NVIDIA / NVIDIA/cuda-quantum

Serialization and deserialization of kernel

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enhancement stale-notified
Dominant language
C++
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Forks
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Avg merge
1d 22h
Merged PRs (30d)
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Description

Required prerequisites
  • Search the issue tracker to check if your feature has already been mentioned or rejected in other issues.
Describe the feature

The ability to save and load the kernel is needed.

The use case is, for example, to save kernels, used as a cache, or broadcast with MPI.
There are many ways to implement this: QASM3, some MLIR, or even the original format.

Requirements

  • not only Python but also C++
  • Backward compatibility, i.e., you can load a saved kernel from a future version

Reference: CUDA has JIT feature and it can be stored.

Deserialization is related to https://github.com/NVIDIA/cuda-quantum/issues/755

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

No source files or tests are named. Start by reviewing issue 755 and the linked CUDA NVRTC and Jitify references, then identify the existing kernel representations and APIs for both C++ and Python. Done means an agreed serialization approach supports saving and loading in both languages with the requested backward-compatibility guarantees.

Written by the indexing model from the issue text.

Assessment

Tech stack
cpp, python
Domain
backend-api-design
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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