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Lattice_reduction_gpu_cub: add GRID_REDUCTION_TIMING instrumentation

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Guards accelerator_for and CUB DeviceReduce calls in sumD_gpu_direct
and sumD_gpu_large with #ifdef GRID_REDUCTION_TIMING to isolate where
time is spent in each path. Large path accumulates across all groups
and prints totals with words/nfull/rem context.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Peter Boyle
2026-05-18 14:23:44 -04:00
parent dc6ae51cab
commit e12bc7f07c
1 changed files with 51 additions and 0 deletions
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Grid/lattice/Lattice_reduction_gpu_cub.h
+51
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@@ -64,11 +64,18 @@ inline typename vobj::scalar_objectD sumD_gpu_direct(const vobj *lat, Integer os
deviceVector<sobjD> per_site(osites);
sobjD *per_site_p = &per_site[0];
#ifdef GRID_REDUCTION_TIMING
RealD t_for = -usecond();
#endif
accelerator_for(ss, osites, 1, {
sobj tmp = Reduce(lat[ss]);
sobjD tmpD; tmpD = tmp;
per_site_p[ss] = tmpD;
});
#ifdef GRID_REDUCTION_TIMING
accelerator_barrier();
t_for += usecond();
#endif
sobjD zero; zeroit(zero);
sobjD *d_out = static_cast<sobjD *>(acceleratorAllocDevice(sizeof(sobjD)));
@@ -86,6 +93,9 @@ inline typename vobj::scalar_objectD sumD_gpu_direct(const vobj *lat, Integer os
d_temp = acceleratorAllocDevice(temp_bytes);
#ifdef GRID_REDUCTION_TIMING
RealD t_cub = -usecond();
#endif
gpuErr = gpucub::DeviceReduce::Reduce(d_temp, temp_bytes, per_site_p, d_out,
(int)osites, gpucub::Sum(), zero, computeStream);
if (gpuErr != gpuSuccess) {
@@ -95,6 +105,13 @@ inline typename vobj::scalar_objectD sumD_gpu_direct(const vobj *lat, Integer os
}
accelerator_barrier();
#ifdef GRID_REDUCTION_TIMING
t_cub += usecond();
std::cout << GridLogMessage << "sumD_gpu_direct"
<< " sizeof(sobjD)=" << sizeof(sobjD)
<< " accelerator_for=" << t_for << " us"
<< " CUB_reduce=" << t_cub << " us" << std::endl;
#endif
sobjD result;
acceleratorCopyFromDevice(d_out, &result, sizeof(sobjD));
@@ -147,9 +164,16 @@ inline typename vobj::scalar_objectD sumD_gpu_large(const vobj *lat, Integer osi
}
d_temp = acceleratorAllocDevice(temp_bytes);
#ifdef GRID_REDUCTION_TIMING
RealD t_for_large = 0.0, t_cub_large = 0.0;
#endif
// Full groups of 4 words.
for (int g = 0; g < nfull; g++) {
int base = 4 * g;
#ifdef GRID_REDUCTION_TIMING
t_for_large -= usecond();
#endif
accelerator_for(ss, osites, 1, {
R4 r4;
r4._internal[0] = TensorRemove(Reduce(idat[ss * words + base ]));
@@ -158,6 +182,11 @@ inline typename vobj::scalar_objectD sumD_gpu_large(const vobj *lat, Integer osi
r4._internal[3] = TensorRemove(Reduce(idat[ss * words + base + 3]));
buf_p[ss] = r4;
});
#ifdef GRID_REDUCTION_TIMING
accelerator_barrier();
t_for_large += usecond();
t_cub_large -= usecond();
#endif
gpuErr = gpucub::DeviceReduce::Reduce(d_temp, temp_bytes, buf_p, d_out,
(int)osites, gpucub::Sum(), zero4, computeStream);
if (gpuErr != gpuSuccess) {
@@ -166,6 +195,9 @@ inline typename vobj::scalar_objectD sumD_gpu_large(const vobj *lat, Integer osi
exit(EXIT_FAILURE);
}
accelerator_barrier();
#ifdef GRID_REDUCTION_TIMING
t_cub_large += usecond();
#endif
R4 group_result;
acceleratorCopyFromDevice(d_out, &group_result, sizeof(R4));
ret_p[base ] = TensorRemove(group_result._internal[0]);
@@ -177,12 +209,20 @@ inline typename vobj::scalar_objectD sumD_gpu_large(const vobj *lat, Integer osi
// Partial last group: zero-pad unused slots so they contribute nothing to the sum.
if (rem > 0) {
int base = 4 * nfull;
#ifdef GRID_REDUCTION_TIMING
t_for_large -= usecond();
#endif
accelerator_for(ss, osites, 1, {
R4 r4; zeroit(r4);
for (int k = 0; k < rem; k++)
r4._internal[k] = TensorRemove(Reduce(idat[ss * words + base + k]));
buf_p[ss] = r4;
});
#ifdef GRID_REDUCTION_TIMING
accelerator_barrier();
t_for_large += usecond();
t_cub_large -= usecond();
#endif
gpuErr = gpucub::DeviceReduce::Reduce(d_temp, temp_bytes, buf_p, d_out,
(int)osites, gpucub::Sum(), zero4, computeStream);
if (gpuErr != gpuSuccess) {
@@ -191,12 +231,23 @@ inline typename vobj::scalar_objectD sumD_gpu_large(const vobj *lat, Integer osi
exit(EXIT_FAILURE);
}
accelerator_barrier();
#ifdef GRID_REDUCTION_TIMING
t_cub_large += usecond();
#endif
R4 partial_result;
acceleratorCopyFromDevice(d_out, &partial_result, sizeof(R4));
for (int k = 0; k < rem; k++)
ret_p[4 * nfull + k] = TensorRemove(partial_result._internal[k]);
}
#ifdef GRID_REDUCTION_TIMING
std::cout << GridLogMessage << "sumD_gpu_large"
<< " sizeof(sobjD)=" << sizeof(sobjD)
<< " words=" << words << " nfull=" << nfull << " rem=" << rem
<< " accelerator_for=" << t_for_large << " us"
<< " CUB_reduce=" << t_cub_large << " us" << std::endl;
#endif
acceleratorFreeDevice(d_temp);
acceleratorFreeDevice(d_out);
return ret;