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lammps/src/KOKKOS/fix_rx_kokkos.cpp
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fix_rx_kokkos.cpp
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/* ----------------------------------------------------------------------
LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
http://lammps.sandia.gov, Sandia National Laboratories
Steve Plimpton, sjplimp@sandia.gov
Copyright (2003) Sandia Corporation. Under the terms of Contract
DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
certain rights in this software. This software is distributed under
the GNU General Public License.
See the README file in the top-level LAMMPS directory.
------------------------------------------------------------------------- */
#include <stdio.h>
#include <string.h>
#include "fix_rx_kokkos.h"
#include "atom_masks.h"
#include "atom_kokkos.h"
#include "force.h"
#include "memory.h"
#include "update.h"
#include "respa.h"
#include "modify.h"
#include "neighbor.h"
#include "neigh_list_kokkos.h"
#include "neigh_request.h"
#include "error.h"
#include "math_special_kokkos.h"
#include <float.h> // DBL_EPSILON
using namespace LAMMPS_NS;
using namespace FixConst;
using namespace MathSpecialKokkos;
#ifdef DBL_EPSILON
#define MY_EPSILON (10.0*DBL_EPSILON)
#else
#define MY_EPSILON (10.0*2.220446049250313e-16)
#endif
#define SparseKinetics_enableIntegralReactions (true)
#define SparseKinetics_invalidIndex (-1)
// From fix_rx.cpp ... this should be lifted into fix_rx.h or fix_rx_kokkos.h?
enum{NONE,HARMONIC};
enum{LUCY};
namespace /* anonymous */
{
typedef double TimerType;
TimerType getTimeStamp(void) { return MPI_Wtime(); }
double getElapsedTime( const TimerType &t0, const TimerType &t1) { return t1-t0; }
} // end namespace
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
FixRxKokkos<DeviceType>::FixRxKokkos(LAMMPS *lmp, int narg, char **arg) :
FixRX(lmp, narg, arg),
pairDPDEKK(NULL),
update_kinetics_data(true)
{
kokkosable = 1;
atomKK = (AtomKokkos *) atom;
execution_space = ExecutionSpaceFromDevice<DeviceType>::space;
datamask_read = EMPTY_MASK;
datamask_modify = EMPTY_MASK;
k_error_flag = DAT::tdual_int_scalar("FixRxKokkos::k_error_flag");
//printf("Inside FixRxKokkos::FixRxKokkos\n");
}
template <typename DeviceType>
FixRxKokkos<DeviceType>::~FixRxKokkos()
{
//printf("Inside FixRxKokkos::~FixRxKokkos copymode= %d\n", copymode);
if (copymode) return;
if (localTempFlag)
memory->destroy_kokkos(k_dpdThetaLocal, dpdThetaLocal);
memory->destroy_kokkos(k_sumWeights, sumWeights);
//memory->destroy_kokkos(k_sumWeights);
//delete [] scratchSpace;
memory->destroy_kokkos(d_scratchSpace);
memory->destroy_kokkos(k_cutsq);
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
void FixRxKokkos<DeviceType>::post_constructor()
{
// Run the parents and then reset one value.
FixRX::post_constructor();
// Need a copy of this
this->my_restartFlag = modify->fix[modify->nfix-1]->restart_reset;
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
void FixRxKokkos<DeviceType>::init()
{
//printf("Inside FixRxKokkos::init\n");
// Call the parent's version.
//FixRX::init();
pairDPDE = (PairDPDfdtEnergy *) force->pair_match("dpd/fdt/energy",1);
if (pairDPDE == NULL)
pairDPDE = (PairDPDfdtEnergy *) force->pair_match("dpd/fdt/energy/kk",1);
if (pairDPDE == NULL)
error->all(FLERR,"Must use pair_style dpd/fdt/energy with fix rx");
pairDPDEKK = dynamic_cast<decltype(pairDPDEKK)>(pairDPDE);
if (pairDPDEKK == NULL)
error->all(FLERR,"Must use pair_style dpd/fdt/energy/kk with fix rx/kk");
bool eos_flag = false;
for (int i = 0; i < modify->nfix; i++)
if (strncmp(modify->fix[i]->style,"eos/table/rx",3) == 0) eos_flag = true;
if(!eos_flag) error->all(FLERR,"fix rx requires fix eos/table/rx to be specified");
if (update_kinetics_data)
create_kinetics_data();
// From FixRX::init()
// need a half neighbor list
// built whenever re-neighboring occurs
int irequest = neighbor->request(this,instance_me);
neighbor->requests[irequest]->pair = 0;
neighbor->requests[irequest]->fix = 1;
// Update the neighbor data for Kokkos.
int neighflag = lmp->kokkos->neighflag;
neighbor->requests[irequest]->
kokkos_host = Kokkos::Impl::is_same<DeviceType,LMPHostType>::value &&
!Kokkos::Impl::is_same<DeviceType,LMPDeviceType>::value;
neighbor->requests[irequest]->
kokkos_device = Kokkos::Impl::is_same<DeviceType,LMPDeviceType>::value;
if (neighflag == FULL) {
neighbor->requests[irequest]->full = 1;
neighbor->requests[irequest]->half = 0;
} else { //if (neighflag == HALF || neighflag == HALFTHREAD)
neighbor->requests[irequest]->full = 0;
neighbor->requests[irequest]->half = 1;
}
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
void FixRxKokkos<DeviceType>::init_list(int, class NeighList* ptr)
{
//printf("Inside FixRxKokkos::init_list\n");
this->list = ptr;
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
void FixRxKokkos<DeviceType>::rk4(const double t_stop, double *y, double *rwork, void* v_params) const
{
double *k1 = rwork;
double *k2 = k1 + nspecies;
double *k3 = k2 + nspecies;
double *k4 = k3 + nspecies;
double *yp = k4 + nspecies;
const int numSteps = minSteps;
const double h = t_stop / double(numSteps);
// Run the requested steps with h.
for (int step = 0; step < numSteps; step++)
{
// k1
rhs(0.0,y,k1,v_params);
// k2
for (int ispecies = 0; ispecies < nspecies; ispecies++)
yp[ispecies] = y[ispecies] + 0.5*h*k1[ispecies];
rhs(0.0,yp,k2,v_params);
// k3
for (int ispecies = 0; ispecies < nspecies; ispecies++)
yp[ispecies] = y[ispecies] + 0.5*h*k2[ispecies];
rhs(0.0,yp,k3,v_params);
// k4
for (int ispecies = 0; ispecies < nspecies; ispecies++)
yp[ispecies] = y[ispecies] + h*k3[ispecies];
rhs(0.0,yp,k4,v_params);
for (int ispecies = 0; ispecies < nspecies; ispecies++)
y[ispecies] += h*(k1[ispecies]/6.0 + k2[ispecies]/3.0 + k3[ispecies]/3.0 + k4[ispecies]/6.0);
} // end for (int step...
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
template <typename VectorType, typename UserDataType>
void FixRxKokkos<DeviceType>::k_rk4(const double t_stop, VectorType& y, VectorType& rwork, UserDataType& userData) const
{
VectorType k1( rwork );
VectorType k2( &k1[nspecies] );
VectorType k3( &k2[nspecies] );
VectorType k4( &k3[nspecies] );
VectorType yp( &k4[nspecies] );
const int numSteps = minSteps;
const double h = t_stop / double(numSteps);
// Run the requested steps with h.
for (int step = 0; step < numSteps; step++)
{
// k1
k_rhs(0.0,y,k1, userData);
// k2
for (int ispecies = 0; ispecies < nspecies; ispecies++)
yp[ispecies] = y[ispecies] + 0.5*h*k1[ispecies];
k_rhs(0.0,yp,k2, userData);
// k3
for (int ispecies = 0; ispecies < nspecies; ispecies++)
yp[ispecies] = y[ispecies] + 0.5*h*k2[ispecies];
k_rhs(0.0,yp,k3, userData);
// k4
for (int ispecies = 0; ispecies < nspecies; ispecies++)
yp[ispecies] = y[ispecies] + h*k3[ispecies];
k_rhs(0.0,yp,k4, userData);
for (int ispecies = 0; ispecies < nspecies; ispecies++)
y[ispecies] += h*(k1[ispecies]/6.0 + k2[ispecies]/3.0 + k3[ispecies]/3.0 + k4[ispecies]/6.0);
} // end for (int step...
}
/* ---------------------------------------------------------------------- */
// f1 = dt*f(t,x)
// f2 = dt*f(t+ c20*dt,x + c21*f1)
// f3 = dt*f(t+ c30*dt,x + c31*f1 + c32*f2)
// f4 = dt*f(t+ c40*dt,x + c41*f1 + c42*f2 + c43*f3)
// f5 = dt*f(t+dt,x + c51*f1 + c52*f2 + c53*f3 + c54*f4)
// f6 = dt*f(t+ c60*dt,x + c61*f1 + c62*f2 + c63*f3 + c64*f4 + c65*f5)
//
// fifth-order runge-kutta integration
// x5 = x + b1*f1 + b3*f3 + b4*f4 + b5*f5 + b6*f6
// fourth-order runge-kutta integration
// x = x + a1*f1 + a3*f3 + a4*f4 + a5*f5
template <typename DeviceType>
template <typename VectorType, typename UserDataType>
void FixRxKokkos<DeviceType>::k_rkf45_step (const int neq, const double h, VectorType& y, VectorType& y_out, VectorType& rwk, UserDataType& userData) const
{
const double c21=0.25;
const double c31=0.09375;
const double c32=0.28125;
const double c41=0.87938097405553;
const double c42=-3.2771961766045;
const double c43=3.3208921256258;
const double c51=2.0324074074074;
const double c52=-8.0;
const double c53=7.1734892787524;
const double c54=-0.20589668615984;
const double c61=-0.2962962962963;
const double c62=2.0;
const double c63=-1.3816764132554;
const double c64=0.45297270955166;
const double c65=-0.275;
const double a1=0.11574074074074;
const double a3=0.54892787524366;
const double a4=0.5353313840156;
const double a5=-0.2;
const double b1=0.11851851851852;
const double b3=0.51898635477583;
const double b4=0.50613149034201;
const double b5=-0.18;
const double b6=0.036363636363636;
// local dependent variables (5 total)
VectorType& f1 = rwk;
VectorType f2( &rwk[ neq] );
VectorType f3( &rwk[2*neq] );
VectorType f4( &rwk[3*neq] );
VectorType f5( &rwk[4*neq] );
VectorType f6( &rwk[5*neq] );
// scratch for the intermediate solution.
VectorType& ytmp = y_out;
// 1)
k_rhs (0.0, y, f1, userData);
for (int k = 0; k < neq; k++){
f1[k] *= h;
ytmp[k] = y[k] + c21 * f1[k];
}
// 2)
k_rhs(0.0, ytmp, f2, userData);
for (int k = 0; k < neq; k++){
f2[k] *= h;
ytmp[k] = y[k] + c31 * f1[k] + c32 * f2[k];
}
// 3)
k_rhs(0.0, ytmp, f3, userData);
for (int k = 0; k < neq; k++) {
f3[k] *= h;
ytmp[k] = y[k] + c41 * f1[k] + c42 * f2[k] + c43 * f3[k];
}
// 4)
k_rhs(0.0, ytmp, f4, userData);
for (int k = 0; k < neq; k++) {
f4[k] *= h;
ytmp[k] = y[k] + c51 * f1[k] + c52 * f2[k] + c53 * f3[k] + c54 * f4[k];
}
// 5)
k_rhs(0.0, ytmp, f5, userData);
for (int k = 0; k < neq; k++) {
f5[k] *= h;
ytmp[k] = y[k] + c61*f1[k] + c62*f2[k] + c63*f3[k] + c64*f4[k] + c65*f5[k];
}
// 6)
k_rhs(0.0, ytmp, f6, userData);
for (int k = 0; k < neq; k++)
{
//const double f6 = h * ydot[k];
f6[k] *= h;
// 5th-order solution.
const double r5 = b1*f1[k] + b3*f3[k] + b4*f4[k] + b5*f5[k] + b6*f6[k];
// 4th-order solution.
const double r4 = a1*f1[k] + a3*f3[k] + a4*f4[k] + a5*f5[k];
// Truncation error: difference between 4th and 5th-order solutions.
rwk[k] = fabs(r5 - r4);
// Update solution.
//y_out[k] = y[k] + r5; // Local extrapolation
y_out[k] = y[k] + r4;
}
return;
}
template <typename DeviceType>
template <typename VectorType, typename UserDataType>
int FixRxKokkos<DeviceType>::k_rkf45_h0
(const int neq, const double t, const double t_stop,
const double hmin, const double hmax,
double& h0, VectorType& y, VectorType& rwk, UserDataType& userData) const
{
// Set lower and upper bounds on h0, and take geometric mean as first trial value.
// Exit with this value if the bounds cross each other.
// Adjust upper bound based on ydot ...
double hg = sqrt(hmin*hmax);
//if (hmax < hmin)
//{
// h0 = hg;
// return;
//}
// Start iteration to find solution to ... {WRMS norm of (h0^2 y'' / 2)} = 1
VectorType& ydot = rwk;
VectorType y1 ( &ydot[ neq] );
VectorType ydot1 ( &ydot[2*neq] );
const int max_iters = 10;
bool hnew_is_ok = false;
double hnew = hg;
int iter = 0;
// compute ydot at t=t0
k_rhs (t, y, ydot, userData);
while(1)
{
// Estimate y'' with finite-difference ...
for (int k = 0; k < neq; k++)
y1[k] = y[k] + hg * ydot[k];
// compute y' at t1
k_rhs (t + hg, y1, ydot1, userData);
// Compute WRMS norm of y''
double yddnrm = 0.0;
for (int k = 0; k < neq; k++){
double ydd = (ydot1[k] - ydot[k]) / hg;
double wterr = ydd / (relTol * fabs( y[k] ) + absTol);
yddnrm += wterr * wterr;
}
yddnrm = sqrt( yddnrm / double(neq) );
//std::cout << "iter " << _iter << " hg " << hg << " y'' " << yddnrm << std::endl;
//std::cout << "ydot " << ydot[neq-1] << std::endl;
// should we accept this?
if (hnew_is_ok || iter == max_iters){
hnew = hg;
//if (iter == max_iters)
// fprintf(stderr, "ERROR_HIN_MAX_ITERS\n");
break;
}
// Get the new value of h ...
hnew = (yddnrm*hmax*hmax > 2.0) ? sqrt(2.0 / yddnrm) : sqrt(hg * hmax);
// test the stopping conditions.
double hrat = hnew / hg;
// Accept this value ... the bias factor should bring it within range.
if ( (hrat > 0.5) && (hrat < 2.0) )
hnew_is_ok = true;
// If y'' is still bad after a few iterations, just accept h and give up.
if ( (iter > 1) && hrat > 2.0 ) {
hnew = hg;
hnew_is_ok = true;
}
//printf("iter=%d, yddnrw=%e, hnew=%e, hmin=%e, hmax=%e\n", iter, yddnrm, hnew, hmin, hmax);
hg = hnew;
iter ++;
}
// bound and bias estimate
h0 = hnew * 0.5;
h0 = fmax(h0, hmin);
h0 = fmin(h0, hmax);
//printf("h0=%e, hmin=%e, hmax=%e\n", h0, hmin, hmax);
return (iter + 1);
}
template <typename DeviceType>
template <typename VectorType, typename UserDataType>
void FixRxKokkos<DeviceType>::k_rkf45(const int neq, const double t_stop, VectorType& y, VectorType& rwork, UserDataType& userData, CounterType& counter) const
{
// Rounding coefficient.
const double uround = DBL_EPSILON;
// Adaption limit (shrink or grow)
const double adaption_limit = 4.0;
// Safety factor on the adaption. very specific but not necessary .. 0.9 is common.
const double hsafe = 0.840896415;
// Time rounding factor.
const double tround = t_stop * uround;
// Counters for diagnostics.
int nst = 0; // # of steps (accepted)
int nit = 0; // # of iterations total
int nfe = 0; // # of RHS evaluations
// Min/Max step-size limits.
const double h_min = 100.0 * tround;
const double h_max = (minSteps > 0) ? t_stop / double(minSteps) : t_stop;
// Set the initial step-size. 0 forces an internal estimate ... stable Euler step size.
double h = (minSteps > 0) ? t_stop / double(minSteps) : 0.0;
double t = 0.0;
if (h < h_min){
//fprintf(stderr,"hin not implemented yet\n");
//exit(-1);
nfe = k_rkf45_h0 (neq, t, t_stop, h_min, h_max, h, y, rwork, userData);
}
//printf("t= %e t_stop= %e h= %e\n", t, t_stop, h);
// Integrate until we reach the end time.
while (fabs(t - t_stop) > tround)
{
VectorType& yout = rwork;
VectorType eout ( &yout[neq] );
// Take a trial step.
k_rkf45_step (neq, h, y, yout, eout, userData);
// Estimate the solution error.
// ... weighted 2-norm of the error.
double err2 = 0.0;
for (int k = 0; k < neq; k++){
const double wterr = eout[k] / (relTol * fabs( y[k] ) + absTol);
err2 += wterr * wterr;
}
double err = fmax( uround, sqrt( err2 / double(nspecies) ));
// Accept the solution?
if (err <= 1.0 || h <= h_min){
t += h;
nst++;
for (int k = 0; k < neq; k++)
y[k] = yout[k];
}
// Adjust h for the next step.
double hfac = hsafe * sqrt( sqrt( 1.0 / err ) );
// Limit the adaption.
hfac = fmax( hfac, 1.0 / adaption_limit );
hfac = fmin( hfac, adaption_limit );
// Apply the adaption factor...
h *= hfac;
// Limit h.
h = fmin( h, h_max );
h = fmax( h, h_min );
// Stretch h if we're within 5% ... and we didn't just fail.
if (err <= 1.0 && (t + 1.05*h) > t_stop)
h = t_stop - t;
// And don't overshoot the end.
if (t + h > t_stop)
h = t_stop - t;
nit++;
nfe += 6;
if (maxIters && nit > maxIters){
//fprintf(stderr,"atom[%d] took too many iterations in rkf45 %d %e %e\n", id, nit, t, t_stop);
counter.nFails ++;
break;
// We should set an error here so that the solution is not used!
}
} // end while
counter.nSteps += nst;
counter.nIters += nit;
counter.nFuncs += nfe;
//printf("id= %d nst= %d nit= %d\n", id, nst, nit);
}
/* ---------------------------------------------------------------------- */
// f1 = dt*f(t,x)
// f2 = dt*f(t+ c20*dt,x + c21*f1)
// f3 = dt*f(t+ c30*dt,x + c31*f1 + c32*f2)
// f4 = dt*f(t+ c40*dt,x + c41*f1 + c42*f2 + c43*f3)
// f5 = dt*f(t+dt,x + c51*f1 + c52*f2 + c53*f3 + c54*f4)
// f6 = dt*f(t+ c60*dt,x + c61*f1 + c62*f2 + c63*f3 + c64*f4 + c65*f5)
//
// fifth-order runge-kutta integration
// x5 = x + b1*f1 + b3*f3 + b4*f4 + b5*f5 + b6*f6
// fourth-order runge-kutta integration
// x = x + a1*f1 + a3*f3 + a4*f4 + a5*f5
template <typename DeviceType>
void FixRxKokkos<DeviceType>::rkf45_step (const int neq, const double h, double y[], double y_out[], double rwk[], void* v_param) const
{
const double c21=0.25;
const double c31=0.09375;
const double c32=0.28125;
const double c41=0.87938097405553;
const double c42=-3.2771961766045;
const double c43=3.3208921256258;
const double c51=2.0324074074074;
const double c52=-8.0;
const double c53=7.1734892787524;
const double c54=-0.20589668615984;
const double c61=-0.2962962962963;
const double c62=2.0;
const double c63=-1.3816764132554;
const double c64=0.45297270955166;
const double c65=-0.275;
const double a1=0.11574074074074;
const double a3=0.54892787524366;
const double a4=0.5353313840156;
const double a5=-0.2;
const double b1=0.11851851851852;
const double b3=0.51898635477583;
const double b4=0.50613149034201;
const double b5=-0.18;
const double b6=0.036363636363636;
// local dependent variables (5 total)
double* f1 = &rwk[ 0];
double* f2 = &rwk[ neq];
double* f3 = &rwk[2*neq];
double* f4 = &rwk[3*neq];
double* f5 = &rwk[4*neq];
double* f6 = &rwk[5*neq];
// scratch for the intermediate solution.
//double* ytmp = &rwk[6*neq];
double* ytmp = y_out;
// 1)
rhs (0.0, y, f1, v_param);
for (int k = 0; k < neq; k++){
f1[k] *= h;
ytmp[k] = y[k] + c21 * f1[k];
}
// 2)
rhs(0.0, ytmp, f2, v_param);
for (int k = 0; k < neq; k++){
f2[k] *= h;
ytmp[k] = y[k] + c31 * f1[k] + c32 * f2[k];
}
// 3)
rhs(0.0, ytmp, f3, v_param);
for (int k = 0; k < neq; k++) {
f3[k] *= h;
ytmp[k] = y[k] + c41 * f1[k] + c42 * f2[k] + c43 * f3[k];
}
// 4)
rhs(0.0, ytmp, f4, v_param);
for (int k = 0; k < neq; k++) {
f4[k] *= h;
ytmp[k] = y[k] + c51 * f1[k] + c52 * f2[k] + c53 * f3[k] + c54 * f4[k];
}
// 5)
rhs(0.0, ytmp, f5, v_param);
for (int k = 0; k < neq; k++) {
f5[k] *= h;
ytmp[k] = y[k] + c61*f1[k] + c62*f2[k] + c63*f3[k] + c64*f4[k] + c65*f5[k];
}
// 6)
rhs(0.0, ytmp, f6, v_param);
for (int k = 0; k < neq; k++)
{
//const double f6 = h * ydot[k];
f6[k] *= h;
// 5th-order solution.
const double r5 = b1*f1[k] + b3*f3[k] + b4*f4[k] + b5*f5[k] + b6*f6[k];
// 4th-order solution.
const double r4 = a1*f1[k] + a3*f3[k] + a4*f4[k] + a5*f5[k];
// Truncation error: difference between 4th and 5th-order solutions.
rwk[k] = fabs(r5 - r4);
// Update solution.
//y_out[k] = y[k] + r5; // Local extrapolation
y_out[k] = y[k] + r4;
}
return;
}
template <typename DeviceType>
int FixRxKokkos<DeviceType>::rkf45_h0
(const int neq, const double t, const double t_stop,
const double hmin, const double hmax,
double& h0, double y[], double rwk[], void* v_params) const
{
// Set lower and upper bounds on h0, and take geometric mean as first trial value.
// Exit with this value if the bounds cross each other.
// Adjust upper bound based on ydot ...
double hg = sqrt(hmin*hmax);
//if (hmax < hmin)
//{
// h0 = hg;
// return;
//}
// Start iteration to find solution to ... {WRMS norm of (h0^2 y'' / 2)} = 1
double *ydot = rwk;
double *y1 = ydot + neq;
double *ydot1 = y1 + neq;
const int max_iters = 10;
bool hnew_is_ok = false;
double hnew = hg;
int iter = 0;
// compute ydot at t=t0
rhs (t, y, ydot, v_params);
while(1)
{
// Estimate y'' with finite-difference ...
for (int k = 0; k < neq; k++)
y1[k] = y[k] + hg * ydot[k];
// compute y' at t1
rhs (t + hg, y1, ydot1, v_params);
// Compute WRMS norm of y''
double yddnrm = 0.0;
for (int k = 0; k < neq; k++){
double ydd = (ydot1[k] - ydot[k]) / hg;
double wterr = ydd / (relTol * fabs( y[k] ) + absTol);
yddnrm += wterr * wterr;
}
yddnrm = sqrt( yddnrm / double(neq) );
//std::cout << "iter " << _iter << " hg " << hg << " y'' " << yddnrm << std::endl;
//std::cout << "ydot " << ydot[neq-1] << std::endl;
// should we accept this?
if (hnew_is_ok || iter == max_iters){
hnew = hg;
if (iter == max_iters)
fprintf(stderr, "ERROR_HIN_MAX_ITERS\n");
break;
}
// Get the new value of h ...
hnew = (yddnrm*hmax*hmax > 2.0) ? sqrt(2.0 / yddnrm) : sqrt(hg * hmax);
// test the stopping conditions.
double hrat = hnew / hg;
// Accept this value ... the bias factor should bring it within range.
if ( (hrat > 0.5) && (hrat < 2.0) )
hnew_is_ok = true;
// If y'' is still bad after a few iterations, just accept h and give up.
if ( (iter > 1) && hrat > 2.0 ) {
hnew = hg;
hnew_is_ok = true;
}
//printf("iter=%d, yddnrw=%e, hnew=%e, hmin=%e, hmax=%e\n", iter, yddnrm, hnew, hmin, hmax);
hg = hnew;
iter ++;
}
// bound and bias estimate
h0 = hnew * 0.5;
h0 = fmax(h0, hmin);
h0 = fmin(h0, hmax);
//printf("h0=%e, hmin=%e, hmax=%e\n", h0, hmin, hmax);
return (iter + 1);
}
template <typename DeviceType>
void FixRxKokkos<DeviceType>::rkf45(const int neq, const double t_stop, double *y, double *rwork, void *v_param, CounterType& counter) const
{
// Rounding coefficient.
const double uround = DBL_EPSILON;
// Adaption limit (shrink or grow)
const double adaption_limit = 4.0;
// Safety factor on the adaption. very specific but not necessary .. 0.9 is common.
const double hsafe = 0.840896415;
// Time rounding factor.
const double tround = t_stop * uround;
// Counters for diagnostics.
int nst = 0; // # of steps (accepted)
int nit = 0; // # of iterations total
int nfe = 0; // # of RHS evaluations
// Min/Max step-size limits.
const double h_min = 100.0 * tround;
const double h_max = (minSteps > 0) ? t_stop / double(minSteps) : t_stop;
// Set the initial step-size. 0 forces an internal estimate ... stable Euler step size.
double h = (minSteps > 0) ? t_stop / double(minSteps) : 0.0;
double t = 0.0;
if (h < h_min){
//fprintf(stderr,"hin not implemented yet\n");
//exit(-1);
nfe = rkf45_h0 (neq, t, t_stop, h_min, h_max, h, y, rwork, v_param);
}
//printf("t= %e t_stop= %e h= %e\n", t, t_stop, h);
// Integrate until we reach the end time.
while (fabs(t - t_stop) > tround){
double *yout = rwork;
double *eout = yout + neq;
// Take a trial step.
rkf45_step (neq, h, y, yout, eout, v_param);
// Estimate the solution error.
// ... weighted 2-norm of the error.
double err2 = 0.0;
for (int k = 0; k < neq; k++){
const double wterr = eout[k] / (relTol * fabs( y[k] ) + absTol);
err2 += wterr * wterr;
}
double err = fmax( uround, sqrt( err2 / double(nspecies) ));
// Accept the solution?
if (err <= 1.0 || h <= h_min){
t += h;
nst++;
for (int k = 0; k < neq; k++)
y[k] = yout[k];
}
// Adjust h for the next step.
double hfac = hsafe * sqrt( sqrt( 1.0 / err ) );
// Limit the adaption.
hfac = fmax( hfac, 1.0 / adaption_limit );
hfac = fmin( hfac, adaption_limit );
// Apply the adaption factor...
h *= hfac;
// Limit h.
h = fmin( h, h_max );
h = fmax( h, h_min );
// Stretch h if we're within 5% ... and we didn't just fail.
if (err <= 1.0 && (t + 1.05*h) > t_stop)
h = t_stop - t;
// And don't overshoot the end.
if (t + h > t_stop)
h = t_stop - t;
nit++;
nfe += 6;
if (maxIters && nit > maxIters){
//fprintf(stderr,"atom[%d] took too many iterations in rkf45 %d %e %e\n", id, nit, t, t_stop);
counter.nFails ++;
break;
// We should set an error here so that the solution is not used!
}
} // end while
counter.nSteps += nst;
counter.nIters += nit;
counter.nFuncs += nfe;
//printf("id= %d nst= %d nit= %d\n", id, nst, nit);
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
int FixRxKokkos<DeviceType>::rhs(double t, const double *y, double *dydt, void *params) const
{
// Use the sparse format instead.
if (useSparseKinetics)
return this->rhs_sparse( t, y, dydt, params);
else
return this->rhs_dense ( t, y, dydt, params);
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
int FixRxKokkos<DeviceType>::rhs_dense(double t, const double *y, double *dydt, void *params) const
{
UserRHSData *userData = (UserRHSData *) params;
double *rxnRateLaw = userData->rxnRateLaw;
double *kFor = userData->kFor;
//const double VDPD = domain->xprd * domain->yprd * domain->zprd / atom->natoms;
//const int nspecies = atom->nspecies_dpd;
for(int ispecies=0; ispecies<nspecies; ispecies++)
dydt[ispecies] = 0.0;
// Construct the reaction rate laws
for(int jrxn=0; jrxn<nreactions; jrxn++){
double rxnRateLawForward = kFor[jrxn];
for(int ispecies=0; ispecies<nspecies; ispecies++){
const double concentration = y[ispecies]/VDPD;
rxnRateLawForward *= pow( concentration, d_kineticsData.stoichReactants(jrxn,ispecies) );
//rxnRateLawForward *= pow(concentration,stoichReactants[jrxn][ispecies]);
}
rxnRateLaw[jrxn] = rxnRateLawForward;
}
// Construct the reaction rates for each species
for(int ispecies=0; ispecies<nspecies; ispecies++)
for(int jrxn=0; jrxn<nreactions; jrxn++)
{
dydt[ispecies] += d_kineticsData.stoich(jrxn,ispecies) *VDPD*rxnRateLaw[jrxn];
//dydt[ispecies] += stoich[jrxn][ispecies]*VDPD*rxnRateLaw[jrxn];
}
return 0;
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
int FixRxKokkos<DeviceType>::rhs_sparse(double t, const double *y, double *dydt, void *v_params) const
{
UserRHSData *userData = (UserRHSData *) v_params;
//const double VDPD = domain->xprd * domain->yprd * domain->zprd / atom->natoms;
#define kFor (userData->kFor)
#define kRev (NULL)
#define rxnRateLaw (userData->rxnRateLaw)
#define conc (dydt)
#define maxReactants (this->sparseKinetics_maxReactants)
#define maxSpecies (this->sparseKinetics_maxSpecies)
#define nuk (this->d_kineticsData.nuk)
#define nu (this->d_kineticsData.nu)
#define inu (this->d_kineticsData.inu)
#define isIntegral(idx) ( SparseKinetics_enableIntegralReactions \
&& this->d_kineticsData.isIntegral(idx) )
for (int k = 0; k < nspecies; ++k)
conc[k] = y[k] / VDPD;
// Construct the reaction rate laws
for (int i = 0; i < nreactions; ++i)
{
double rxnRateLawForward;
if (isIntegral(i)){
rxnRateLawForward = kFor[i] * powint( conc[ nuk(i,0) ], inu(i,0) );
for (int kk = 1; kk < maxReactants; ++kk){
const int k = nuk(i,kk);
if (k == SparseKinetics_invalidIndex) break;
//if (k != SparseKinetics_invalidIndex)
rxnRateLawForward *= powint( conc[k], inu(i,kk) );
}
} else {
rxnRateLawForward = kFor[i] * pow( conc[ nuk(i,0) ], nu(i,0) );
for (int kk = 1; kk < maxReactants; ++kk){
const int k = nuk(i,kk);
if (k == SparseKinetics_invalidIndex) break;
//if (k != SparseKinetics_invalidIndex)
rxnRateLawForward *= pow( conc[k], nu(i,kk) );
}
}
rxnRateLaw[i] = rxnRateLawForward;
}
// Construct the reaction rates for each species from the
// Stoichiometric matrix and ROP vector.
for (int k = 0; k < nspecies; ++k)
dydt[k] = 0.0;
for (int i = 0; i < nreactions; ++i){
// Reactants ...
dydt[ nuk(i,0) ] -= nu(i,0) * rxnRateLaw[i];
for (int kk = 1; kk < maxReactants; ++kk){
const int k = nuk(i,kk);
if (k == SparseKinetics_invalidIndex) break;
//if (k != SparseKinetics_invalidIndex)
dydt[k] -= nu(i,kk) * rxnRateLaw[i];
}
// Products ...
dydt[ nuk(i,maxReactants) ] += nu(i,maxReactants) * rxnRateLaw[i];
for (int kk = maxReactants+1; kk < maxSpecies; ++kk){
const int k = nuk(i,kk);
if (k == SparseKinetics_invalidIndex) break;
//if (k != SparseKinetics_invalidIndex)
dydt[k] += nu(i,kk) * rxnRateLaw[i];
}
}
// Add in the volume factor to convert to the proper units.
for (int k = 0; k < nspecies; ++k)
dydt[k] *= VDPD;
#undef kFor
#undef kRev
#undef rxnRateLaw
#undef conc
#undef maxReactants
#undef maxSpecies
#undef nuk
#undef nu
#undef inu
#undef isIntegral
//#undef invalidIndex
return 0;
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
template <typename VectorType, typename UserDataType>
int FixRxKokkos<DeviceType>::k_rhs(double t, const VectorType& y, VectorType& dydt, UserDataType& userData) const
{
// Use the sparse format instead.
if (useSparseKinetics)
return this->k_rhs_sparse( t, y, dydt, userData);
else
return this->k_rhs_dense ( t, y, dydt, userData);
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
template <typename VectorType, typename UserDataType>
int FixRxKokkos<DeviceType>::k_rhs_dense(double t, const VectorType& y, VectorType& dydt, UserDataType& userData) const
{
#define rxnRateLaw (userData.rxnRateLaw)
#define kFor (userData.kFor )
//const double VDPD = domain->xprd * domain->yprd * domain->zprd / atom->natoms;
//const int nspecies = atom->nspecies_dpd;
for(int ispecies=0; ispecies<nspecies; ispecies++)
dydt[ispecies] = 0.0;
// Construct the reaction rate laws
for(int jrxn=0; jrxn<nreactions; jrxn++){
double rxnRateLawForward = kFor[jrxn];
for(int ispecies=0; ispecies<nspecies; ispecies++){
const double concentration = y[ispecies]/VDPD;
rxnRateLawForward *= pow( concentration, d_kineticsData.stoichReactants(jrxn,ispecies) );
//rxnRateLawForward *= pow(concentration,stoichReactants[jrxn][ispecies]);
}
rxnRateLaw[jrxn] = rxnRateLawForward;
}
// Construct the reaction rates for each species
for(int ispecies=0; ispecies<nspecies; ispecies++)
for(int jrxn=0; jrxn<nreactions; jrxn++)
{
dydt[ispecies] += d_kineticsData.stoich(jrxn,ispecies) *VDPD*rxnRateLaw[jrxn];
//dydt[ispecies] += stoich[jrxn][ispecies]*VDPD*rxnRateLaw[jrxn];
}
#undef rxnRateLaw
#undef kFor
return 0;
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
template <typename VectorType, typename UserDataType>
int FixRxKokkos<DeviceType>::k_rhs_sparse(double t, const VectorType& y, VectorType& dydt, UserDataType& userData) const
{
#define kFor (userData.kFor)
#define kRev (NULL)
#define rxnRateLaw (userData.rxnRateLaw)
#define conc (dydt)
#define maxReactants (this->sparseKinetics_maxReactants)
#define maxSpecies (this->sparseKinetics_maxSpecies)
#define nuk (this->d_kineticsData.nuk)
#define nu (this->d_kineticsData.nu)
#define inu (this->d_kineticsData.inu)
#define isIntegral(idx) ( SparseKinetics_enableIntegralReactions \
&& this->d_kineticsData.isIntegral(idx) )
for (int k = 0; k < nspecies; ++k)
conc[k] = y[k] / VDPD;
// Construct the reaction rate laws
for (int i = 0; i < nreactions; ++i)
{
double rxnRateLawForward;
if (isIntegral(i)){
rxnRateLawForward = kFor[i] * powint( conc[ nuk(i,0) ], inu(i,0) );
for (int kk = 1; kk < maxReactants; ++kk){
const int k = nuk(i,kk);
if (k == SparseKinetics_invalidIndex) break;
//if (k != SparseKinetics_invalidIndex)
rxnRateLawForward *= powint( conc[k], inu(i,kk) );
}
} else {
rxnRateLawForward = kFor[i] * pow( conc[ nuk(i,0) ], nu(i,0) );
for (int kk = 1; kk < maxReactants; ++kk){
const int k = nuk(i,kk);
if (k == SparseKinetics_invalidIndex) break;
//if (k != SparseKinetics_invalidIndex)
rxnRateLawForward *= pow( conc[k], nu(i,kk) );
}
}
rxnRateLaw[i] = rxnRateLawForward;
}
// Construct the reaction rates for each species from the
// Stoichiometric matrix and ROP vector.
for (int k = 0; k < nspecies; ++k)
dydt[k] = 0.0;
for (int i = 0; i < nreactions; ++i){
// Reactants ...
dydt[ nuk(i,0) ] -= nu(i,0) * rxnRateLaw[i];
for (int kk = 1; kk < maxReactants; ++kk){
const int k = nuk(i,kk);
if (k == SparseKinetics_invalidIndex) break;
//if (k != SparseKinetics_invalidIndex)
dydt[k] -= nu(i,kk) * rxnRateLaw[i];
}
// Products ...
dydt[ nuk(i,maxReactants) ] += nu(i,maxReactants) * rxnRateLaw[i];
for (int kk = maxReactants+1; kk < maxSpecies; ++kk){
const int k = nuk(i,kk);
if (k == SparseKinetics_invalidIndex) break;
//if (k != SparseKinetics_invalidIndex)
dydt[k] += nu(i,kk) * rxnRateLaw[i];
}
}
// Add in the volume factor to convert to the proper units.
for (int k = 0; k < nspecies; ++k)
dydt[k] *= VDPD;
#undef kFor
#undef kRev
#undef rxnRateLaw
#undef conc
#undef maxReactants
#undef maxSpecies
#undef nuk
#undef nu
#undef inu
#undef isIntegral
//#undef invalidIndex
return 0;
}
/* ---------------------------------------------------------------------- */
/*template <typename DeviceType>
template <typename SolverType>
KOKKOS_INLINE_FUNCTION
void FixRxKokkos<DeviceType>::operator()(SolverType, const int &i) const
{
if (atom->mask[i] & groupbit)
{
double *rwork = new double[8*nspecies];
UserRHSData userData;
userData.kFor = new double[nreactions];
userData.rxnRateLaw = new double[nreactions];
int ode_counter[4] = { 0 };
const double theta = (localTempFlag) ? dpdThetaLocal[i] : atom->dpdTheta[i];
//Compute the reaction rate constants
for (int irxn = 0; irxn < nreactions; irxn++)
{
if (SolverType::setToZero)
userData.kFor[irxn] = 0.0;
else
userData.kFor[irxn] = Arr[irxn]*pow(theta,nArr[irxn])*exp(-Ea[irxn]/force->boltz/theta);
}
if (odeIntegrationFlag == ODE_LAMMPS_RK4)
rk4(i, rwork, &userData);
else if (odeIntegrationFlag == ODE_LAMMPS_RKF45)
rkf45(i, rwork, &userData, ode_counter);
delete [] rwork;
delete [] userData.kFor;
delete [] userData.rxnRateLaw;
}
} */
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
void FixRxKokkos<DeviceType>::create_kinetics_data(void)
{
//printf("Inside FixRxKokkos::create_kinetics_data\n");
memory->create_kokkos( d_kineticsData.Arr, h_kineticsData.Arr, nreactions, "KineticsType::Arr");
memory->create_kokkos( d_kineticsData.nArr, h_kineticsData.nArr, nreactions, "KineticsType::nArr");
memory->create_kokkos( d_kineticsData.Ea, h_kineticsData.Ea, nreactions, "KineticsType::Ea");
for (int i = 0; i < nreactions; ++i)
{
h_kineticsData.Arr[i] = Arr[i];
h_kineticsData.nArr[i] = nArr[i];
h_kineticsData.Ea[i] = Ea[i];
}
Kokkos::deep_copy( d_kineticsData.Arr, h_kineticsData.Arr );
Kokkos::deep_copy( d_kineticsData.nArr, h_kineticsData.nArr );
Kokkos::deep_copy( d_kineticsData.Ea, h_kineticsData.Ea );
if (useSparseKinetics)
{
memory->create_kokkos( d_kineticsData.nu , h_kineticsData.nu , nreactions, sparseKinetics_maxSpecies, "KineticsType::nu");
memory->create_kokkos( d_kineticsData.nuk, h_kineticsData.nuk, nreactions, sparseKinetics_maxSpecies, "KineticsType::nuk");
for (int i = 0; i < nreactions; ++i)
for (int k = 0; k < sparseKinetics_maxSpecies; ++k)
{
h_kineticsData.nu (i,k) = sparseKinetics_nu [i][k];
h_kineticsData.nuk(i,k) = sparseKinetics_nuk[i][k];
}
Kokkos::deep_copy( d_kineticsData.nu, h_kineticsData.nu );
Kokkos::deep_copy( d_kineticsData.nuk, h_kineticsData.nuk );
if (SparseKinetics_enableIntegralReactions)
{
memory->create_kokkos( d_kineticsData.inu, h_kineticsData.inu, nreactions, sparseKinetics_maxSpecies, "KineticsType::inu");
memory->create_kokkos( d_kineticsData.isIntegral, h_kineticsData.isIntegral, nreactions, "KineticsType::isIntegral");
for (int i = 0; i < nreactions; ++i)
{
h_kineticsData.isIntegral(i) = sparseKinetics_isIntegralReaction[i];
for (int k = 0; k < sparseKinetics_maxSpecies; ++k)
h_kineticsData.inu(i,k) = sparseKinetics_inu[i][k];
}
Kokkos::deep_copy( d_kineticsData.inu, h_kineticsData.inu );
Kokkos::deep_copy( d_kineticsData.isIntegral, h_kineticsData.isIntegral );
}
}
//else
//{
// Dense option
memory->create_kokkos( d_kineticsData.stoich, h_kineticsData.stoich, nreactions, nspecies, "KineticsType::stoich");
memory->create_kokkos( d_kineticsData.stoichReactants, h_kineticsData.stoichReactants, nreactions, nspecies, "KineticsType::stoichReactants");
memory->create_kokkos( d_kineticsData.stoichProducts, h_kineticsData.stoichProducts, nreactions, nspecies, "KineticsType::stoichProducts");
for (int i = 0; i < nreactions; ++i)
for (int k = 0; k < nspecies; ++k)
{
h_kineticsData.stoich(i,k) = stoich[i][k];
h_kineticsData.stoichReactants(i,k) = stoichReactants[i][k];
h_kineticsData.stoichProducts(i,k) = stoichProducts[i][k];
}
Kokkos::deep_copy( d_kineticsData.stoich, h_kineticsData.stoich );
Kokkos::deep_copy( d_kineticsData.stoichReactants, h_kineticsData.stoichReactants );
Kokkos::deep_copy( d_kineticsData.stoichProducts, h_kineticsData.stoichProducts );
//}
update_kinetics_data = false;
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
void FixRxKokkos<DeviceType>::setup_pre_force(int vflag)
{
//printf("Inside FixRxKokkos<DeviceType>::setup_pre_force restartFlag= %d\n", my_restartFlag);
if (my_restartFlag)
my_restartFlag = 0;
else
this->solve_reactions( vflag, false );
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
void FixRxKokkos<DeviceType>::pre_force(int vflag)
{
//printf("Inside FixRxKokkos<DeviceType>::pre_force localTempFlag= %d\n", localTempFlag);
this->solve_reactions( vflag, true );
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
KOKKOS_INLINE_FUNCTION
void FixRxKokkos<DeviceType>::operator()(Tag_FixRxKokkos_zeroCounterViews, const int& i) const
{
d_diagnosticCounterPerODEnSteps(i) = 0;
d_diagnosticCounterPerODEnFuncs(i) = 0;
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
template <bool ZERO_RATES>
KOKKOS_INLINE_FUNCTION
void FixRxKokkos<DeviceType>::operator()(Tag_FixRxKokkos_solveSystems<ZERO_RATES>, const int& i, CounterType& counter) const
{
if (d_mask(i) & groupbit)
{
StridedArrayType<double,1> y( d_scratchSpace.ptr_on_device() + scratchSpaceSize * i );
StridedArrayType<double,1> rwork( &y[nspecies] );
UserRHSDataKokkos<1> userData;
userData.kFor.m_data = &( rwork[7*nspecies] );
userData.rxnRateLaw.m_data = &( userData.kFor[ nreactions ] );
CounterType counter_i;
const double theta = (localTempFlag) ? d_dpdThetaLocal(i) : d_dpdTheta(i);
//Compute the reaction rate constants
for (int irxn = 0; irxn < nreactions; irxn++)
{
if (ZERO_RATES)
userData.kFor[irxn] = 0.0;
else
{
userData.kFor[irxn] = d_kineticsData.Arr(irxn) *
pow(theta, d_kineticsData.nArr(irxn)) *
exp(-d_kineticsData.Ea(irxn) / boltz / theta);
}
}
// Update ConcOld and initialize the ODE solution vector y[].
for (int ispecies = 0; ispecies < nspecies; ispecies++)
{
const double tmp = d_dvector(ispecies, i);
d_dvector(ispecies+nspecies, i) = tmp;
y[ispecies] = tmp;
}
// Solver the ODE system.
if (odeIntegrationFlag == ODE_LAMMPS_RK4)
{
k_rk4(t_stop, y, rwork, userData);
}
else if (odeIntegrationFlag == ODE_LAMMPS_RKF45)
{
k_rkf45(nspecies, t_stop, y, rwork, userData, counter_i);
if (diagnosticFrequency == 1)
{
d_diagnosticCounterPerODEnSteps(i) = counter_i.nSteps;
d_diagnosticCounterPerODEnFuncs(i) = counter_i.nFuncs;
}
}
// Store the solution back in dvector.
for (int ispecies = 0; ispecies < nspecies; ispecies++)
{
if (y[ispecies] < -1.0e-10)
{
//error->one(FLERR,"Computed concentration in RK solver is < -1.0e-10");
k_error_flag.template view<DeviceType>()() = 2;
// This should be an atomic update.
}
else if (y[ispecies] < MY_EPSILON)
y[ispecies] = 0.0;
d_dvector(ispecies,i) = y[ispecies];
}
// Update the iteration statistics counter. Is this unique for each iteration?
counter += counter_i;
} // if
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
void FixRxKokkos<DeviceType>::solve_reactions(const int vflag, const bool isPreForce)
{
//printf("Inside FixRxKokkos<DeviceType>::solve_reactions localTempFlag= %d isPreForce= %s\n", localTempFlag, isPreForce ? "True" : "false");
copymode = 1;
if (update_kinetics_data)
create_kinetics_data();
TimerType timer_start = getTimeStamp();
//const int nlocal = atom->nlocal;
this->nlocal = atom->nlocal;
const int nghost = atom->nghost;
const int newton_pair = force->newton_pair;
// Set the forward rates to zero if acting as setup_pre_force.
const bool setRatesToZero = (isPreForce == false);
if (localTempFlag)
{
const int count = nlocal + (newton_pair ? nghost : 0);
if (count > k_dpdThetaLocal.template view<DeviceType>().dimension_0()) {
memory->destroy_kokkos (k_dpdThetaLocal, dpdThetaLocal);
memory->create_kokkos (k_dpdThetaLocal, dpdThetaLocal, count, "FixRxKokkos::dpdThetaLocal");
this->d_dpdThetaLocal = k_dpdThetaLocal.template view<DeviceType>();
this->h_dpdThetaLocal = k_dpdThetaLocal.h_view;
}
const int neighflag = lmp->kokkos->neighflag;
#define _template_switch(_wtflag, _localTempFlag) { \
if (neighflag == HALF) \
if (newton_pair) \
computeLocalTemperature<_wtflag, _localTempFlag, true , HALF> (); \
else \
computeLocalTemperature<_wtflag, _localTempFlag, false, HALF> (); \
else if (neighflag == HALFTHREAD) \
if (newton_pair) \
computeLocalTemperature<_wtflag, _localTempFlag, true , HALFTHREAD> (); \
else \
computeLocalTemperature<_wtflag, _localTempFlag, false, HALFTHREAD> (); \
else if (neighflag == FULL) \
if (newton_pair) \
computeLocalTemperature<_wtflag, _localTempFlag, true , FULL> (); \
else \
computeLocalTemperature<_wtflag, _localTempFlag, false, FULL> (); \
}
// Are there is no other options than wtFlag = (0)LUCY and localTempFlag = NONE : HARMONIC?
if (localTempFlag == HARMONIC) {
_template_switch(LUCY, HARMONIC)
}
else {
_template_switch(LUCY, NONE)
}
#undef _template_switch
}
TimerType timer_localTemperature = getTimeStamp();
// Total counters from the ODE solvers.
CounterType TotalCounters;
// Set data needed in the operators.
// ...
// Local references to the atomKK objects.
//typename ArrayTypes<DeviceType>::t_efloat_1d d_dpdTheta = atomKK->k_dpdTheta.view<DeviceType>();
//typename ArrayTypes<DeviceType>::t_float_2d d_dvector = atomKK->k_dvector.view<DeviceType>();
//typename ArrayTypes<DeviceType>::t_int_1d d_mask = atomKK->k_mask.view<DeviceType>();
this->d_dpdTheta = atomKK->k_dpdTheta.view<DeviceType>();
this->d_dvector = atomKK->k_dvector.view<DeviceType>();
this->d_mask = atomKK->k_mask.view<DeviceType>();
// Get up-to-date data.
atomKK->sync( execution_space, MASK_MASK | DVECTOR_MASK | DPDTHETA_MASK );
// Set some constants outside of the parallel_for
//const double boltz = force->boltz;
//const double t_stop = update->dt; // DPD time-step and integration length.
this->boltz = force->boltz;
this->t_stop = update->dt; // DPD time-step and integration length.
// Average DPD volume. Used in the RHS function.
this->VDPD = domain->xprd * domain->yprd * domain->zprd / atom->natoms;
if (odeIntegrationFlag == ODE_LAMMPS_RKF45 && diagnosticFrequency == 1)
{
memory->create_kokkos (k_diagnosticCounterPerODEnSteps, diagnosticCounterPerODEnSteps, nlocal, "FixRxKokkos::diagnosticCounterPerODEnSteps");
memory->create_kokkos (k_diagnosticCounterPerODEnFuncs, diagnosticCounterPerODEnFuncs, nlocal, "FixRxKokkos::diagnosticCounterPerODEnFuncs");
d_diagnosticCounterPerODEnSteps = k_diagnosticCounterPerODEnSteps.template view<DeviceType>();
d_diagnosticCounterPerODEnFuncs = k_diagnosticCounterPerODEnFuncs.template view<DeviceType>();
Kokkos::parallel_for ( Kokkos::RangePolicy<DeviceType, Tag_FixRxKokkos_zeroCounterViews>(0,nlocal), *this);
//Kokkos::parallel_for ( nlocal,
// LAMMPS_LAMBDA(const int i)
// {
// d_diagnosticCounterPerODEnSteps(i) = 0;
// d_diagnosticCounterPerODEnFuncs(i) = 0;
// }
// );
}
// Error flag for any failures.
//DAT::tdual_int_scalar k_error_flag("pair:error_flag");
// Initialize and sync the device flag.
k_error_flag.h_view() = 0;
k_error_flag.template modify<LMPHostType>();
k_error_flag.template sync<DeviceType>();
// Create scratch array space.
//const size_t scratchSpaceSize = (8*nspecies + 2*nreactions);
this->scratchSpaceSize = (8*nspecies + 2*nreactions);
//double *scratchSpace = new double[ scratchSpaceSize * nlocal ];
//typename ArrayTypes<DeviceType>::t_double_1d d_scratchSpace("d_scratchSpace", scratchSpaceSize * nlocal);
if (nlocal*scratchSpaceSize > d_scratchSpace.dimension_0()) {
memory->destroy_kokkos (d_scratchSpace);
memory->create_kokkos (d_scratchSpace, nlocal*scratchSpaceSize, "FixRxKokkos::d_scratchSpace");
}
#if 0
Kokkos::parallel_reduce( nlocal, LAMMPS_LAMBDA(int i, CounterType &counter)
{
if (d_mask(i) & groupbit)
{
//double *y = new double[8*nspecies];
//double *rwork = y + nspecies;
//StridedArrayType<double,1> _y( y );
//StridedArrayType<double,1> _rwork( rwork );
StridedArrayType<double,1> y( d_scratchSpace.ptr_on_device() + scratchSpaceSize * i );
StridedArrayType<double,1> rwork( &y[nspecies] );
//UserRHSData userData;
//userData.kFor = new double[nreactions];
//userData.rxnRateLaw = new double[nreactions];
//UserRHSDataKokkos<1> userDataKokkos;
//userDataKokkos.kFor.m_data = userData.kFor;
//userDataKokkos.rxnRateLaw.m_data = userData.rxnRateLaw;
UserRHSDataKokkos<1> userData;
userData.kFor.m_data = &( rwork[7*nspecies] );
userData.rxnRateLaw.m_data = &( userData.kFor[ nreactions ] );
CounterType counter_i;
const double theta = (localTempFlag) ? d_dpdThetaLocal(i) : d_dpdTheta(i);
//Compute the reaction rate constants
for (int irxn = 0; irxn < nreactions; irxn++)
{
if (setRatesToZero)
userData.kFor[irxn] = 0.0;
else
{
userData.kFor[irxn] = d_kineticsData.Arr(irxn) *
pow(theta, d_kineticsData.nArr(irxn)) *
exp(-d_kineticsData.Ea(irxn) / boltz / theta);
}
}
// Update ConcOld and initialize the ODE solution vector y[].
for (int ispecies = 0; ispecies < nspecies; ispecies++)
{
const double tmp = d_dvector(ispecies, i);
d_dvector(ispecies+nspecies, i) = tmp;
y[ispecies] = tmp;
}
// Solver the ODE system.
if (odeIntegrationFlag == ODE_LAMMPS_RK4)
{
k_rk4(t_stop, y, rwork, userData);
}
else if (odeIntegrationFlag == ODE_LAMMPS_RKF45)
{
k_rkf45(nspecies, t_stop, y, rwork, userData, counter_i);
if (diagnosticFrequency == 1)
{
d_diagnosticCounterPerODEnSteps(i) = counter_i.nSteps;
d_diagnosticCounterPerODEnFuncs(i) = counter_i.nFuncs;
}
}
// Store the solution back in dvector.
for (int ispecies = 0; ispecies < nspecies; ispecies++)
{
if (y[ispecies] < -1.0e-10)
{
//error->one(FLERR,"Computed concentration in RK solver is < -1.0e-10");
k_error_flag.template view<DeviceType>()() = 2;
// This should be an atomic update.
}
else if (y[ispecies] < MY_EPSILON)
y[ispecies] = 0.0;
d_dvector(ispecies,i) = y[ispecies];
}
//delete [] y;
//delete [] userData.kFor;
//delete [] userData.rxnRateLaw;
// Update the iteration statistics counter. Is this unique for each iteration?
counter += counter_i;
} // if
} // parallel_for lambda-body
, TotalCounters // reduction value for all iterations.
);
#else
if (setRatesToZero)
Kokkos::parallel_reduce( Kokkos::RangePolicy<DeviceType, Tag_FixRxKokkos_solveSystems<true > >(0,nlocal), *this, TotalCounters);
else
Kokkos::parallel_reduce( Kokkos::RangePolicy<DeviceType, Tag_FixRxKokkos_solveSystems<false> >(0,nlocal), *this, TotalCounters);
#endif
TimerType timer_ODE = getTimeStamp();
// Check the error flag for any failures.
k_error_flag.template modify<DeviceType>();
k_error_flag.template sync<LMPHostType>();
if (k_error_flag.h_view() == 2)
error->one(FLERR,"Computed concentration in RK solver is < -1.0e-10");
// Signal that dvector has been modified on this execution space.
atomKK->modified( execution_space, DVECTOR_MASK );
// Communicate the updated species data to all nodes
atomKK->sync ( Host, DVECTOR_MASK );
comm->forward_comm_fix(this);
atomKK->modified ( Host, DVECTOR_MASK );
TimerType timer_stop = getTimeStamp();
double time_ODE = getElapsedTime(timer_localTemperature, timer_ODE);
//printf("me= %d kokkos total= %g temp= %g ode= %g comm= %g nlocal= %d nfc= %d %d\n", comm->me,
// getElapsedTime(timer_start, timer_stop),
// getElapsedTime(timer_start, timer_localTemperature),
// getElapsedTime(timer_localTemperature, timer_ODE),
// getElapsedTime(timer_ODE, timer_stop), nlocal, TotalCounters.nFuncs, TotalCounters.nSteps);
// Warn the user if a failure was detected in the ODE solver.
if (TotalCounters.nFails > 0){
char sbuf[128];
sprintf(sbuf,"in FixRX::pre_force, ODE solver failed for %d atoms.", TotalCounters.nFails);
error->warning(FLERR, sbuf);
}
// Compute and report ODE diagnostics, if requested.
if (odeIntegrationFlag == ODE_LAMMPS_RKF45 && diagnosticFrequency != 0)
{
// Update the counters.
diagnosticCounter[StepSum] += TotalCounters.nSteps;
diagnosticCounter[FuncSum] += TotalCounters.nFuncs;
diagnosticCounter[TimeSum] += time_ODE;
diagnosticCounter[AtomSum] += nlocal;
diagnosticCounter[numDiagnosticCounters-1] ++;
if ( (diagnosticFrequency > 0 &&
((update->ntimestep - update->firststep) % diagnosticFrequency) == 0) ||
(diagnosticFrequency < 0 && update->ntimestep == update->laststep) )
this->odeDiagnostics();
}
copymode = 0;
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
void FixRxKokkos<DeviceType>::odeDiagnostics(void)
{
TimerType timer_start = getTimeStamp();
// Compute:
// 1) Average # of ODE integrator steps and RHS evaluations per atom globally.
// 2) RMS # of ...
// 3) Average # of ODE steps and RHS evaluations per MPI task.
// 4) RMS # of ODE steps and RHS evaluations per MPI task.
// 5) MAX # of ODE steps and RHS evaluations per MPI task.
//
// ... 1,2 are for ODE control diagnostics.
// ... 3-5 are for load balancing diagnostics.
//
// To do this, we'll need to
// a) Allreduce (sum) the sum of nSteps / nFuncs. Dividing by atom->natoms
// gives the avg # of steps/funcs per atom globally.
// b) Reduce (sum) to root the sum of squares of the differences.
// i) Sum_i (steps_i - avg_steps_global)^2
// ii) Sum_i (funcs_i - avg_funcs_global)^2
// iii) (avg_steps_local - avg_steps_global)^2
// iv) (avg_funcs_local - avg_funcs_global)^2
const int numCounters = numDiagnosticCounters-1;
// # of time-steps for averaging.
const int nTimes = this->diagnosticCounter[numDiagnosticCounters-1];
// # of ODE's per time-step (on average).
//const int nODEs = this->diagnosticCounter[AtomSum] / nTimes;
// Sum up the sums from each task.
double sums[numCounters];
double my_vals[numCounters];
double max_per_proc[numCounters];
double min_per_proc[numCounters];
// Compute counters per dpd time-step.
for (int i = 0; i < numCounters; ++i){
my_vals[i] = this->diagnosticCounter[i] / nTimes;
//printf("my sum[%d] = %f %d\n", i, my_vals[i], comm->me);
}
MPI_Allreduce (my_vals, sums, numCounters, MPI_DOUBLE, MPI_SUM, world);
MPI_Reduce (my_vals, max_per_proc, numCounters, MPI_DOUBLE, MPI_MAX, 0, world);
MPI_Reduce (my_vals, min_per_proc, numCounters, MPI_DOUBLE, MPI_MIN, 0, world);
const double nODEs = sums[numCounters-1];
double avg_per_atom[numCounters], avg_per_proc[numCounters];
// Averages per-ODE and per-proc per time-step.
for (int i = 0; i < numCounters; ++i){
avg_per_atom[i] = sums[i] / nODEs;
avg_per_proc[i] = sums[i] / comm->nprocs;
}
// Sum up the differences from each task.
double sum_sq[2*numCounters];
double my_sum_sq[2*numCounters];
for (int i = 0; i < numCounters; ++i){
double diff_i = my_vals[i] - avg_per_proc[i];
my_sum_sq[i] = diff_i * diff_i;
}
double max_per_ODE[numCounters], min_per_ODE[numCounters];
// Process the per-ODE RMS of the # of steps/funcs
if (diagnosticFrequency == 1)
{
h_diagnosticCounterPerODEnSteps = k_diagnosticCounterPerODEnSteps.h_view;
h_diagnosticCounterPerODEnFuncs = k_diagnosticCounterPerODEnFuncs.h_view;
Kokkos::deep_copy( h_diagnosticCounterPerODEnSteps, d_diagnosticCounterPerODEnSteps );
Kokkos::deep_copy( h_diagnosticCounterPerODEnFuncs, d_diagnosticCounterPerODEnFuncs );
double my_max[numCounters], my_min[numCounters];
//const int nlocal = atom->nlocal;
nlocal = atom->nlocal;
HAT::t_int_1d h_mask = atomKK->k_mask.h_view;
for (int i = 0; i < numCounters; ++i)
{
my_sum_sq[i+numCounters] = 0;
my_max[i] = 0;
my_min[i] = DBL_MAX;
}
for (int j = 0; j < nlocal; ++j)
if (h_mask(j) & groupbit)
{
int nSteps = h_diagnosticCounterPerODEnSteps(j);
double diff_nSteps = double( nSteps ) - avg_per_atom[StepSum];
my_sum_sq[StepSum+numCounters] += diff_nSteps*diff_nSteps;
my_max[StepSum] = std::max( my_max[StepSum], (double)nSteps );
my_min[StepSum] = std::min( my_min[StepSum], (double)nSteps );
int nFuncs = h_diagnosticCounterPerODEnFuncs(j);
double diff_nFuncs = double( nFuncs ) - avg_per_atom[FuncSum];
my_sum_sq[FuncSum+numCounters] += diff_nFuncs*diff_nFuncs;
my_max[FuncSum] = std::max( my_max[FuncSum], (double)nFuncs );
my_min[FuncSum] = std::min( my_min[FuncSum], (double)nFuncs );
}
memory->destroy_kokkos( k_diagnosticCounterPerODEnSteps, diagnosticCounterPerODEnSteps );
memory->destroy_kokkos( k_diagnosticCounterPerODEnFuncs, diagnosticCounterPerODEnFuncs );
MPI_Reduce (my_sum_sq, sum_sq, 2*numCounters, MPI_DOUBLE, MPI_SUM, 0, world);
MPI_Reduce (my_max, max_per_ODE, numCounters, MPI_DOUBLE, MPI_MAX, 0, world);
MPI_Reduce (my_min, min_per_ODE, numCounters, MPI_DOUBLE, MPI_MIN, 0, world);
}
else
MPI_Reduce (my_sum_sq, sum_sq, numCounters, MPI_DOUBLE, MPI_SUM, 0, world);
TimerType timer_stop = getTimeStamp();
double time_local = getElapsedTime( timer_start, timer_stop );
if (comm->me == 0){
char smesg[128];
#define print_mesg(smesg) {\
if (screen) fprintf(screen,"%s\n", smesg); \
if (logfile) fprintf(logfile,"%s\n", smesg); }
sprintf(smesg, "FixRX::ODE Diagnostics: # of iters |# of rhs evals| run-time (sec) | # atoms");
print_mesg(smesg);
sprintf(smesg, " AVG per ODE : %-12.5g | %-12.5g | %-12.5g", avg_per_atom[0], avg_per_atom[1], avg_per_atom[2]);
print_mesg(smesg);
// only valid for single time-step!
if (diagnosticFrequency == 1){
double rms_per_ODE[numCounters];
for (int i = 0; i < numCounters; ++i)
rms_per_ODE[i] = sqrt( sum_sq[i+numCounters] / nODEs );
sprintf(smesg, " RMS per ODE : %-12.5g | %-12.5g ", rms_per_ODE[0], rms_per_ODE[1]);
print_mesg(smesg);
sprintf(smesg, " MAX per ODE : %-12.5g | %-12.5g ", max_per_ODE[0], max_per_ODE[1]);
print_mesg(smesg);
sprintf(smesg, " MIN per ODE : %-12.5g | %-12.5g ", min_per_ODE[0], min_per_ODE[1]);
print_mesg(smesg);
}
sprintf(smesg, " AVG per Proc : %-12.5g | %-12.5g | %-12.5g | %-12.5g", avg_per_proc[StepSum], avg_per_proc[FuncSum], avg_per_proc[TimeSum], avg_per_proc[AtomSum]);
print_mesg(smesg);
if (comm->nprocs > 1){
double rms_per_proc[numCounters];
for (int i = 0; i < numCounters; ++i)
rms_per_proc[i] = sqrt( sum_sq[i] / comm->nprocs );
sprintf(smesg, " RMS per Proc : %-12.5g | %-12.5g | %-12.5g | %-12.5g", rms_per_proc[0], rms_per_proc[1], rms_per_proc[2], rms_per_proc[AtomSum]);
print_mesg(smesg);
sprintf(smesg, " MAX per Proc : %-12.5g | %-12.5g | %-12.5g | %-12.5g", max_per_proc[0], max_per_proc[1], max_per_proc[2], max_per_proc[AtomSum]);
print_mesg(smesg);
sprintf(smesg, " MIN per Proc : %-12.5g | %-12.5g | %-12.5g | %-12.5g", min_per_proc[0], min_per_proc[1], min_per_proc[2], min_per_proc[AtomSum]);
print_mesg(smesg);
}
sprintf(smesg, " AVG'd over %d time-steps", nTimes);
print_mesg(smesg);
sprintf(smesg, " AVG'ing took %g sec", time_local);
print_mesg(smesg);
#undef print_mesg
}
// Reset the counters.
for (int i = 0; i < numDiagnosticCounters; ++i)
diagnosticCounter[i] = 0;
return;
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
KOKKOS_INLINE_FUNCTION
void FixRxKokkos<DeviceType>::operator()(Tag_FixRxKokkos_zeroTemperatureViews, const int& i) const
{
d_sumWeights(i) = 0.0;
d_dpdThetaLocal(i) = 0.0;
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
template <int WT_FLAG, bool NEWTON_PAIR, int NEIGHFLAG>
KOKKOS_INLINE_FUNCTION
void FixRxKokkos<DeviceType>::operator()(Tag_FixRxKokkos_firstPairOperator<WT_FLAG,NEWTON_PAIR,NEIGHFLAG>, const int& ii) const
{
// Create an atomic view of sumWeights and dpdThetaLocal. Only needed
// for Half/thread scenarios.
typedef Kokkos::View< E_FLOAT*, typename DAT::t_efloat_1d::array_layout, DeviceType, Kokkos::MemoryTraits< AtomicF< NEIGHFLAG >::value> > AtomicViewType;
AtomicViewType a_dpdThetaLocal = d_dpdThetaLocal;
AtomicViewType a_sumWeights = d_sumWeights;
// Local scalar accumulators.
double i_dpdThetaLocal = 0.0;
double i_sumWeights = 0.0;
const int i = d_ilist(ii);
const double xtmp = d_x(i,0);
const double ytmp = d_x(i,1);
const double ztmp = d_x(i,2);
const int itype = d_type(i);
const int jnum = d_numneigh(i);
for (int jj = 0; jj < jnum; jj++)
{
const int j = (d_neighbors(i,jj) & NEIGHMASK);
const int jtype = d_type(j);
const double delx = xtmp - d_x(j,0);
const double dely = ytmp - d_x(j,1);
const double delz = ztmp - d_x(j,2);
const double rsq = delx*delx + dely*dely + delz*delz;
const double cutsq_ij = d_cutsq(itype,jtype);
if (rsq < cutsq_ij)
{
const double rcut = sqrt( cutsq_ij );
double rij = sqrt(rsq);
double ratio = rij/rcut;
double wij = 0.0;
// Lucy's Weight Function
if (WT_FLAG == LUCY)
{
wij = (1.0+3.0*ratio) * (1.0-ratio)*(1.0-ratio)*(1.0-ratio);
i_dpdThetaLocal += wij / d_dpdTheta(j);
if ((NEIGHFLAG==HALF || NEIGHFLAG==HALFTHREAD) && (NEWTON_PAIR || j < nlocal))
a_dpdThetaLocal(j) += wij / d_dpdTheta(i);
}
i_sumWeights += wij;
if ((NEIGHFLAG==HALF || NEIGHFLAG==HALFTHREAD) && (NEWTON_PAIR || j < nlocal))
a_sumWeights(j) += wij;
}
}
// Update, don't assign, the array value (because another iteration may have hit it).
a_dpdThetaLocal(i) += i_dpdThetaLocal;
a_sumWeights(i) += i_sumWeights;
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
template <int WT_FLAG, int LOCAL_TEMP_FLAG>
KOKKOS_INLINE_FUNCTION
void FixRxKokkos<DeviceType>::operator()(Tag_FixRxKokkos_2ndPairOperator<WT_FLAG,LOCAL_TEMP_FLAG>, const int& i) const
{
double wij = 0.0;
// Lucy Weight Function
if (WT_FLAG == LUCY)
{
wij = 1.0;
d_dpdThetaLocal(i) += wij / d_dpdTheta(i);
}
d_sumWeights(i) += wij;
// Normalized local temperature
d_dpdThetaLocal(i) = d_dpdThetaLocal(i) / d_sumWeights(i);
if (LOCAL_TEMP_FLAG == HARMONIC)
d_dpdThetaLocal(i) = 1.0 / d_dpdThetaLocal(i);
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
template <int WT_FLAG, int LOCAL_TEMP_FLAG, bool NEWTON_PAIR, int NEIGHFLAG>
void FixRxKokkos<DeviceType>::computeLocalTemperature()
{
//typename ArrayTypes<DeviceType>::t_x_array_randomread d_x = atomKK->k_x.view<DeviceType>();
//typename ArrayTypes<DeviceType>::t_int_1d_randomread d_type = atomKK->k_type.view<DeviceType>();
//typename ArrayTypes<DeviceType>::t_efloat_1d d_dpdTheta = atomKK->k_dpdTheta.view<DeviceType>();
d_x = atomKK->k_x.view<DeviceType>();
d_type = atomKK->k_type.view<DeviceType>();
d_dpdTheta = atomKK->k_dpdTheta.view<DeviceType>();
atomKK->sync(execution_space, X_MASK | TYPE_MASK | DPDTHETA_MASK );
//const int nlocal = atom->nlocal;
nlocal = atom->nlocal;
const int nghost = atom->nghost;
//printf("Inside FixRxKokkos::computeLocalTemperature: %d %d %d %d %d %d %d\n", WT_FLAG, LOCAL_TEMP_FLAG, NEWTON_PAIR, (int)lmp->kokkos->neighflag, NEIGHFLAG, nlocal, nghost);
// Pull from pairDPDE. The pairDPDEKK objects are protected so recreate here for now.
//pairDPDEKK->k_cutsq.template sync<DeviceType>();
//typename ArrayTypes<DeviceType>::t_ffloat_2d d_cutsq = pairDPDEKK->k_cutsq.template view<DeviceType();
//!< Copies pulled from pairDPDE for local use since pairDPDEKK's objects are protected.
//typename ArrayTypes<DeviceType>::tdual_ffloat_2d k_cutsq;
//typename ArrayTypes<DeviceType>::t_ffloat_2d d_cutsq;
//double **h_cutsq;
{
const int ntypes = atom->ntypes;
//memory->create_kokkos (k_cutsq, h_cutsq, ntypes+1, ntypes+1, "pair:cutsq");
if (ntypes+1 > k_cutsq.dimension_0()) {
memory->destroy_kokkos (k_cutsq);
memory->create_kokkos (k_cutsq, ntypes+1, ntypes+1, "FixRxKokkos::k_cutsq");
d_cutsq = k_cutsq.template view<DeviceType>();
}
for (int i = 1; i <= ntypes; ++i)
for (int j = i; j <= ntypes; ++j)
{
k_cutsq.h_view(i,j) = pairDPDE->cutsq[i][j];
k_cutsq.h_view(j,i) = k_cutsq.h_view(i,j);
}
k_cutsq.template modify<LMPHostType>();
k_cutsq.template sync<DeviceType>();
}
// Initialize the local temperature weight array
int sumWeightsCt = nlocal + (NEWTON_PAIR ? nghost : 0);
//memory->create_kokkos (k_sumWeights, sumWeights, sumWeightsCt, "FixRxKokkos::sumWeights");
if (sumWeightsCt > k_sumWeights.template view<DeviceType>().dimension_0()) {
memory->destroy_kokkos(k_sumWeights, sumWeights);
memory->create_kokkos (k_sumWeights, sumWeightsCt, "FixRxKokkos::sumWeights");
d_sumWeights = k_sumWeights.template view<DeviceType>();
h_sumWeights = k_sumWeights.h_view;
}
// Initialize the accumulator to zero ...
//Kokkos::parallel_for (sumWeightsCt,
// LAMMPS_LAMBDA(const int i)
// {
// d_sumWeights(i) = 0.0;
// }
// );
Kokkos::parallel_for (Kokkos::RangePolicy<DeviceType, Tag_FixRxKokkos_zeroTemperatureViews>(0, sumWeightsCt), *this);
// Local list views. (This isn't working!)
NeighListKokkos<DeviceType>* k_list = static_cast<NeighListKokkos<DeviceType>*>(list);
if (not(list->kokkos))
error->one(FLERR,"list is not a Kokkos list\n");
//typename ArrayTypes<DeviceType>::t_neighbors_2d d_neighbors = k_list->d_neighbors;
//typename ArrayTypes<DeviceType>::t_int_1d d_ilist = k_list->d_ilist;
//typename ArrayTypes<DeviceType>::t_int_1d d_numneigh = k_list->d_numneigh;
d_neighbors = k_list->d_neighbors;
d_ilist = k_list->d_ilist;
d_numneigh = k_list->d_numneigh;
const int inum = list->inum;
// loop over neighbors of my atoms
#if 0
Kokkos::parallel_for ( inum,
LAMMPS_LAMBDA(const int ii)
{
// Create an atomic view of sumWeights and dpdThetaLocal. Only needed
// for Half/thread scenarios.
//typedef Kokkos::View< E_FLOAT*, typename DAT::t_efloat_1d::array_layout, DeviceType, Kokkos::MemoryTraits< AtomicF< NEIGHFLAG >::value> > AtomicViewType;
typedef Kokkos::View< E_FLOAT*, typename DAT::t_efloat_1d::array_layout, DeviceType, Kokkos::MemoryTraits< AtomicF< NEIGHFLAG >::value> > AtomicViewType;
AtomicViewType a_dpdThetaLocal = d_dpdThetaLocal;
AtomicViewType a_sumWeights = d_sumWeights;
// Local scalar accumulators.
double i_dpdThetaLocal = 0.0;
double i_sumWeights = 0.0;
const int i = d_ilist(ii);
const double xtmp = d_x(i,0);
const double ytmp = d_x(i,1);
const double ztmp = d_x(i,2);
const int itype = d_type(i);
const int jnum = d_numneigh(i);
for (int jj = 0; jj < jnum; jj++)
{
const int j = (d_neighbors(i,jj) & NEIGHMASK);
const int jtype = d_type(j);
const double delx = xtmp - d_x(j,0);
const double dely = ytmp - d_x(j,1);
const double delz = ztmp - d_x(j,2);
const double rsq = delx*delx + dely*dely + delz*delz;
const double cutsq_ij = d_cutsq(itype,jtype);
if (rsq < cutsq_ij)
{
const double rcut = sqrt( cutsq_ij );
double rij = sqrt(rsq);
double ratio = rij/rcut;
double wij = 0.0;
// Lucy's Weight Function
if (WT_FLAG == LUCY)
{
wij = (1.0+3.0*ratio) * (1.0-ratio)*(1.0-ratio)*(1.0-ratio);
i_dpdThetaLocal += wij / d_dpdTheta(j);
if (NEWTON_PAIR || j < nlocal)
a_dpdThetaLocal(j) += wij / d_dpdTheta(i);
}
i_sumWeights += wij;
if (NEWTON_PAIR || j < nlocal)
a_sumWeights(j) += wij;
}
}
// Update, don't assign, the array value (because another iteration may have hit it).
a_dpdThetaLocal(i) += i_dpdThetaLocal;
a_sumWeights(i) += i_sumWeights;
}
);
#else
Kokkos::parallel_for (Kokkos::RangePolicy<DeviceType, Tag_FixRxKokkos_firstPairOperator<WT_FLAG, NEWTON_PAIR, NEIGHFLAG> >(0, inum), *this);
#endif
// Signal that dpdThetaLocal and sumWeights have been modified.
k_dpdThetaLocal.template modify<DeviceType>();
k_sumWeights. template modify<DeviceType>();
// Communicate the sum dpdTheta and the weights on the host.
if (NEWTON_PAIR) comm->reverse_comm_fix(this);
// Update the device view in case they got changed.
k_dpdThetaLocal.template sync<DeviceType>();
k_sumWeights. template sync<DeviceType>();
// self-interaction for local temperature
#if 0
Kokkos::parallel_for ( nlocal,
LAMMPS_LAMBDA(const int i)
{
double wij = 0.0;
// Lucy Weight Function
if (WT_FLAG == LUCY)
{
wij = 1.0;
d_dpdThetaLocal(i) += wij / d_dpdTheta(i);
}
d_sumWeights(i) += wij;
// Normalized local temperature
d_dpdThetaLocal(i) = d_dpdThetaLocal(i) / d_sumWeights(i);
if (LOCAL_TEMP_FLAG == HARMONIC)
d_dpdThetaLocal(i) = 1.0 / d_dpdThetaLocal(i);
}
);
#else
Kokkos::parallel_for (Kokkos::RangePolicy<DeviceType, Tag_FixRxKokkos_2ndPairOperator<WT_FLAG, LOCAL_TEMP_FLAG> >(0, nlocal), *this);
#endif
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
int FixRxKokkos<DeviceType>::pack_forward_comm(int n, int *list, double *buf, int pbc_flag, int *pbc)
{
//printf("inside FixRxKokkos::pack_forward_comm %d\n", comm->me);
HAT::t_float_2d h_dvector = atomKK->k_dvector.h_view;
int m = 0;
for (int ii = 0; ii < n; ii++) {
const int jj = list[ii];
for(int ispecies = 0; ispecies < nspecies; ispecies++){
buf[m++] = h_dvector(ispecies,jj);
buf[m++] = h_dvector(ispecies+nspecies,jj);
}
}
//printf("done with FixRxKokkos::pack_forward_comm %d\n", comm->me);
return m;
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
void FixRxKokkos<DeviceType>::unpack_forward_comm(int n, int first, double *buf)
{
//printf("inside FixRxKokkos::unpack_forward_comm %d\n", comm->me);
HAT::t_float_2d h_dvector = atomKK->k_dvector.h_view;
const int last = first + n ;
int m = 0;
for (int ii = first; ii < last; ii++){
for (int ispecies = 0; ispecies < nspecies; ispecies++){
h_dvector(ispecies,ii) = buf[m++];
h_dvector(ispecies+nspecies,ii) = buf[m++];
}
}
//printf("done with FixRxKokkos::unpack_forward_comm %d\n", comm->me);
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
int FixRxKokkos<DeviceType>::pack_reverse_comm(int n, int first, double *buf)
{
//printf("inside FixRxKokkos::pack_reverse_comm %d %d %d\n", comm->me, first, n);
// Sync the host view.
k_dpdThetaLocal.template sync<LMPHostType>();
k_sumWeights. template sync<LMPHostType>();
const int last = first + n;
int m = 0;
for (int i = first; i < last; ++i)
{
buf[m++] = h_dpdThetaLocal(i);
buf[m++] = h_sumWeights(i);
}
//printf("done with FixRxKokkos::pack_reverse_comm %d\n", comm->me);
return m;
}
/* ---------------------------------------------------------------------- */
template <typename DeviceType>
void FixRxKokkos<DeviceType>::unpack_reverse_comm(int n, int *list, double *buf)
{
// printf("inside FixRxKokkos::unpack_reverse_comm %d\n", comm->me);
int m = 0;
for (int i = 0; i < n; i++) {
const int j = list[i];
h_dpdThetaLocal(j) += buf[m++];
h_sumWeights(j) += buf[m++];
}
// Signal that the host view has been modified.
k_dpdThetaLocal.template modify<LMPHostType>();
k_sumWeights. template modify<LMPHostType>();
// printf("done with FixRxKokkos::unpack_reverse_comm %d\n", comm->me);
}
namespace LAMMPS_NS {
template class FixRxKokkos<LMPDeviceType>;
#ifdef KOKKOS_HAVE_CUDA
template class FixRxKokkos<LMPHostType>;
#endif
}
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