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Refinement: the weight trials' own slots made while the placement runs

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Bitwise. MakeOwnSlot copies the model as it was before the topology and reads only what the placement does not
change (cell, reflections, the engine's kind, the B ceiling), so the slots are now built on their threads right
after the start score, beside the rigid-body and group-B placement, and joined where they were built before
(also where the placement throws). The "slots" stage goes from 0.23 s to 0 on 9yl4; the placement is not
slowed (0.59 -> 0.60 s). Refined CIF md5 unchanged on 5reo, 5f6m, 9yl4, 7d98, 5f6m MD start (GPU) and 6o2h
(CPU); side by side = one at a time. Wall: 5reo 1.46-1.53 -> 1.54, 5f6m 2.26 -> 2.21, 9yl4 7.03 -> 6.83, 7d98
3.65 -> 3.56, 5f6m MD start 4.20 -> 4.15 s.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu
(cherry picked from commit 0752a921a4293d4213894e3242c4ef36d8ce2a05)
This commit is contained in:
leonarski_f committed 2026-10-26 09:16:34 +01:00
1 parent 1f8b5b1986
commit f34d2f4cca
1 file changed
+31 -21
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image_analysis/structure_refinement/Refinement.cpp
+31 -21
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@@ -1272,6 +1272,35 @@ RefinementResult RefineModel(const gemmi::Structure &placed, const std::vector<M
return result;
}
// The trials run side by side, as many at a time as the longest set of them has and the cards take engines:
// on the main model and engine, and on copies with engines of their own; each with a share of the threads. The
// copies are made while the placement runs: they start from the model as it was before the topology was made
// and take nothing from the main context that the placement changes.
int wanted = static_cast<int>(std::max({settings.weight_ladder.size() * settings.adp_ladder.size(),
settings.final_ladder.size(), size_t{3}}));
if (settings.max_trials_at_once > 0)
wanted = std::min(wanted, static_cast<int>(settings.max_trials_at_once));
const std::vector<int> devices = settings.restrained ? OwnSlotDevices(ctx, wanted - 1, settings) : std::vector<int>();
const size_t slot_threads = std::max<size_t>(1, settings.nthreads / (devices.size() + 1));
std::vector<std::unique_ptr<OwnSlot>> own(devices.size());
std::vector<std::thread> slot_builders;
// joined before the slots are taken, or here where the placement throws
struct JoinAll {
std::vector<std::thread> &threads;
~JoinAll() {
for (std::thread &t : threads)
if (t.joinable())
t.join();
}
} join_slot_builders{slot_builders};
for (size_t k = 0; k < devices.size(); k++)
slot_builders.emplace_back([&, k]() {
#ifdef JFJOCH_USE_CUDA
const ScopedGpuPin pin(devices[k] >= 0 ? devices[k] : get_gpu());
#endif
own[k] = MakeOwnSlot(before_topology, ctx, devices[k], slot_threads, settings);
});
RefinePlacement(ctx, settings.group_b, result);
if (restrained)
PlaceRiders(ctx, topo);
@@ -1317,28 +1346,9 @@ RefinementResult RefineModel(const gemmi::Structure &placed, const std::vector<M
const std::vector<gemmi::Position> pos0 = ctx.Positions();
const std::vector<double> b0 = ctx.B();
// The trials run side by side, as many at a time as the longest set of them has and the cards take engines:
// on the main model and engine, and on copies with engines of their own; each with a share of the threads.
std::optional<RefinementStage> slot_stage("slots");
int wanted = static_cast<int>(std::max({settings.weight_ladder.size() * settings.adp_ladder.size(),
settings.final_ladder.size(), size_t{3}}));
if (settings.max_trials_at_once > 0)
wanted = std::min(wanted, static_cast<int>(settings.max_trials_at_once));
const std::vector<int> devices = OwnSlotDevices(ctx, wanted - 1, settings);
const size_t slot_threads = std::max<size_t>(1, settings.nthreads / (devices.size() + 1));
std::vector<std::unique_ptr<OwnSlot>> own(devices.size());
{
std::vector<std::thread> threads;
for (size_t k = 0; k < devices.size(); k++)
threads.emplace_back([&, k]() {
#ifdef JFJOCH_USE_CUDA
const ScopedGpuPin pin(devices[k] >= 0 ? devices[k] : get_gpu());
#endif
own[k] = MakeOwnSlot(before_topology, ctx, devices[k], slot_threads, settings);
});
for (std::thread &t : threads)
t.join();
}
for (std::thread &t : slot_builders)
t.join();
const size_t main_threads = ctx.nthreads;
ctx.nthreads = slot_threads;
std::vector<TrialSlot> trial_slots{{&ctx, &topo}};