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Our engineering & Master degrees
Our engineering & Master degrees

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Project : Processing on GPU-FPGA (Image)(SICOM S9) - 5PMSPAM1

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  • Number of hours

    • Lectures : 0
    • Tutorials : 0
    • Laboratory works : 0
    • Projects : 32.0
    • Internship : 0
    • Written tests : 0
    ECTS : 4.0

Goals

This project is interested in the implementation of deep learning algorithms applied to images on GPU processor.
The objective is to illustrate an approach of adequacy between algorithm and architecture that is necessary for an efficient implementation. Industrial flows of development are used in this teaching.

Contact Dominique HOUZET

Content

The project takes place in two stages:

  • Study of the convolutional neural network with its database experimented with standard tools (Keras ...)
  • C / CUDA implementation on CPU / GPU of the different CNN layers with optimization of the implementation on GPU


Prerequisites

Tests

during the last project session, there will be an oral presentation of the work carried out. A 15-20 page project report is also produced.



Rapport : 100%

Additional Information

Curriculum->Double-Diploma Engineer/Master->Semester 9
Curriculum->Engineering degree->Semester 9

Bibliography

CUDA programming guide, Nvidia

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Date of update September 21, 2021

Université Grenoble Alpes