# Training Microsoft's MatterGen model doesn't use GPUs

**URL:** <https://deeptalk.lambda.ai/t/training-microsofts-mattergen-model-doesnt-use-gpus/4681>\
**Category:** Technical Help\
**Created:** [July 2, 2025, 4:13pm UTC](https://deeptalk.lambda.ai/t/training-microsofts-mattergen-model-doesnt-use-gpus/4681 "2025-07-02T16:13:16Z")\
**Posts on this page:** 1\
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**Author:** ![wigging](https://sea1.discourse-cdn.com/flex019/user_avatar/deeptalk.lambda.ai/wigging/32/763_2.png) [@wigging](https://deeptalk.lambda.ai/u/wigging)\
**Post date:** [July 2, 2025, 4:13pm UTC](https://deeptalk.lambda.ai/t/training-microsofts-mattergen-model-doesnt-use-gpus/4681/1 "2025-07-02T16:13:16Z")

</div>

I’m trying to train Microsoft’s [mattergen](https://github.com/microsoft/mattergen) model using eight A100 GPUs on the Lambda Cloud. The instance type I used is `gpu_8x_a100_80gb_sxm4` and region is `us-east-1`. The Python version on the instance is `3.10.12`. Here are the details of the instance from the fastfetch tool:

```plaintext
                             .... ubuntu@xxx-xxx-xx-xxx
              .',:clooo: .:looooo:. ---------------------
           .;looooooooc .oooooooooo' OS: Ubuntu 22.04.5 LTS x86_64
        .;looooool:,''. :ooooooooooc Host: KVM/QEMU Standard PC (Q35 + ICH9, 2009) (pc-q35-8.0)
       ;looool;. 'oooooooooo, Kernel: Linux 6.8.0-52-generic
      ;clool' .cooooooc. ,, Uptime: 1 hour, 53 mins
         ... ...... .:oo, Packages: 1243 (dpkg), 6 (snap)
  .;clol:,. .loooo' Shell: bash 5.1.16
 :ooooooooo, 'ooool Terminal: /dev/pts/0
'ooooooooooo. loooo. CPU: 2 x AMD EPYC 7J13 64-Core (240) @ 2.45 GHz
'ooooooooool coooo. GPU 1: NVIDIA A100 SXM4 80GB
 ,loooooooc. .loooo. GPU 2: NVIDIA A100 SXM4 80GB
   .,;;;'. ;ooooc GPU 3: RedHat Virtio GPU
       ... ,ooool. GPU 4: NVIDIA A100 SXM4 80GB
    .cooooc. ..',,'. .cooo. GPU 5: NVIDIA A100 SXM4 80GB
      ;ooooo:. ;oooooooc. :l. GPU 6: NVIDIA A100 SXM4 80GB
       .coooooc,.. coooooooooo. GPU 7: NVIDIA A100 SXM4 80GB
         .:ooooooolc:. .ooooooooooo' GPU 8: NVIDIA A100 SXM4 80GB
           .':loooooo; ,oooooooooc GPU 9: NVIDIA A100 SXM4 80GB
               ..';::c' .;loooo:' Memory: 21.51 GiB / 1.73 TiB (1%)
                                               Swap: Disabled
                                               Disk (/): 32.86 GiB / 18.93 TiB (0%) - ext4
                                               Local IP (eno1): 10.19.89.112/20
                                               Locale: C.UTF-8

```

I had to install Git LFS] to train the MatterGen model. I used the commands shown below to install Git LFS on the instance.

```plaintext
sudo apt install git-lfs

git lfs install

```

I also installed [uv](https://docs.astral.sh/uv/) which is suggested in the MatterGen docs to setup the Python environment.

```plaintext
curl -LsSf https://astral.sh/uv/install.sh | sh

```

Next, I cloned the mattergen repository to the instance and followed the suggested steps for installation:

```plaintext
git clone https://github.com/microsoft/mattergen.git

cd mattergen

pip install uv

uv venv .venv --python 3.10 

source .venv/bin/activate

uv pip install -e .

```

I preprocessed the MP-20 dataset for training using the commands shown below.

```plaintext
git lfs pull -I data-release/mp-20/ --exclude=""

unzip data-release/mp-20/mp_20.zip -d datasets

csv-to-dataset --csv-folder datasets/mp_20/ --dataset-name mp_20 --cache-folder datasets/cache

```

After processing the dataset, I tried to train the model using the command shown below.

```plaintext
mattergen-train \
    data_module=mp_20 \
    ~trainer.logger \
    trainer.devices=8

```

On the Lambda Cloud instance, none of the GPUs are utilized during the training which I checked with `nvidia-smi`. The training uses 100% of the CPUs which I verified with `htop`. I tried this same procedure on a different system and mattergen was able to find and utilize the GPUs.

So is there something else I need to do for installing and training MatterGen on a Lambda Cloud instance? I know there is a Lambda Stack installed on the instances, but I don’t know how to install mattergen within this stack.

---

_[View the full topic](https://deeptalk.lambda.ai/t/training-microsofts-mattergen-model-doesnt-use-gpus/4681)._