No configuration effort. Link code and data. Watch your model being trained.
Download our agent, install it on your machines and link them to your workspace on our platform.
Having configured runtime frameworks, just link your code, data and run the experiment.
Run your code with different parameters on multiple GPUs. When satisfied train your model in distributed context.
Deepstributed lets you – as a Machine Learning Engineer – to run any experiments in a way you always wanted. You start with one code with various hyperparameters on many machines, and then you execute the most probable one in a distributed environment.
What is more, you can use our preconfigured computing scenarios so you do not have to configure anything when – for example – running the Tensorflow distributed experiment.
Deepstributed alows you to join your code, hyperparameteres,
data sets and models in one place. We are giving you the tools
to manage you experiments: setting them up, queueing, parameterising, iterationing and disitributing over many GPUs.
We let you add your own GPUs to our platform. You can run your experiments on them and when it is not used you can share them among other MLEs.
If you need more for your experiment you reach out for the community supplies or buy additional ones from GPUaaS providers.
When your GPU resources do not work for your experiment you can share them with other MLEs. We will pay you for every minute of your precious cards working for the community.
See some of their testimonials here
I cannot even count the amount of time we have saved with Deepstributed. This is the tool you were always thinking about and never had the courage to think someone is going to actually build it.
As Deepstributed is in the early stage of development, we can afford to give away the access only for the limited group of users. Please, write us and try to describe your company, your role and the way you want to use our platform.
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Deepstributed Ltd.
MassChallenge Switzerland
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Deepstributed Sp. z o.o.
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54-413 Wrocław, PL