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Compared to the BQM solver in HSS, ParallelTempering is very slow. I've attached a Python program for observing this, including a DQM from Accenture.
import hybrid from dimod import BinaryQuadraticModel bqm = ... main = hybrid.reference.HybridizedParallelTempering(num_replicas=10, max_iter=None, max_time=None, convergence=3, num_sweeps=10000) init_state = hybrid.State.from_sample(hybrid.utils.min_sample(bqm), bqm) solution = main.run(init_state).result().samples.first print(solution)
I have observed output like this:
real 1m16.454s user 1m25.997s sys 0m2.610s
whereas BQM solver in HSS requires times like this:
real 0m11.247s user 0m1.875s sys 0m0.573s
I will send the BQM in a file to @randomir; I don't know yet how to clip a very long string into Github Markdown.
The text was updated successfully, but these errors were encountered:
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Compared to the BQM solver in HSS, ParallelTempering is very slow. I've attached a Python program for observing this, including a DQM from Accenture.
I have observed output like this:
whereas BQM solver in HSS requires times like this:
I will send the BQM in a file to @randomir; I don't know yet how to clip a very long string into Github Markdown.
The text was updated successfully, but these errors were encountered: