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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better esp-nn alternative or higher similarity.
esp-nn reviews and mentions
Posts with mentions or reviews of esp-nn.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-01-16.
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TinyML: Ultra-low power Machine Learning
There are a range of ML acceleration possible on existing chips. The basic 4-wide 8 bit integer SIMD extensions in NEON is available on basically all ARM Cortex M4F chips, which is already available 8+ years. It gives 4-5x speedup for neural networks.
The more recent ESP32-S3 has operations with up to 10x speedup, see https://github.com/espressif/esp-nn
Then there are RISCV chips with neural network co processors like Kendryte K210.
ARM has also defined a new set of extensions for NN acceleration, and reference designs for cores being ARM Cortex M85. Chips are becoming available this year.
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[Discussion] Best practices for taking deep learning models to bare metal MCUs
https://github.com/espressif/esp-nn https://github.com/espressif/tflite-micro-esp-examples
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Ask HN: What Are You Working on This Year?
The ESP32-S3 introduces vector instructions which are supported by TFLite already. See here - https://github.com/espressif/esp-nn#performance
S3 also supports Octal PSRAM vs the single lane SPI PSRAM found on the older ESP32-CAM style boards, should be 8x the bandwidth with all else equal. So far I've only seen the octal PSRAM's available on WROOM modules and it looks likes there only support for Espressif branded Octal PSRAM chips at this point.
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A note from our sponsor - WorkOS
workos.com | 26 Apr 2024
Stats
Basic esp-nn repo stats
3
111
4.7
7 months ago
espressif/esp-nn is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of esp-nn is Assembly.
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