From 280b1ec7ca41a5acc28d3a23a5865b838904549e Mon Sep 17 00:00:00 2001 From: Jason Andrews Date: Wed, 2 Jul 2025 10:20:03 -0500 Subject: [PATCH] start review of Visualizing Ethos-U on FVPs --- .../visualizing-ethos-u-performance/_index.md | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/content/learning-paths/embedded-and-microcontrollers/visualizing-ethos-u-performance/_index.md b/content/learning-paths/embedded-and-microcontrollers/visualizing-ethos-u-performance/_index.md index e57c5de281..71ce781eab 100644 --- a/content/learning-paths/embedded-and-microcontrollers/visualizing-ethos-u-performance/_index.md +++ b/content/learning-paths/embedded-and-microcontrollers/visualizing-ethos-u-performance/_index.md @@ -1,6 +1,10 @@ --- title: Visualizing Ethos-U Performance on Arm FVPs +draft: true +cascade: + draft: true + minutes_to_complete: 120 who_is_this_for: This is an introductory topic for developers and data scientists new to Tiny Machine Learning (TinyML), who want to visualize ExecuTorch performance on a virtual device. @@ -12,8 +16,8 @@ learning_objectives: - Observe model execution on the FVP's graphical user interface (GUI). prerequisites: - - Basic knowledge of Machine Learning concepts - - A Linux or Mac computer + - Basic knowledge of Machine Learning concepts. + - A computer running Linux or macOS. author: Waheed Brown @@ -25,7 +29,6 @@ armips: - Cortex-A - Cortex-M - Ethos-U - - Ethos-U85 operatingsystems: - Linux