Single Precision Support #458
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Control for pip builds from env var.
ax3l
added
bug
And annotate harder issues in AoS.
SP has some detailed padding before `idcpu` and at the end of each particle, if they do not align with the size of `double`.
Importing into pandas does not support binary fields, but there is no quick way to remove them.
| # print('particle 2 from aos:\n',aos[1]) | ||
| # print('array interface\n', aos.__array_interface__) | ||
| arr = aos.to_numpy() | ||
| int_arg = 7 if arr[0][0].dtype == "float32" else 6 # padding |
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Is this something that users will have to know, that there might be this extra padding element so the indices for the integers might be shifted?
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I fear so... I have not found a way to kick out numpy struct elements (in the SP case: the paddings) without doing a copy yet.
That said, nobody should use AoS anymore in AMReX. I am inclined to drop all support for it in pyAMReX to stop wasting time :)
| }/* | ||
| if constexpr (ParticleType::NInt % 2 != 0) { // alignas | ||
| descr.append(py::make_tuple("", "|V4")); // empty space due to alignment | ||
| }*/ |
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Adding this end-of-particle padding after the int (32bit) array fails both the double precision tests o.0
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There seems to be a follow-up issue in SP in ImpactX (which uses pure SoA particle layout) for Note the PR here just works around AoS stuff (legacy). |
For AoS and SoA `.to_numpy()` and dependent logic like `.to_df()`, the lifetime of the temporary copied variable is only handled by NumPy if we first create a named variable. The `to_host()` returned object is a temporary, and `np.array` using the `__array_interface__` protocol does not keep it alive automatically unless it is stored in an actual variable (eg., `tmp`). X-ref: - conda-forge/impactx-feedstock#56 (comment) - #458 (comment)
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setup.pyAs a follow-up, one could add support for SP
.to_df()by removing binary columns (members) from the AoS before passing it into Pandas. But this legacy layout is not our need or focus, nor worth spending more time on.