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Precision change improvements

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Added a new, much faster implementation of precision change that uses (optionally) a precomputed workspace containing pointer offsets that is device resident, such that all lattice copying occurs only on the device and no host<->device transfer is required, other than the pointer table. It also avoids the need to unpack and repack the fields using explicit lane copying. When this new precisionChange is called without a workspace, one will be computed on-the-fly; however it is still considerably faster than the original implementation.

In the special case of using double2 and when the Grids are the same, calls to the new precisionChange will automatically use precisionChangeFast, such that there is a single API call for all precision changes.

Reliable update and mixed-prec multishift have been modified to precompute precision change workspaces

Renamed the original precisionChange as precisionChangeOrig

Fixed incorrect pointer offset bug in copyLane

Added a test and a benchmark for precisionChange

Added a test for reliable update CG
This commit is contained in:
Christopher Kelly
2023-02-21 10:52:42 -05:00
parent 472ed2dd5c
commit 1db58a8acc
7 changed files with 616 additions and 16 deletions
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Grid/tensors/Tensor_extract_merge.h
+3 -3
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@@ -226,7 +226,7 @@ template<class vobjOut, class vobjIn>
accelerator_inline
void copyLane(vobjOut & __restrict__ vecOut, int lane_out, const vobjIn & __restrict__ vecIn, int lane_in)
{
static_assert( std::is_same<typename vobjOut::DoublePrecision, typename vobjIn::DoublePrecision>::value == 1, "copyLane: tensor types must be the same" ); //if tensor types are same the DoublePrecision type must be the same
static_assert( std::is_same<typename vobjOut::scalar_typeD, typename vobjIn::scalar_typeD>::value == 1, "copyLane: tensor types must be the same" ); //if tensor types are same the DoublePrecision type must be the same
typedef typename vobjOut::vector_type ovector_type;
typedef typename vobjIn::vector_type ivector_type;
@@ -251,9 +251,9 @@ void copyLane(vobjOut & __restrict__ vecOut, int lane_out, const vobjIn & __rest
ovector_type * __restrict__ op = (ovector_type *)&vecOut;
ivector_type * __restrict__ ip = (ivector_type *)&vecIn;
for(int w=0;w<owords;w++){
itmp = ip[iNsimd*w].getlane(lane_in);
itmp = ip[w].getlane(lane_in);
otmp = itmp; //potential precision change
op[oNsimd*w].putlane(otmp,lane_out);
op[w].putlane(otmp,lane_out);
}
}