Perf imp for cudaq decoders#42
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sacpis
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Apr 3, 2026
sacpis
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- This change replaces the per-sample decode loop with a single decode_batch call when the decoder supports it. This reduces the Python to C++ overhead from B calls to just 1.
- In both _decode_cudaq_batch and _decode_ldpc_batch APIs, observable projection is now a single batched matrix multiplication instead of B separate scalar dot products. This eliminates the per-sample loop overhead.
…le projection Signed-off-by: Sachin Pisal <spisal@nvidia.com>
Signed-off-by: Sachin Pisal <spisal@nvidia.com>
ivanbasov
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Apr 3, 2026
ivanbasov
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Apr 3, 2026
Signed-off-by: Sachin Pisal <spisal@nvidia.com>
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Thank you @ivanbasov for reviewing this PR. Have addressed the feedback. |
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Thank you, @sacpis ! Looks good. We are freezing code now for a QA review. |
ivanbasov
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Apr 7, 2026
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* adding decode_batch path in failure_analysis and vectorizing observable projection Signed-off-by: Sachin Pisal <spisal@nvidia.com> * pass syndromes as list-of-lists to cudaq decode_batch Signed-off-by: Sachin Pisal <spisal@nvidia.com> * implementing feedback Signed-off-by: Sachin Pisal <spisal@nvidia.com> --------- Signed-off-by: Sachin Pisal <spisal@nvidia.com>
ivanbasov
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Apr 10, 2026
* adding decode_batch path in failure_analysis and vectorizing observable projection Signed-off-by: Sachin Pisal <spisal@nvidia.com> * pass syndromes as list-of-lists to cudaq decode_batch Signed-off-by: Sachin Pisal <spisal@nvidia.com> * implementing feedback Signed-off-by: Sachin Pisal <spisal@nvidia.com> --------- Signed-off-by: Sachin Pisal <spisal@nvidia.com>
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