EDA@TUM (tum-ei-eda)

EDA@TUM

tum-ei-eda

Geek Repo

Open Source Repository of the ESL Group of the Chair of Electronic Design Automation, TU Munich

Location:Munich, Germany

Home Page:https://www.ce.cit.tum.de/en/eda/research/electronic-system-level/

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EDA@TUM's repositories

VPV-Peripherals

Library of example SystemC/TLM peripherals for various SoCs based on the SCS library

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utvm_staticrt_codegen

This project contains a code generator that produces static C NN inference deployment code targeting tiny micro-controllers (TinyML) as replacement for other µTVM runtimes. This tools generates a runtime, which statically executes the compiled model. This reduces the overhead in terms of code size and execution time compared to having a dynamic on-device runtime.

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tensorflow

An Open Source Machine Learning Framework for Everyone

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rvv-gauss-demo

RISC-V Vector Extension v0.9 (RVV0.9) accelerated Gaussian Elimination for post-quantum McEliece cryptosystems.

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stm32-tflm-mnist

Implementation of `mnist` TFLM example running on STM32 Boards

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stm32-tflm-micro-speech

Implementation of `micro_speech` TFLM example running on STM32 Boards

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stm32-tflm-hello-world

Hello world TFLM example for STM32 boards

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stm32-tflm-cmake

Cmake modules for STM32, specifically for TFLM applications

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stm32-tflm-demos

Tiny machine learning demos for STM32 microcontrollers

License:GPL-3.0Stargazers:6Issues:0Issues:0

TinyML-Examples

Collection of TinyML benchmark NN models (in the making)

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riscv-binutils-gdb

RISC-V backports for binutils-gdb. Development is done upstream at the FSF.

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TinyML-MicroSpeech-Example

MicroSpeech example from the TinyML book

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tflite_micro_compiler

generate tflite micro code which bypasses the interpreter (directly calls into kernels)

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uTensor

AI inference library based on mbed and TensorFlow

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tflm-offline-interpreter

This project runs the TFLM interpreter off-target to produce static code that is able to run inference on the processed model. This avoids interpretation and code size overheads on a target that does not need to process different models dynamically.

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CMSIS_5

CMSIS Version 5 Development Repository

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