This library has some minor support for GPU acceleration already, mostly focusing on mctrajectory and apply!.
This bounty is for translating that existing support to KernelAbstractions (while keeping the CUDA backend) and updating the test suite so that both the CUDA and KernelAbstractions can be tested. This bounty includes the requirement to make some benchmark plots to see whether the KernelAbstractions backend is much slower than the CUDA backend.
A lot of follow-up work can happen building upon this bounty, adding many other capabilities.
Required skills: Understanding of the stabilizer formalism. Knowledge of GPU programming
Reviewer: Stefan Krastanov
Duration: 1 month
Payout procedure:
The Funding for these bounties comes from the National Science Foundation and from the NSF Center for Quantum Networks. The payouts are managed by the NumFOCUS foundation and processed in bulk once every two months. If you live in a country in which NumFOCUS can make payments, you can participate in this bounty program.
Bug bounty logistic details (click to expand)
To claim exclusive time to work on this bounty either post a comment here or message [skrastanov@umass.edu](mailto:skrastanov@umass.edu) with:
- your name
- github username
- **(optional)** a brief list of previous pertinent projects you have engaged in
Currently the project is claimed by `no one` until `...`.
If you want to, you can work on this project without making a claim, however claims are encouraged to give you and other contributors peace of mind. Whoever has made a claim takes precedence when solutions are considered.
You can always propose your own funded project, if you would like to contribute something of value that is not yet covered by an official bounty.
abanerg
commented
6 days ago
This library has some minor support for GPU acceleration already, mostly focusing on
mctrajectoryandapply!.This bounty is for translating that existing support to KernelAbstractions (while keeping the CUDA backend) and updating the test suite so that both the CUDA and KernelAbstractions can be tested. This bounty includes the requirement to make some benchmark plots to see whether the KernelAbstractions backend is much slower than the CUDA backend.
A lot of follow-up work can happen building upon this bounty, adding many other capabilities.
Required skills: Understanding of the stabilizer formalism. Knowledge of GPU programming
Reviewer: Stefan Krastanov
Duration: 1 month
Payout procedure:
The Funding for these bounties comes from the National Science Foundation and from the NSF Center for Quantum Networks. The payouts are managed by the NumFOCUS foundation and processed in bulk once every two months. If you live in a country in which NumFOCUS can make payments, you can participate in this bounty program.
Click here for more details about the bug bounty program.
Bug bounty logistic details (click to expand)
To claim exclusive time to work on this bounty either post a comment here or message [skrastanov@umass.edu](mailto:skrastanov@umass.edu) with: - your name - github username - **(optional)** a brief list of previous pertinent projects you have engaged in Currently the project is claimed by `no one` until `...`. If you want to, you can work on this project without making a claim, however claims are encouraged to give you and other contributors peace of mind. Whoever has made a claim takes precedence when solutions are considered. You can always propose your own funded project, if you would like to contribute something of value that is not yet covered by an official bounty.