Hello everyone, my name is Mahameru from Indonesia. I'm currently conducting computer vision research using Axelera PCI and M2 cards. I've tried running the model using YOLO Model versions 8 and 11, and I get different confidence levels when running using the CPU/GPU (local on my laptop) and Axelera. Can anyone help me?
confidance
+3- Axelera Team
Hi there
Ah, I bet this is something to do with quantisation.
When a model runs on the CPU/GPU it's using 16 or 32-bit floating point. But on Metis, the model is quantised to an 8-bit integer to get the optimal performance and efficiency benefits of the hardware. So that quantisation step will probably shift confidence scores slightly compared to the original FP32 model, if that makes sense?
But it’s usually pretty minimal even then. Here’s a bit more info about it, that should help. Is it vastly different of you, or just a bit of a variance?
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