Uploaded April 2024 | Updated September 2026, 1 week ago
Powered by a #dualcore #RISCV CPU running up to 400 MHz, #ESP32P4 also supports single-precision #FPU and #AI extensions, thus providing all the necessary computational resources. In addition, ESP32-P4 integrates an #LPCore which can run up to 40 MHz.
The ESP32-P4 HP core system features 768 KB of on-chip #SRAM, which can be accessed as #cache when external #PSRAM is available. Additionally, the ESP32-P4 HP core system includes 8 KB of #zerowait #TCM #RAM.
To know more about the ESP32-P4, click on the below links:
Video: youtube.com/watch?v=GTHHDZeIzcA
Website: espressif.com/en/products/socs/esp32-p4
#Espressif #ESP32 #IoT #AIoT #embeddedsolutions
Powered by a #dualcore #RISCV CPU running up to 400 MHz, #ESP32P4 also supports single-precision #FPU and #AI extensions, thus providing all the necessary computational resources. In addition, ESP32-P4 integrates an #LPCore which can run up to 40 MHz.
The ESP32-P4 HP core system features 768 KB of on-chip #SRAM, which can be accessed as #cache when external #PSRAM is available. Additionally, the ESP32-P4 HP core system includes 8 KB of #zerowait #TCM #RAM.
To know more about the ESP32-P4, click on the below links:
Video: youtube.com/watch?v=GTHHDZeIzcA
Website: espressif.com/en/products/socs/esp32-p4
#Espressif #ESP32 #IoT #AIoT #embeddedsolutions







—into API calls needed to initialize the data model, encodes them to protobuf messages and stores it in a space-efficient format on the flash.
By design, this allows the application and the data model to be decoupled and stored independently. The repo also includes an IDF component that can read this serialized format and create the data model at runtime. However, the same format is usable across Matter implementations like Matter.js, rs-matter, Matter (CircuitPython) or Arduino Matter, eliminating the need for code generators to be developed for these languages.
The talk will provide an introduction to data models of IoT devices, how Matter approaches the data modeling problem, and how the Data Model Interpreter tools and components work. It will also cover the potential use cases.
Speakers: Dhaval Gujar and Amit Sheth DevCon25 - Runtime Data Model Interpreter for Connected Devices](https://i.ytimg.com/vi/UmZA3k8RDXU/mqdefault.jpg)


