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Can we add some of the NVIDIA simulators to the OpenQAOA stack? NVIDIA's cuQuantum SDK provides users with quantum circuit simulation tools:
cuStateVec: a library for state vector computations
cuTensorNet: a library for tensor network computations
Integrating these tools with our stack would be helpful to implement tensor network simulations or simply make use of the high-performance simulators.
Changes to be made
In the same way we implemented different backends (physical QPU or simulators), implement a plugin package openqaoa-nvidia that allows execution on NVIDIA's backend. More specifically, changes include:
Creation of a new plugin openqaoa-nvidia including all necessary components (e.g. setup.py, pyproject.toml, etc...).
Creation of a openqaoa-nvidia/backend equivalent, bridging the stack's internal representation to one compatible with NVIDIA's SDK.
Creation of unit tests to make sure all features are correctly supported.
The text was updated successfully, but these errors were encountered:
Hi, I would like to work on this enhancement. Can you please direct towards a plugin template used in your code that closely resembles the kind of components required for this.
You can find examples of such backends in the other plugins already implemented, e.g. openqaoa-azure, openqaoa-braket, openqaoa-qiskit, and openqaoa-pyquil. All plugins have a /backends/ folder where you can find:
device.py containing the information to access the specific provider's devices (qpu or sim, local or remote).
gates_*.py that contains the mapping between openqaoa's abstract gate representation and the provider's gates.
qaoa_*_qpu/sim.py that describes the creation of a QAO object on the specific backend.
Finally there is also a backend configuration file in the root folder of the plugin to describe how everything is mapped to the core library of openqaoa.
You can always refer to the existing plugins for the implementation of this new backend.
Hope that helps!
Issue Description
Can we add some of the NVIDIA simulators to the OpenQAOA stack?
NVIDIA's cuQuantum SDK provides users with quantum circuit simulation tools:
Integrating these tools with our stack would be helpful to implement tensor network simulations or simply make use of the high-performance simulators.
Changes to be made
In the same way we implemented different backends (physical QPU or simulators), implement a plugin package
openqaoa-nvidia
that allows execution on NVIDIA's backend. More specifically, changes include:openqaoa-nvidia
including all necessary components (e.g.setup.py
,pyproject.toml
, etc...).openqaoa-nvidia/backend
equivalent, bridging the stack's internal representation to one compatible with NVIDIA's SDK.The text was updated successfully, but these errors were encountered: