Difference between revisions of "ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 3"
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| + | == Model deployment == | ||
| + | |||
| + | == Building and running the application == | ||
| + | In order to have reproducible and reliable results, some measures were taken: | ||
| + | * The inference was repeated several times and the average execution time was computed | ||
| + | * All the files required to run the test—the executable, the image files, etc.—are stored on a tmpfs RAM disk in order to make file system/storage medium overhead neglectable. | ||
| + | |||
| + | == Results == | ||
Revision as of 16:47, 25 September 2020
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Contents
History[edit | edit source]
| Version | Date | Notes |
|---|---|---|
| 1.0.0 | September 2020 | First public release |
Introduction[edit | edit source]
This Technical Note (TN for short) belongs to the series introduced here. Specifically, it illustrates the execution of an inference application (fruit classifier) that makes use of the model described in this section when executed on the Xilinx Zynq UltraScale+ MPSoC ZCU104 Evaluation Kit. The results achieved are also compared to the ones produced by the platforms that were considered in the previous articles of this series.
Environment[edit | edit source]
| Component | Name/version | Version | |
|---|---|---|---|
| Host | |||
| Target | Hardware platform | ZCU104 | |
| Linux BSP | Petalinux | 2020.1 |
Model deployment[edit | edit source]
Building and running the application[edit | edit source]
In order to have reproducible and reliable results, some measures were taken:
- The inference was repeated several times and the average execution time was computed
- All the files required to run the test—the executable, the image files, etc.—are stored on a tmpfs RAM disk in order to make file system/storage medium overhead neglectable.
