Difference between revisions of "Getting started with AI on NXP i.MX8M Plus/Introduction/Overview/i.MX8M Plus hardware specifications"

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The board used in this entire research is the Variscite DART-MX8M-PLUS based on NXP i.MX8M Plus and some of the main characteristics are listed in the table below.
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        <th id="n">Negative</th>
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        <th>Characteristic</th>
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        <th id="p">Positive</th>
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! Hardware module
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! Specification
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| CPU
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| - 4 cores ARM Cortex A53.<br />- Frequency: [1200, 1800] Hz.<br />- Supported 32 and 64 bits.<br />- One thread per core.
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| GPU
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| - 3D GPU GC7000UltraLite.<br />- 2D GPU GC520L.
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| NPU
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| - Reaches up to 2.3 TOP/s.<br />- Optimized for voice and image<br /> recognition, object detection. <br />- Uses Winograd Algorithm. <br />- Supports 8 and 16 bits operations. 
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| RAM
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| - 4 GB.<br />- LPDDR4-4000.
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Latest revision as of 11:03, 21 March 2023




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Previous: Introduction/Overview Index Next: Introduction/Overview/Development tools
Getting started with
AI on NXP i.MX8M Plus
Ridgerun-logo.svg
Introduction
Overview
Development kit
Quick getting started
Development
Gatesgarth and Hardknott Yocto versions
Integrating multimedia software stack
Integrating Artificial Intelligence software stack
Developing software for the board
Neural Processing Unit
Introduction
Profiling the NPU
Use Case experiments: Smart Parking
Introduction to the use case
License Plate Detection
License Plate Recognition
Bash scripts for CPU usage and time estimation
Serial experiments
Parallel Experiments
Results
GStreamer
Exploring Rosetta element for character recognition
Example pipelines
Contact Us




The board used in this entire research is the Variscite DART-MX8M-PLUS based on NXP i.MX8M Plus and some of the main characteristics are listed in the table below.

Hardware module Specification
CPU - 4 cores ARM Cortex A53.
- Frequency: [1200, 1800] Hz.
- Supported 32 and 64 bits.
- One thread per core.
GPU - 3D GPU GC7000UltraLite.
- 2D GPU GC520L.
NPU - Reaches up to 2.3 TOP/s.
- Optimized for voice and image
recognition, object detection.
- Uses Winograd Algorithm.
- Supports 8 and 16 bits operations.
RAM - 4 GB.
- LPDDR4-4000.


Previous: Introduction/Overview Index Next: Introduction/Overview/Development tools



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