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Description
I have a rather open ended question regarding usage
I want to go up to a large number of derivative orders considering that I'm mainly interested in capturing the operator spectra. Here's an example I'm taking for the 2d ising case, dim=2.01, k =26, l =25, n = 30, m = 20. I'm just starting out with testing spectrum extraction with SDP on this case so I'm a bit unsure about how I should manage the parameter besides trying to maximize the number of derivatives. This seems to take quite a bit of time running on a single thread.
Is there any way to get the block calculations in PYCFTBoot to use multiple threads. Have there been points identified for parallelizing using say something like the multiprocessing library in python. I know that SDPB can be made faster by specifying the number of threads but that is not my rate limiting step here.