UPMEM-MLP

UPMEM-MLP implements a multilayer perceptron training application in C and accelerates this application on the UPMEM platform.

Prerequisites

• CMake 3.10 or higher
• GCC
• Python
• UPMEM SDK

Installing UPMEM SDK

1. Download UPMEM SDK tarball for your system from this link

NOTICE: UPMEM SDK is no longer downloadable on UPMEM's official SDK Downloads page.

2. Extract its content and (preferably) move it to a better place like /usr/local/bin/

3. Add the shell script upmem_env.sh, which sets necessary environment variables, to be sourced into your .bashrc:

source /usr/local/bin/upmem-sdk/upmem_env.sh simulator > /dev/null

4. Restart your shell session for the changes to become effective

5. Test your setup:

which dpu-lldb

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Getting Started

1. Clone this repository and navigate inside it:

git clone https://github.com/OpenHardware-Initiative/UPMEM-MLP.git
cd UPMEM-MLP

2. (Optional, but recommended) Create a Python virtual environment:

python3 -m venv venv
source venv/bin/activate

3. Install Python requirements:

pip install -r requirements.txt

4. Extract training samples & labels:

python3 read_dataset.py

5. Compile the MLP:

make

6. Run the MLP:

./build/mlp

With this command, you can use:

• BATCH_SIZE=... to configure the batch size used during training, which otherwise defaults to 20
• MAX_EPOCH=... to configure the maximum number of epochs the training can run for, which otherwise defaults to 10
• NUM_TRAIN_SAMPLES=... to configure from the command line how many samples the model should be trained with, which otherwise defaults to 200
• UPMEM=0 to turn off matrix multiplication on UPMEM
• SAN=1 to run the MLP with GCC sanitizer
• EVAL=1 to run the MLP in evaluation mode, which adds to the printout how many cycles are spent in training

Running the Unit Tests

UPMEM-MLP comes with unit tests, which can be found in tests/. Run these unit tests using:

mkdir build
cd build
cmake ..
make
make test

Status

UPMEM-MLP is completed and being actively maintained as of 2025-11-23.

License

UPMEM-MLP is licensed under the Apache License v2.0. See LICENSE for more details.

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