[cudaq.run] Current cudaq.run issues
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- Dominant language
- C++
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Description
Tuples:
- Disable for current release:
https://github.com/NVIDIA/cuda-quantum/pull/3032
Issues
-
Spec is needed for tuples in python kernels
https://github.com/NVIDIA/cuda-quantum/issues/3031 -
Incorrect IR generated for updating tuple elements
https://github.com/NVIDIA/cuda-quantum/issues/2965
https://github.com/NVIDIA/cuda-quantum/pull/3002 -
Tuple re-assigment does not work in kernels
https://github.com/NVIDIA/cuda-quantum/issues/3015 -
Tuple unpacking cause and assertion error
https://github.com/NVIDIA/cuda-quantum/issues/3029
Lists/vectors
- Disable support for vectors for the current release
c++: https://github.com/NVIDIA/cuda-quantum/pull/3010
python: https://github.com/NVIDIA/cuda-quantum/pull/3050
Issues
-
Returning vectors generates a malloc call on quantum devices
https://github.com/NVIDIA/cuda-quantum/issues/2964 -
ReturnToOutputLog only handles constant lists
https://github.com/NVIDIA/cuda-quantum/issues/2963 -
Malloc function is not included in module on remote simulators
https://github.com/NVIDIA/cuda-quantum/issues/3012
Structs/dataclasses:
Issues
- Incorrect quake for updating elements of struct in python
https://github.com/NVIDIA/cuda-quantum/issues/2966
https://github.com/NVIDIA/cuda-quantum/pull/3000
Run_async
Issues
- Run async should not call
pyAltLaunchKernelwith no return type (causes seg faults)
https://github.com/NVIDIA/cuda-quantum/issues/2984
https://github.com/NVIDIA/cuda-quantum/pull/3074
C++-only
Issues
- Results are not produces due to early inlining in nvqc++
https://github.com/NVIDIA/cuda-quantum/issues/3037
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
This issue is a tracker for cudaq.run problems rather than a self-contained change. Start with the linked unresolved issues, especially the tuple, vector, and run_async entries, and read their linked pull requests where present. Done means the selected underlying issues are resolved and the checklist is updated.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp, python
- Domain
- backend, compilers
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100