Circuit library modernization #13046
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mod: circuit
Related to the core of the `QuantumCircuit` class or the circuit library
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Cryoris
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Hi @MozammilQ, it's great to see you're interested! We would like to have some PRs done by the dev team first to figure out the details and have some examples ready. Once that's done it you're very welcome to help 🙂 |
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@Cryoris, I would be interested in implementing a multitude of quantum arithmetic circuits for synthesis. When the time is right please let me know. Qiskit team should also decide if they really want these circuits as part of the core library or not. |
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This commit adds a new function quantum_volume used for generating a quantum volume model circuit. This new function is defined in Rust and multithreaded to improve the throughput of the circuit generation. This new function will eventually replace the existing QuantumVolume class as part of Qiskit#13046. Since quantum volume is a circuit defined by it's structure using a generator function is inline with the goals of Qiskit#13046. Right now the performance is bottlenecked by the creation of the UnitaryGate objects as these are still defined solely in Python. We'll likely need to port the class to have a rust native representation to further speed up the construction of the circuit.
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* Add Rust quantum volume function This commit adds a new function quantum_volume used for generating a quantum volume model circuit. This new function is defined in Rust and multithreaded to improve the throughput of the circuit generation. This new function will eventually replace the existing QuantumVolume class as part of #13046. Since quantum volume is a circuit defined by it's structure using a generator function is inline with the goals of #13046. Right now the performance is bottlenecked by the creation of the UnitaryGate objects as these are still defined solely in Python. We'll likely need to port the class to have a rust native representation to further speed up the construction of the circuit. * Adjust type hints on python function Co-authored-by: Julien Gacon <[email protected]> * Add missing __future__ import The previous commit was relying on the behavior of the annotations future import but neglected to add it. This commit corrects the oversight. * Add comment on random unitary algorithm * Reduce allocations random_unitaries The previous implementation had 4 heap allocations for each random unitary constructed, this commit uses some fixed sized stack allocated arrays and reduces that to two allocations one for q and r from the factorization. We'll always need at least one for the `Array2` that gets stored in each `UnitaryGate` as a numpy array. But to reduce to just this we'll need a method of computing the QR factorization without an allocation for the result space, nalgebtra might be a path for doing that. While this currently isn't a bottleneck as the `UnitaryGate` python object creation is the largest source of runtime, but assuming that's fixed in the future this might have a larger impact. * Preallocate unitaries for serial path When executing in the serial path we previously were working directly with an iterator where the 2q unitaries we're created on the iterator that we passed directly to circuit constructor. However testing shows that precomputing all the unitaries into a Vec and passing the iterator off of that to the circuit constructor is marginally but consistently faster. So this commit pivots to using that instead. * Fix determinism and error handling of of qv function This commit fixes two issues in the reproducibility of the quantum volume circuit. The first was the output unitary matrices for a fixed seed would differ between the parallel and serial execution path. This was because how the RNGs were used was different in the different code paths. This change results in the serial path being marginally less efficient, but it shouldn't be a big deal when compared to getting different results in different contexts. The second was the seed usage in parallel mode was dependent on the number of threads on the local system. This was problematic because the exact circuit generated between two systems would be different even with a fixed seed. This was fixed to avoid depending on the number of threads to determine how the seeds were used across multiple threads. The last fix here was a change to the error handling so that the CircuitData constructor used to create the circuit object can handle a fallible iterator. Previously we were throwing away the python error and panicking if the Python call to generate the UnitaryGate object raised an error for any reason. * Mention the new function is multithreaded in docstring * Update qiskit/circuit/library/quantum_volume.py Co-authored-by: Julien Gacon <[email protected]> --------- Co-authored-by: Julien Gacon <[email protected]> Co-authored-by: Julien Gacon <[email protected]>
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* Add Rust quantum volume function This commit adds a new function quantum_volume used for generating a quantum volume model circuit. This new function is defined in Rust and multithreaded to improve the throughput of the circuit generation. This new function will eventually replace the existing QuantumVolume class as part of Qiskit#13046. Since quantum volume is a circuit defined by it's structure using a generator function is inline with the goals of Qiskit#13046. Right now the performance is bottlenecked by the creation of the UnitaryGate objects as these are still defined solely in Python. We'll likely need to port the class to have a rust native representation to further speed up the construction of the circuit. * Adjust type hints on python function Co-authored-by: Julien Gacon <[email protected]> * Add missing __future__ import The previous commit was relying on the behavior of the annotations future import but neglected to add it. This commit corrects the oversight. * Add comment on random unitary algorithm * Reduce allocations random_unitaries The previous implementation had 4 heap allocations for each random unitary constructed, this commit uses some fixed sized stack allocated arrays and reduces that to two allocations one for q and r from the factorization. We'll always need at least one for the `Array2` that gets stored in each `UnitaryGate` as a numpy array. But to reduce to just this we'll need a method of computing the QR factorization without an allocation for the result space, nalgebtra might be a path for doing that. While this currently isn't a bottleneck as the `UnitaryGate` python object creation is the largest source of runtime, but assuming that's fixed in the future this might have a larger impact. * Preallocate unitaries for serial path When executing in the serial path we previously were working directly with an iterator where the 2q unitaries we're created on the iterator that we passed directly to circuit constructor. However testing shows that precomputing all the unitaries into a Vec and passing the iterator off of that to the circuit constructor is marginally but consistently faster. So this commit pivots to using that instead. * Fix determinism and error handling of of qv function This commit fixes two issues in the reproducibility of the quantum volume circuit. The first was the output unitary matrices for a fixed seed would differ between the parallel and serial execution path. This was because how the RNGs were used was different in the different code paths. This change results in the serial path being marginally less efficient, but it shouldn't be a big deal when compared to getting different results in different contexts. The second was the seed usage in parallel mode was dependent on the number of threads on the local system. This was problematic because the exact circuit generated between two systems would be different even with a fixed seed. This was fixed to avoid depending on the number of threads to determine how the seeds were used across multiple threads. The last fix here was a change to the error handling so that the CircuitData constructor used to create the circuit object can handle a fallible iterator. Previously we were throwing away the python error and panicking if the Python call to generate the UnitaryGate object raised an error for any reason. * Mention the new function is multithreaded in docstring * Update qiskit/circuit/library/quantum_volume.py Co-authored-by: Julien Gacon <[email protected]> --------- Co-authored-by: Julien Gacon <[email protected]> Co-authored-by: Julien Gacon <[email protected]>
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* Add Rust quantum volume function This commit adds a new function quantum_volume used for generating a quantum volume model circuit. This new function is defined in Rust and multithreaded to improve the throughput of the circuit generation. This new function will eventually replace the existing QuantumVolume class as part of Qiskit#13046. Since quantum volume is a circuit defined by it's structure using a generator function is inline with the goals of Qiskit#13046. Right now the performance is bottlenecked by the creation of the UnitaryGate objects as these are still defined solely in Python. We'll likely need to port the class to have a rust native representation to further speed up the construction of the circuit. * Adjust type hints on python function Co-authored-by: Julien Gacon <[email protected]> * Add missing __future__ import The previous commit was relying on the behavior of the annotations future import but neglected to add it. This commit corrects the oversight. * Add comment on random unitary algorithm * Reduce allocations random_unitaries The previous implementation had 4 heap allocations for each random unitary constructed, this commit uses some fixed sized stack allocated arrays and reduces that to two allocations one for q and r from the factorization. We'll always need at least one for the `Array2` that gets stored in each `UnitaryGate` as a numpy array. But to reduce to just this we'll need a method of computing the QR factorization without an allocation for the result space, nalgebtra might be a path for doing that. While this currently isn't a bottleneck as the `UnitaryGate` python object creation is the largest source of runtime, but assuming that's fixed in the future this might have a larger impact. * Preallocate unitaries for serial path When executing in the serial path we previously were working directly with an iterator where the 2q unitaries we're created on the iterator that we passed directly to circuit constructor. However testing shows that precomputing all the unitaries into a Vec and passing the iterator off of that to the circuit constructor is marginally but consistently faster. So this commit pivots to using that instead. * Fix determinism and error handling of of qv function This commit fixes two issues in the reproducibility of the quantum volume circuit. The first was the output unitary matrices for a fixed seed would differ between the parallel and serial execution path. This was because how the RNGs were used was different in the different code paths. This change results in the serial path being marginally less efficient, but it shouldn't be a big deal when compared to getting different results in different contexts. The second was the seed usage in parallel mode was dependent on the number of threads on the local system. This was problematic because the exact circuit generated between two systems would be different even with a fixed seed. This was fixed to avoid depending on the number of threads to determine how the seeds were used across multiple threads. The last fix here was a change to the error handling so that the CircuitData constructor used to create the circuit object can handle a fallible iterator. Previously we were throwing away the python error and panicking if the Python call to generate the UnitaryGate object raised an error for any reason. * Mention the new function is multithreaded in docstring * Update qiskit/circuit/library/quantum_volume.py Co-authored-by: Julien Gacon <[email protected]> --------- Co-authored-by: Julien Gacon <[email protected]> Co-authored-by: Julien Gacon <[email protected]>
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Summary
Modernize the circuit library to improve compiler quality and construction speed. The library circuits are classified in two categories:
Instruction/Gateobjects with a detached synthesis, that the compiler can reason about.Examples: QFT, Pauli evolutions, arithmetic circuits, MCX gates.
QuantumCircuit.Examples: n-local circuits, quantum volume
Changes are to be pending-deprecated for 1.3, deprecated for 1.4 and finalized for 2.0.
Examples
The move to abstract blocks allows the compiler to reason about the circuit building blocks, where previously there was an eager construction:
Python functions can be used as drop-in replacement,
but can enable performance-improvements, e.g. by directly composing onto output circuits.
Abstract blocks
Structural circuits
Performance
PauliEvolutionGatefor Rustiq & port it to Rust #13295The text was updated successfully, but these errors were encountered: