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37 * \brief Implements LINCS using CUDA
39 * This file contains implementation of LINCS constraints algorithm
40 * using CUDA, including class initialization, data-structures management
43 * \author Artem Zhmurov <zhmurov@gmail.com>
44 * \author Alan Gray <alang@nvidia.com>
46 * \ingroup module_mdlib
50 #include "lincs_gpu.cuh"
59 #include "gromacs/gpu_utils/cuda_arch_utils.cuh"
60 #include "gromacs/gpu_utils/cudautils.cuh"
61 #include "gromacs/gpu_utils/devicebuffer.cuh"
62 #include "gromacs/gpu_utils/gputraits.h"
63 #include "gromacs/gpu_utils/typecasts.cuh"
64 #include "gromacs/gpu_utils/vectype_ops.cuh"
65 #include "gromacs/math/functions.h"
66 #include "gromacs/math/vec.h"
67 #include "gromacs/mdlib/constr.h"
68 #include "gromacs/pbcutil/pbc.h"
69 #include "gromacs/pbcutil/pbc_aiuc_cuda.cuh"
70 #include "gromacs/topology/forcefieldparameters.h"
71 #include "gromacs/topology/ifunc.h"
72 #include "gromacs/topology/topology.h"
77 //! Number of CUDA threads in a block
78 constexpr static int c_threadsPerBlock = 256;
79 //! Maximum number of threads in a block (for __launch_bounds__)
80 constexpr static int c_maxThreadsPerBlock = c_threadsPerBlock;
82 /*! \brief Main kernel for LINCS constraints.
84 * See Hess et al., J. Comput. Chem. 18: 1463-1472 (1997) for the description of the algorithm.
86 * In CUDA version, one thread is responsible for all computations for one constraint. The blocks are
87 * filled in a way that no constraint is coupled to the constraint from the next block. This is achieved
88 * by moving active threads to the next block, if the correspondent group of coupled constraints is to big
89 * to fit the current thread block. This may leave some 'dummy' threads in the end of the thread block, i.e.
90 * threads that are not required to do actual work. Since constraints from different blocks are not coupled,
91 * there is no need to synchronize across the device. However, extensive communication in a thread block
94 * \todo Reduce synchronization overhead. Some ideas are:
95 * 1. Consider going to warp-level synchronization for the coupled constraints.
96 * 2. Move more data to local/shared memory and try to get rid of atomic operations (at least on
98 * 3. Use analytical solution for matrix A inversion.
99 * 4. Introduce mapping of thread id to both single constraint and single atom, thus designating
100 * Nth threads to deal with Nat <= Nth coupled atoms and Nc <= Nth coupled constraints.
101 * See Issue #2885 for details (https://gitlab.com/gromacs/gromacs/-/issues/2885)
102 * \todo The use of __restrict__ for gm_xp and gm_v causes failure, probably because of the atomic
103 operations. Investigate this issue further.
105 * \param[in,out] kernelParams All parameters and pointers for the kernel condensed in single struct.
106 * \param[in] invdt Inverse timestep (needed to update velocities).
108 template<bool updateVelocities, bool computeVirial>
109 __launch_bounds__(c_maxThreadsPerBlock) __global__
110 void lincs_kernel(LincsGpuKernelParameters kernelParams,
111 const float3* __restrict__ gm_x,
116 const PbcAiuc pbcAiuc = kernelParams.pbcAiuc;
117 const int numConstraintsThreads = kernelParams.numConstraintsThreads;
118 const int numIterations = kernelParams.numIterations;
119 const int expansionOrder = kernelParams.expansionOrder;
120 const int2* __restrict__ gm_constraints = kernelParams.d_constraints;
121 const float* __restrict__ gm_constraintsTargetLengths = kernelParams.d_constraintsTargetLengths;
122 const int* __restrict__ gm_coupledConstraintsCounts = kernelParams.d_coupledConstraintsCounts;
123 const int* __restrict__ gm_coupledConstraintsIdxes = kernelParams.d_coupledConstraintsIndices;
124 const float* __restrict__ gm_massFactors = kernelParams.d_massFactors;
125 float* __restrict__ gm_matrixA = kernelParams.d_matrixA;
126 const float* __restrict__ gm_inverseMasses = kernelParams.d_inverseMasses;
127 float* __restrict__ gm_virialScaled = kernelParams.d_virialScaled;
129 int threadIndex = blockIdx.x * blockDim.x + threadIdx.x;
131 // numConstraintsThreads should be a integer multiple of blockSize (numConstraintsThreads = numBlocks*blockSize).
132 // This is to ensure proper synchronizations and reduction. All array are padded to the required size.
133 assert(threadIndex < numConstraintsThreads);
135 // Vectors connecting constrained atoms before algorithm was applied.
136 // Needed to construct constrain matrix A
137 extern __shared__ float3 sm_r[];
139 int2 pair = gm_constraints[threadIndex];
143 // Mass-scaled Lagrange multiplier
144 float lagrangeScaled = 0.0f;
149 float sqrtReducedMass;
155 // i == -1 indicates dummy constraint at the end of the thread block.
156 bool isDummyThread = (i == -1);
158 // Everything computed for these dummies will be equal to zero
164 sqrtReducedMass = 0.0f;
166 xi = make_float3(0.0f, 0.0f, 0.0f);
167 xj = make_float3(0.0f, 0.0f, 0.0f);
168 rc = make_float3(0.0f, 0.0f, 0.0f);
173 targetLength = gm_constraintsTargetLengths[threadIndex];
174 inverseMassi = gm_inverseMasses[i];
175 inverseMassj = gm_inverseMasses[j];
176 sqrtReducedMass = rsqrt(inverseMassi + inverseMassj);
181 float3 dx = pbcDxAiuc(pbcAiuc, xi, xj);
183 float rlen = rsqrtf(dx.x * dx.x + dx.y * dx.y + dx.z * dx.z);
187 sm_r[threadIdx.x] = rc;
188 // Make sure that all r's are saved into shared memory
189 // before they are accessed in the loop below
193 * Constructing LINCS matrix (A)
196 // Only non-zero values are saved (for coupled constraints)
197 int coupledConstraintsCount = gm_coupledConstraintsCounts[threadIndex];
198 for (int n = 0; n < coupledConstraintsCount; n++)
200 int index = n * numConstraintsThreads + threadIndex;
201 int c1 = gm_coupledConstraintsIdxes[index];
203 float3 rc1 = sm_r[c1 - blockIdx.x * blockDim.x];
204 gm_matrixA[index] = gm_massFactors[index] * (rc.x * rc1.x + rc.y * rc1.y + rc.z * rc1.z);
207 // Skipping in dummy threads
214 float3 dx = pbcDxAiuc(pbcAiuc, xi, xj);
216 float sol = sqrtReducedMass * ((rc.x * dx.x + rc.y * dx.y + rc.z * dx.z) - targetLength);
219 * Inverse matrix using a set of expansionOrder matrix multiplications
222 // This will use the same memory space as sm_r, which is no longer needed.
223 extern __shared__ float sm_rhs[];
224 // Save current right-hand-side vector in the shared memory
225 sm_rhs[threadIdx.x] = sol;
227 for (int rec = 0; rec < expansionOrder; rec++)
229 // Making sure that all sm_rhs are saved before they are accessed in a loop below
233 for (int n = 0; n < coupledConstraintsCount; n++)
235 int index = n * numConstraintsThreads + threadIndex;
236 int c1 = gm_coupledConstraintsIdxes[index];
237 // Convolute current right-hand-side with A
238 // Different, non overlapping parts of sm_rhs[..] are read during odd and even iterations
239 mvb = mvb + gm_matrixA[index] * sm_rhs[c1 - blockIdx.x * blockDim.x + blockDim.x * (rec % 2)];
241 // 'Switch' rhs vectors, save current result
242 // These values will be accessed in the loop above during the next iteration.
243 sm_rhs[threadIdx.x + blockDim.x * ((rec + 1) % 2)] = mvb;
247 // Current mass-scaled Lagrange multipliers
248 lagrangeScaled = sqrtReducedMass * sol;
250 // Save updated coordinates before correction for the rotational lengthening
251 float3 tmp = rc * lagrangeScaled;
253 // Writing for all but dummy constraints
256 atomicAdd(&gm_xp[i], -tmp * inverseMassi);
257 atomicAdd(&gm_xp[j], tmp * inverseMassj);
261 * Correction for centripetal effects
263 for (int iter = 0; iter < numIterations; iter++)
265 // Make sure that all xp's are saved: atomic operation calls before are
266 // communicating current xp[..] values across thread block.
275 float3 dx = pbcDxAiuc(pbcAiuc, xi, xj);
277 float len2 = targetLength * targetLength;
278 float dlen2 = 2.0f * len2 - norm2(dx);
280 // TODO A little bit more effective but slightly less readable version of the below would be:
281 // float proj = sqrtReducedMass*(targetLength - (dlen2 > 0.0f ? 1.0f : 0.0f)*dlen2*rsqrt(dlen2));
285 proj = sqrtReducedMass * (targetLength - dlen2 * rsqrt(dlen2));
289 proj = sqrtReducedMass * targetLength;
292 sm_rhs[threadIdx.x] = proj;
296 * Same matrix inversion as above is used for updated data
298 for (int rec = 0; rec < expansionOrder; rec++)
300 // Make sure that all elements of rhs are saved into shared memory
304 for (int n = 0; n < coupledConstraintsCount; n++)
306 int index = n * numConstraintsThreads + threadIndex;
307 int c1 = gm_coupledConstraintsIdxes[index];
309 mvb = mvb + gm_matrixA[index] * sm_rhs[c1 - blockIdx.x * blockDim.x + blockDim.x * (rec % 2)];
311 sm_rhs[threadIdx.x + blockDim.x * ((rec + 1) % 2)] = mvb;
315 // Add corrections to Lagrange multipliers
316 float sqrtmu_sol = sqrtReducedMass * sol;
317 lagrangeScaled += sqrtmu_sol;
319 // Save updated coordinates for the next iteration
320 // Dummy constraints are skipped
323 float3 tmp = rc * sqrtmu_sol;
324 atomicAdd(&gm_xp[i], -tmp * inverseMassi);
325 atomicAdd(&gm_xp[j], tmp * inverseMassj);
329 // Updating particle velocities for all but dummy threads
330 if (updateVelocities && !isDummyThread)
332 float3 tmp = rc * invdt * lagrangeScaled;
333 atomicAdd(&gm_v[i], -tmp * inverseMassi);
334 atomicAdd(&gm_v[j], tmp * inverseMassj);
340 // Virial is computed from Lagrange multiplier (lagrangeScaled), target constrain length
341 // (targetLength) and the normalized vector connecting constrained atoms before
342 // the algorithm was applied (rc). The evaluation of virial in each thread is
343 // followed by basic reduction for the values inside single thread block.
344 // Then, the values are reduced across grid by atomicAdd(...).
346 // TODO Shuffle reduction.
347 // TODO Should be unified and/or done once when virial is actually needed.
348 // TODO Recursive version that removes atomicAdd(...)'s entirely is needed. Ideally,
349 // one that works for any datatype.
351 // Save virial for each thread into the shared memory. Tensor is symmetrical, hence only
352 // 6 values are saved. Dummy threads will have zeroes in their virial: targetLength,
353 // lagrangeScaled and rc are all set to zero for them in the beginning of the kernel.
354 // The sm_threadVirial[..] will overlap with the sm_r[..] and sm_rhs[..], but the latter
355 // two are no longer in use.
356 extern __shared__ float sm_threadVirial[];
357 float mult = targetLength * lagrangeScaled;
358 sm_threadVirial[0 * blockDim.x + threadIdx.x] = mult * rc.x * rc.x;
359 sm_threadVirial[1 * blockDim.x + threadIdx.x] = mult * rc.x * rc.y;
360 sm_threadVirial[2 * blockDim.x + threadIdx.x] = mult * rc.x * rc.z;
361 sm_threadVirial[3 * blockDim.x + threadIdx.x] = mult * rc.y * rc.y;
362 sm_threadVirial[4 * blockDim.x + threadIdx.x] = mult * rc.y * rc.z;
363 sm_threadVirial[5 * blockDim.x + threadIdx.x] = mult * rc.z * rc.z;
367 // Reduce up to one virial per thread block. All blocks are divided by half, the first
368 // half of threads sums two virials. Then the first half is divided by two and the first
369 // half of it sums two values. This procedure is repeated until only one thread is left.
370 // Only works if the threads per blocks is a power of two (hence static_assert
371 // in the beginning of the kernel).
372 for (int divideBy = 2; divideBy <= static_cast<int>(blockDim.x); divideBy *= 2)
374 int dividedAt = blockDim.x / divideBy;
375 if (static_cast<int>(threadIdx.x) < dividedAt)
377 for (int d = 0; d < 6; d++)
379 sm_threadVirial[d * blockDim.x + threadIdx.x] +=
380 sm_threadVirial[d * blockDim.x + (threadIdx.x + dividedAt)];
383 // Syncronize if not within one warp
384 if (dividedAt > warpSize / 2)
389 // First 6 threads in the block add the results of 6 tensor components to the global memory address.
392 atomicAdd(&(gm_virialScaled[threadIdx.x]), sm_threadVirial[threadIdx.x * blockDim.x]);
399 /*! \brief Select templated kernel.
401 * Returns pointer to a CUDA kernel based on provided booleans.
403 * \param[in] updateVelocities If the velocities should be constrained.
404 * \param[in] computeVirial If virial should be updated.
406 * \return Pointer to CUDA kernel
408 inline auto getLincsKernelPtr(const bool updateVelocities, const bool computeVirial)
411 auto kernelPtr = lincs_kernel<true, true>;
412 if (updateVelocities && computeVirial)
414 kernelPtr = lincs_kernel<true, true>;
416 else if (updateVelocities && !computeVirial)
418 kernelPtr = lincs_kernel<true, false>;
420 else if (!updateVelocities && computeVirial)
422 kernelPtr = lincs_kernel<false, true>;
424 else if (!updateVelocities && !computeVirial)
426 kernelPtr = lincs_kernel<false, false>;
431 void LincsGpu::apply(const DeviceBuffer<Float3> d_x,
432 DeviceBuffer<Float3> d_xp,
433 const bool updateVelocities,
434 DeviceBuffer<Float3> d_v,
436 const bool computeVirial,
438 const PbcAiuc pbcAiuc)
440 ensureNoPendingDeviceError("In CUDA version of LINCS");
442 // Early exit if no constraints
443 if (kernelParams_.numConstraintsThreads == 0)
450 // Fill with zeros so the values can be reduced to it
451 // Only 6 values are needed because virial is symmetrical
452 clearDeviceBufferAsync(&kernelParams_.d_virialScaled, 0, 6, deviceStream_);
455 auto kernelPtr = getLincsKernelPtr(updateVelocities, computeVirial);
457 KernelLaunchConfig config;
458 config.blockSize[0] = c_threadsPerBlock;
459 config.blockSize[1] = 1;
460 config.blockSize[2] = 1;
461 config.gridSize[0] = (kernelParams_.numConstraintsThreads + c_threadsPerBlock - 1) / c_threadsPerBlock;
462 config.gridSize[1] = 1;
463 config.gridSize[2] = 1;
465 // Shared memory is used to store:
466 // -- Current coordinates (3 floats per thread)
467 // -- Right-hand-sides for matrix inversion (2 floats per thread)
468 // -- Virial tensor components (6 floats per thread)
469 // Since none of these three are needed simultaneously, they can be saved at the same shared memory address
470 // (i.e. correspondent arrays are intentionally overlapped in address space). Consequently, only
471 // max{3, 2, 6} = 6 floats per thread are needed in case virial is computed, or max{3, 2} = 3 if not.
474 config.sharedMemorySize = c_threadsPerBlock * 6 * sizeof(float);
478 config.sharedMemorySize = c_threadsPerBlock * 3 * sizeof(float);
481 kernelParams_.pbcAiuc = pbcAiuc;
483 const auto kernelArgs = prepareGpuKernelArguments(kernelPtr,
486 asFloat3Pointer(&d_x),
487 asFloat3Pointer(&d_xp),
488 asFloat3Pointer(&d_v),
491 launchGpuKernel(kernelPtr,
495 "lincs_kernel<updateVelocities, computeVirial>",
500 // Copy LINCS virial data and add it to the common virial
501 copyFromDeviceBuffer(h_virialScaled_.data(),
502 &kernelParams_.d_virialScaled,
506 GpuApiCallBehavior::Sync,
509 // Mapping [XX, XY, XZ, YY, YZ, ZZ] internal format to a tensor object
510 virialScaled[XX][XX] += h_virialScaled_[0];
511 virialScaled[XX][YY] += h_virialScaled_[1];
512 virialScaled[XX][ZZ] += h_virialScaled_[2];
514 virialScaled[YY][XX] += h_virialScaled_[1];
515 virialScaled[YY][YY] += h_virialScaled_[3];
516 virialScaled[YY][ZZ] += h_virialScaled_[4];
518 virialScaled[ZZ][XX] += h_virialScaled_[2];
519 virialScaled[ZZ][YY] += h_virialScaled_[4];
520 virialScaled[ZZ][ZZ] += h_virialScaled_[5];
526 LincsGpu::LincsGpu(int numIterations,
528 const DeviceContext& deviceContext,
529 const DeviceStream& deviceStream) :
530 deviceContext_(deviceContext),
531 deviceStream_(deviceStream)
533 kernelParams_.numIterations = numIterations;
534 kernelParams_.expansionOrder = expansionOrder;
536 static_assert(sizeof(real) == sizeof(float),
537 "Real numbers should be in single precision in GPU code.");
539 gmx::isPowerOfTwo(c_threadsPerBlock),
540 "Number of threads per block should be a power of two in order for reduction to work.");
542 allocateDeviceBuffer(&kernelParams_.d_virialScaled, 6, deviceContext_);
543 h_virialScaled_.resize(6);
545 // The data arrays should be expanded/reallocated on first call of set() function.
546 numConstraintsThreadsAlloc_ = 0;
550 LincsGpu::~LincsGpu()
552 freeDeviceBuffer(&kernelParams_.d_virialScaled);
554 if (numConstraintsThreadsAlloc_ > 0)
556 freeDeviceBuffer(&kernelParams_.d_constraints);
557 freeDeviceBuffer(&kernelParams_.d_constraintsTargetLengths);
559 freeDeviceBuffer(&kernelParams_.d_coupledConstraintsCounts);
560 freeDeviceBuffer(&kernelParams_.d_coupledConstraintsIndices);
561 freeDeviceBuffer(&kernelParams_.d_massFactors);
562 freeDeviceBuffer(&kernelParams_.d_matrixA);
564 if (numAtomsAlloc_ > 0)
566 freeDeviceBuffer(&kernelParams_.d_inverseMasses);
570 //! Helper type for discovering coupled constraints
571 struct AtomsAdjacencyListElement
573 AtomsAdjacencyListElement(const int indexOfSecondConstrainedAtom,
574 const int indexOfConstraint,
575 const int signFactor) :
576 indexOfSecondConstrainedAtom_(indexOfSecondConstrainedAtom),
577 indexOfConstraint_(indexOfConstraint),
578 signFactor_(signFactor)
581 //! The index of the other atom constrained to this atom.
582 int indexOfSecondConstrainedAtom_;
583 //! The index of this constraint in the container of constraints.
584 int indexOfConstraint_;
585 /*! \brief A multiplicative factor that indicates the relative
586 * order of the atoms in the atom list.
588 * Used for computing the mass factor of this constraint
589 * relative to any coupled constraints. */
592 //! Constructs and returns an atom constraint adjacency list
593 static std::vector<std::vector<AtomsAdjacencyListElement>>
594 constructAtomsAdjacencyList(const int numAtoms, ArrayRef<const int> iatoms)
596 const int stride = 1 + NRAL(F_CONSTR);
597 const int numConstraints = iatoms.ssize() / stride;
598 std::vector<std::vector<AtomsAdjacencyListElement>> atomsAdjacencyList(numAtoms);
599 for (int c = 0; c < numConstraints; c++)
601 int a1 = iatoms[stride * c + 1];
602 int a2 = iatoms[stride * c + 2];
604 // Each constraint will be represented as a tuple, containing index of the second
605 // constrained atom, index of the constraint and a sign that indicates the order of atoms in
606 // which they are listed. Sign is needed to compute the mass factors.
607 atomsAdjacencyList[a1].emplace_back(a2, c, +1);
608 atomsAdjacencyList[a2].emplace_back(a1, c, -1);
611 return atomsAdjacencyList;
614 /*! \brief Helper function to go through constraints recursively.
616 * For each constraint, counts the number of coupled constraints and stores the value in \p numCoupledConstraints array.
617 * This information is used to split the array of constraints between thread blocks on a GPU so there is no
618 * coupling between constraints from different thread blocks. After the \p numCoupledConstraints array is filled, the
619 * value \p numCoupledConstraints[c] should be equal to the number of constraints that are coupled to \p c and located
620 * after it in the constraints array.
622 * \param[in] a Atom index.
623 * \param[in,out] numCoupledConstraints Indicates if the constraint was already counted and stores
624 * the number of constraints (i) connected to it and (ii) located
625 * after it in memory. This array is filled by this recursive function.
626 * For a set of coupled constraints, only for the first one in this list
627 * the number of consecutive coupled constraints is needed: if there is
628 * not enough space for this set of constraints in the thread block,
629 * the group has to be moved to the next one.
630 * \param[in] atomsAdjacencyList Stores information about connections between atoms.
632 inline int countCoupled(int a,
633 ArrayRef<int> numCoupledConstraints,
634 ArrayRef<const std::vector<AtomsAdjacencyListElement>> atomsAdjacencyList)
638 for (const auto& adjacentAtom : atomsAdjacencyList[a])
640 const int c2 = adjacentAtom.indexOfConstraint_;
641 if (numCoupledConstraints[c2] == -1)
643 numCoupledConstraints[c2] = 0; // To indicate we've been here
645 + countCoupled(adjacentAtom.indexOfSecondConstrainedAtom_,
646 numCoupledConstraints,
653 /*! \brief Add constraint to \p splitMap with all constraints coupled to it.
655 * Adds the constraint \p c from the constrain list \p iatoms to the map \p splitMap
656 * if it was not yet added. Then goes through all the constraints coupled to \p c
657 * and calls itself recursively. This ensures that all the coupled constraints will
658 * be added to neighboring locations in the final data structures on the device,
659 * hence mapping all coupled constraints to the same thread block. A value of -1 in
660 * the \p splitMap is used to flag that constraint was not yet added to the \p splitMap.
662 * \param[in] iatoms The list of constraints.
663 * \param[in] stride Number of elements per constraint in \p iatoms.
664 * \param[in] atomsAdjacencyList Information about connections between atoms.
665 * \param[our] splitMap Map of sequential constraint indexes to indexes to be on the device
666 * \param[in] c Sequential index for constraint to consider adding.
667 * \param[in,out] currentMapIndex The rolling index for the constraints mapping.
669 inline void addWithCoupled(ArrayRef<const int> iatoms,
671 ArrayRef<const std::vector<AtomsAdjacencyListElement>> atomsAdjacencyList,
672 ArrayRef<int> splitMap,
674 int* currentMapIndex)
676 if (splitMap[c] == -1)
678 splitMap[c] = *currentMapIndex;
679 (*currentMapIndex)++;
681 // Constraints, coupled through both atoms.
682 for (int atomIndexInConstraint = 0; atomIndexInConstraint < 2; atomIndexInConstraint++)
684 const int a1 = iatoms[stride * c + 1 + atomIndexInConstraint];
685 for (const auto& adjacentAtom : atomsAdjacencyList[a1])
687 const int c2 = adjacentAtom.indexOfConstraint_;
690 addWithCoupled(iatoms, stride, atomsAdjacencyList, splitMap, c2, currentMapIndex);
697 /*! \brief Computes and returns how many constraints are coupled to each constraint
699 * Needed to introduce splits in data so that all coupled constraints will be computed in a
700 * single GPU block. The position \p c of the vector \p numCoupledConstraints should have the number
701 * of constraints that are coupled to a constraint \p c and are after \p c in the vector. Only
702 * first index of the connected group of the constraints is needed later in the code, hence the
703 * numCoupledConstraints vector is also used to keep track if the constrain was already counted.
705 static std::vector<int> countNumCoupledConstraints(ArrayRef<const int> iatoms,
706 ArrayRef<const std::vector<AtomsAdjacencyListElement>> atomsAdjacencyList)
708 const int stride = 1 + NRAL(F_CONSTR);
709 const int numConstraints = iatoms.ssize() / stride;
710 std::vector<int> numCoupledConstraints(numConstraints, -1);
711 for (int c = 0; c < numConstraints; c++)
713 const int a1 = iatoms[stride * c + 1];
714 const int a2 = iatoms[stride * c + 2];
715 if (numCoupledConstraints[c] == -1)
717 numCoupledConstraints[c] = countCoupled(a1, numCoupledConstraints, atomsAdjacencyList)
718 + countCoupled(a2, numCoupledConstraints, atomsAdjacencyList);
722 return numCoupledConstraints;
725 bool LincsGpu::isNumCoupledConstraintsSupported(const gmx_mtop_t& mtop)
727 for (const gmx_moltype_t& molType : mtop.moltype)
729 ArrayRef<const int> iatoms = molType.ilist[F_CONSTR].iatoms;
730 const auto atomsAdjacencyList = constructAtomsAdjacencyList(molType.atoms.nr, iatoms);
731 // Compute, how many constraints are coupled to each constraint
732 const auto numCoupledConstraints = countNumCoupledConstraints(iatoms, atomsAdjacencyList);
733 for (const int numCoupled : numCoupledConstraints)
735 if (numCoupled > c_threadsPerBlock)
745 void LincsGpu::set(const InteractionDefinitions& idef, const int numAtoms, const real* invmass)
747 // List of constrained atoms (CPU memory)
748 std::vector<int2> constraintsHost;
749 // Equilibrium distances for the constraints (CPU)
750 std::vector<float> constraintsTargetLengthsHost;
751 // Number of constraints, coupled with the current one (CPU)
752 std::vector<int> coupledConstraintsCountsHost;
753 // List of coupled with the current one (CPU)
754 std::vector<int> coupledConstraintsIndicesHost;
755 // Mass factors (CPU)
756 std::vector<float> massFactorsHost;
758 // List of constrained atoms in local topology
759 ArrayRef<const int> iatoms = idef.il[F_CONSTR].iatoms;
760 const int stride = NRAL(F_CONSTR) + 1;
761 const int numConstraints = idef.il[F_CONSTR].size() / stride;
763 // Early exit if no constraints
764 if (numConstraints == 0)
766 kernelParams_.numConstraintsThreads = 0;
770 // Construct the adjacency list, a useful intermediate structure
771 const auto atomsAdjacencyList = constructAtomsAdjacencyList(numAtoms, iatoms);
773 // Compute, how many constraints are coupled to each constraint
774 const auto numCoupledConstraints = countNumCoupledConstraints(iatoms, atomsAdjacencyList);
776 // Map of splits in the constraints data. For each 'old' constraint index gives 'new' which
777 // takes into account the empty spaces which might be needed in the end of each thread block.
778 std::vector<int> splitMap(numConstraints, -1);
779 int currentMapIndex = 0;
780 for (int c = 0; c < numConstraints; c++)
782 // Check if coupled constraints all fit in one block
783 if (numCoupledConstraints.at(c) > c_threadsPerBlock)
786 "Maximum number of coupled constraints (%d) exceeds the size of the CUDA "
787 "thread block (%d). Most likely, you are trying to use the GPU version of "
788 "LINCS with constraints on all-bonds, which is not supported for large "
789 "molecules. When compatible with the force field and integration settings, "
790 "using constraints on H-bonds only.",
791 numCoupledConstraints.at(c),
794 if (currentMapIndex / c_threadsPerBlock
795 != (currentMapIndex + numCoupledConstraints.at(c)) / c_threadsPerBlock)
797 currentMapIndex = ((currentMapIndex / c_threadsPerBlock) + 1) * c_threadsPerBlock;
799 addWithCoupled(iatoms, stride, atomsAdjacencyList, splitMap, c, ¤tMapIndex);
802 kernelParams_.numConstraintsThreads =
803 currentMapIndex + c_threadsPerBlock - currentMapIndex % c_threadsPerBlock;
804 GMX_RELEASE_ASSERT(kernelParams_.numConstraintsThreads % c_threadsPerBlock == 0,
805 "Number of threads should be a multiple of the block size");
807 // Initialize constraints and their target indexes taking into account the splits in the data arrays.
811 constraintsHost.resize(kernelParams_.numConstraintsThreads, pair);
812 std::fill(constraintsHost.begin(), constraintsHost.end(), pair);
813 constraintsTargetLengthsHost.resize(kernelParams_.numConstraintsThreads, 0.0);
814 std::fill(constraintsTargetLengthsHost.begin(), constraintsTargetLengthsHost.end(), 0.0);
815 for (int c = 0; c < numConstraints; c++)
817 int a1 = iatoms[stride * c + 1];
818 int a2 = iatoms[stride * c + 2];
819 int type = iatoms[stride * c];
824 constraintsHost.at(splitMap.at(c)) = pair;
825 constraintsTargetLengthsHost.at(splitMap.at(c)) = idef.iparams[type].constr.dA;
828 // The adjacency list of constraints (i.e. the list of coupled constraints for each constraint).
829 // We map a single thread to a single constraint, hence each thread 'c' will be using one
830 // element from coupledConstraintsCountsHost array, which is the number of constraints coupled
831 // to the constraint 'c'. The coupled constraints indexes are placed into the
832 // coupledConstraintsIndicesHost array. Latter is organized as a one-dimensional array to ensure
833 // good memory alignment. It is addressed as [c + i*numConstraintsThreads], where 'i' goes from
834 // zero to the number of constraints coupled to 'c'. 'numConstraintsThreads' is the width of the
835 // array --- a number, greater then total number of constraints, taking into account the splits
836 // in the constraints array due to the GPU block borders. This number can be adjusted to improve
837 // memory access pattern. Mass factors are saved in a similar data structure.
838 int maxCoupledConstraints = 0;
839 bool maxCoupledConstraintsHasIncreased = false;
840 for (int c = 0; c < numConstraints; c++)
842 int a1 = iatoms[stride * c + 1];
843 int a2 = iatoms[stride * c + 2];
845 // Constraint 'c' is counted twice, but it should be excluded altogether. Hence '-2'.
846 int nCoupledConstraints = atomsAdjacencyList.at(a1).size() + atomsAdjacencyList.at(a2).size() - 2;
848 if (nCoupledConstraints > maxCoupledConstraints)
850 maxCoupledConstraints = nCoupledConstraints;
851 maxCoupledConstraintsHasIncreased = true;
855 coupledConstraintsCountsHost.resize(kernelParams_.numConstraintsThreads, 0);
856 coupledConstraintsIndicesHost.resize(maxCoupledConstraints * kernelParams_.numConstraintsThreads, -1);
857 massFactorsHost.resize(maxCoupledConstraints * kernelParams_.numConstraintsThreads, -1);
859 for (int c1 = 0; c1 < numConstraints; c1++)
861 coupledConstraintsCountsHost.at(splitMap.at(c1)) = 0;
862 int c1a1 = iatoms[stride * c1 + 1];
863 int c1a2 = iatoms[stride * c1 + 2];
865 // Constraints, coupled through the first atom.
867 for (const auto& atomAdjacencyList : atomsAdjacencyList[c1a1])
869 int c2 = atomAdjacencyList.indexOfConstraint_;
873 int c2a2 = atomAdjacencyList.indexOfSecondConstrainedAtom_;
874 int sign = atomAdjacencyList.signFactor_;
875 int index = kernelParams_.numConstraintsThreads
876 * coupledConstraintsCountsHost.at(splitMap.at(c1))
879 coupledConstraintsIndicesHost.at(index) = splitMap.at(c2);
883 float sqrtmu1 = 1.0 / sqrt(invmass[c1a1] + invmass[c1a2]);
884 float sqrtmu2 = 1.0 / sqrt(invmass[c2a1] + invmass[c2a2]);
886 massFactorsHost.at(index) = -sign * invmass[center] * sqrtmu1 * sqrtmu2;
888 coupledConstraintsCountsHost.at(splitMap.at(c1))++;
892 // Constraints, coupled through the second atom.
894 for (const auto& atomAdjacencyList : atomsAdjacencyList[c1a2])
896 int c2 = atomAdjacencyList.indexOfConstraint_;
900 int c2a2 = atomAdjacencyList.indexOfSecondConstrainedAtom_;
901 int sign = atomAdjacencyList.signFactor_;
902 int index = kernelParams_.numConstraintsThreads
903 * coupledConstraintsCountsHost.at(splitMap.at(c1))
906 coupledConstraintsIndicesHost.at(index) = splitMap.at(c2);
910 float sqrtmu1 = 1.0 / sqrt(invmass[c1a1] + invmass[c1a2]);
911 float sqrtmu2 = 1.0 / sqrt(invmass[c2a1] + invmass[c2a2]);
913 massFactorsHost.at(index) = sign * invmass[center] * sqrtmu1 * sqrtmu2;
915 coupledConstraintsCountsHost.at(splitMap.at(c1))++;
920 // (Re)allocate the memory, if the number of constraints has increased.
921 if ((kernelParams_.numConstraintsThreads > numConstraintsThreadsAlloc_) || maxCoupledConstraintsHasIncreased)
923 // Free memory if it was allocated before (i.e. if not the first time here).
924 if (numConstraintsThreadsAlloc_ > 0)
926 freeDeviceBuffer(&kernelParams_.d_constraints);
927 freeDeviceBuffer(&kernelParams_.d_constraintsTargetLengths);
929 freeDeviceBuffer(&kernelParams_.d_coupledConstraintsCounts);
930 freeDeviceBuffer(&kernelParams_.d_coupledConstraintsIndices);
931 freeDeviceBuffer(&kernelParams_.d_massFactors);
932 freeDeviceBuffer(&kernelParams_.d_matrixA);
935 numConstraintsThreadsAlloc_ = kernelParams_.numConstraintsThreads;
937 allocateDeviceBuffer(
938 &kernelParams_.d_constraints, kernelParams_.numConstraintsThreads, deviceContext_);
939 allocateDeviceBuffer(&kernelParams_.d_constraintsTargetLengths,
940 kernelParams_.numConstraintsThreads,
943 allocateDeviceBuffer(&kernelParams_.d_coupledConstraintsCounts,
944 kernelParams_.numConstraintsThreads,
946 allocateDeviceBuffer(&kernelParams_.d_coupledConstraintsIndices,
947 maxCoupledConstraints * kernelParams_.numConstraintsThreads,
949 allocateDeviceBuffer(&kernelParams_.d_massFactors,
950 maxCoupledConstraints * kernelParams_.numConstraintsThreads,
952 allocateDeviceBuffer(&kernelParams_.d_matrixA,
953 maxCoupledConstraints * kernelParams_.numConstraintsThreads,
957 // (Re)allocate the memory, if the number of atoms has increased.
958 if (numAtoms > numAtomsAlloc_)
960 if (numAtomsAlloc_ > 0)
962 freeDeviceBuffer(&kernelParams_.d_inverseMasses);
964 numAtomsAlloc_ = numAtoms;
965 allocateDeviceBuffer(&kernelParams_.d_inverseMasses, numAtoms, deviceContext_);
969 copyToDeviceBuffer(&kernelParams_.d_constraints,
970 constraintsHost.data(),
972 kernelParams_.numConstraintsThreads,
974 GpuApiCallBehavior::Sync,
976 copyToDeviceBuffer(&kernelParams_.d_constraintsTargetLengths,
977 constraintsTargetLengthsHost.data(),
979 kernelParams_.numConstraintsThreads,
981 GpuApiCallBehavior::Sync,
983 copyToDeviceBuffer(&kernelParams_.d_coupledConstraintsCounts,
984 coupledConstraintsCountsHost.data(),
986 kernelParams_.numConstraintsThreads,
988 GpuApiCallBehavior::Sync,
990 copyToDeviceBuffer(&kernelParams_.d_coupledConstraintsIndices,
991 coupledConstraintsIndicesHost.data(),
993 maxCoupledConstraints * kernelParams_.numConstraintsThreads,
995 GpuApiCallBehavior::Sync,
997 copyToDeviceBuffer(&kernelParams_.d_massFactors,
998 massFactorsHost.data(),
1000 maxCoupledConstraints * kernelParams_.numConstraintsThreads,
1002 GpuApiCallBehavior::Sync,
1005 GMX_RELEASE_ASSERT(invmass != nullptr, "Masses of atoms should be specified.\n");
1007 &kernelParams_.d_inverseMasses, invmass, 0, numAtoms, deviceStream_, GpuApiCallBehavior::Sync, nullptr);