook
Intel DevCloud for the Edge hands-on workshop contents (Japanese, 日本語版)
Data-parallel molecular dynamics simulator for Intel oneAPI.
Hands-on workshop contents to learn about Intel DevCloud for the Edge
These are face recognition and object detection programs and used as training materials at KC3 2020.
Traballo Final do Mestrado en Computación de Altas Prestacións (High Performance Computing)
Three real-world scenarios given to analyze and optimize their queuing systems. This project demonstrates how to identify the appropriate Intel Hardware types that will work best for the manufacturing, and retail, and transportation scenarios. This application uses Intel DevCloud.
Implementation of certain crucial algorithms in the field of reinforcement learning.
The main focus area of this project is to propose a possible hardware solution for each scenario. Build out the application and test its performance on the DevCloud using multiple hardware types. Compare the performance to see which hardware performed best.
vector-add scripts using oneAPI and targeting FPGA devices. Verifications made on Intel's devcloud.
Deploy custom queuing AI systems for the retail, manufacturing and transportation scenarios and use the Intel® DevCloud to test solutions performance.
Given real-world scenarios to build a queuing system and the hardware specifications, the user can identify which hardware types work best. The application tested using the Intel® DevCloud.
Project #2 for Intel's Udacity Nanodegree Program, using Intel's OpenDev Cloud for benchmarking different use case scenarios for deploying OpenVino on edge devices
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