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What do you recommend would be the best approach for this stencil on a Xeon Phi? The idea is:

Given a 1-D array A: [0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18]

And three scalars: probUp, probMid, probDown

You need to compute a 1-D array B where:

B[0] = probDown*A[0] + probMid*A[1] + probUp*A[2]

B[1] = probDown*A[1] + probMid*A[2] + probUp*A[3]

B[2] = probDown*A[2] + probMid*A[3] + probUp*A[4]

etc…

Everything is double precision.

The approach I’m going with is to load three vector registers, a0, a1, and a2 (where a0 is aligned to the loop iterator, a1 is shifted by 1 element, and a2 is shifted by 2 elements), do muls and fmadds to smoosh them together with the scalars, and then store.

The only question I guess I have is what would they say the most efficient way is to get the a* vector registers loaded from memory. I’m pretty sure it’s best to do two loads and some shifts (as I’m doing below) as opposed to doing unaligned loads or using gather intrinsics, but I’d be curious if Intel has a different opinion.

- Tags:
- Parallel Computing

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Seems reasonable. You could write c or Fortran with alignment assertions

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The posted papers discussing -qopt-assume-safe-padding are relevant. Compilers use gather and scatter to access partial cache lines only to prevent possible unsafe access outside the array. Unaligned access may be the slowest.

You might get attention from experts if you would ask on the Intel Xeon phi forum.

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