Skip to content

Community Programs

Last updated: Nov 3, 2019

Limited Free Access for Academic Users

The Free Access Program completed in May of 2020.

The last Free Access Program completed as of 2020/05. Users are still welcome to submit their information for any future similar programs.

For users with current academic affiliation we can provide computational resources free of charge on a case-by-case basis.

Applying for Limited Free Access

As below:

  1. Fill in this online form
  2. For new users - submit a registration request using an email address associated with your academic institution include the information requested in 3.
  3. For existing users - if you use a personal email address during the registration, send an email to "support@exabyte.io" from the email address associated with your academic institution (ie. hosted on a ".edu" domain) with a subject containing "Free Access for Academic Users"

we will review and enable access as appropriate. We will prioritize applications providing detailed information about the applicants (ie. Google Scholar, ResearchGate profile(s), links to prior publications) and the nature of the anticipated work.

Conditions

Free access is limited to certain compute resources only and is subject to other limitations as below. We will consider adjusting the limitations according to the user feedback received. Contact "support@exabyte.io" for this.

Limitations

Feature Explanation
Max nodes per job 1
Max cores per job 4
Max job walltime 24 hours
Max job queued per user 4
Available Queues "D" only
Available Resources "cluster-009" only
Included Disk Quota 10 Gb

Acknowledgements

Any/all published work derived from the Limited Free Access program must include the following Acknowledgement text and citation below.

Acknowledgement text

The authors performed this work partially or in full using the Exabyte.io 
platform, a web-based computational ecosystem for the development of new 
materials and chemicals [REFERENCE TO THE BELOW CITATION].

Citation

Timur Bazhirov, "Data-centric online ecosystem for digital materials science", 
arxiv.org preprint, 2019, https://arxiv.org/abs/1902.10838

In Bibtex format:

@article{Exabyte.io-Platform-Reference,
    title={Data-centric online ecosystem for digital materials science},
    author={Bazhirov, Timur},
    journal={arxiv.org/abs/1902.10838},
    year={2019},
}

Publicity

We plan to select some of the work performed under the Limited Free Access program to be highlighted in the online publication sources together with the cloud provider(s) enabling the computational infrastructure.

Reach out to us

We are friendly people like you, why not reach out to us with your suggestions and ideas? You may contact us at info@exabyte.io. If you are interested in joining our team, write to hi@exabyte.io with your resume and cover letter.