inv_multi_cg_quda.cpp

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#include <stdio.h>
#include <stdlib.h>
#include <math.h>

#include <quda_internal.h>
#include <color_spinor_field.h>
#include <blas_quda.h>
#include <dslash_quda.h>
#include <invert_quda.h>
#include <util_quda.h>

#include <worker.h>

namespace quda {

  class ShiftUpdate : public Worker {

    ColorSpinorField *r;
    std::vector<ColorSpinorField*> p;
    std::vector<ColorSpinorField*> x;

    double *alpha;
    double *beta;
    double *zeta;
    double *zeta_old;

    const int j_low;
    int n_shift;

    int n_update; 

  public:
    ShiftUpdate(ColorSpinorField *r, std::vector<ColorSpinorField*> p, std::vector<ColorSpinorField*> x,
    double *alpha, double *beta, double *zeta, double *zeta_old, int j_low, int n_shift) :
      r(r), p(p), x(x), alpha(alpha), beta(beta), zeta(zeta), zeta_old(zeta_old), j_low(j_low), 
      n_shift(n_shift), n_update( (r->Nspin()==4) ? 4 : 2 ) {
      
    }
    virtual ~ShiftUpdate() { }
    
    void updateNshift(int new_n_shift) { n_shift = new_n_shift; }
    void updateNupdate(int new_n_update) { n_update = new_n_update; }
    
    // note that we can't set the stream parameter here so it is
    // ignored.  This is more of a future design direction to consider
    void apply(const cudaStream_t &stream) {      
      static int count = 0;

#if 0
      // on the first call do the first half of the update
      for (int j= (count*n_shift)/n_update+1; j<=((count+1)*n_shift)/n_update && j<n_shift; j++) {
  beta[j] = beta[j_low] * zeta[j] * alpha[j] /  ( zeta_old[j] * alpha[j_low] );
  // update p[i] and x[i]
  blas::axpyBzpcx(alpha[j], *(p[j]), *(x[j]), zeta[j], *r, beta[j]);
      }
#else
      int zero = (count*n_shift)/n_update+1;
      std::vector<ColorSpinorField*> P, X;
      for (int j= (count*n_shift)/n_update+1; j<=((count+1)*n_shift)/n_update && j<n_shift; j++) {
  beta[j] = beta[j_low] * zeta[j] * alpha[j] /  ( zeta_old[j] * alpha[j_low] );
  P.push_back(p[j]);
  X.push_back(x[j]);
      }
      if (P.size()) blas::axpyBzpcx(&alpha[zero], P, X, &zeta[zero], *r, &beta[zero]);
#endif
      if (++count == n_update) count = 0;
    }
    
  };

  // this is the Worker pointer that the dslash uses to launch the shifted updates
  namespace dslash {
    extern Worker* aux_worker;
  }  

  MultiShiftCG::MultiShiftCG(DiracMatrix &mat, DiracMatrix &matSloppy, SolverParam &param,
           TimeProfile &profile) 
    : MultiShiftSolver(param, profile), mat(mat), matSloppy(matSloppy) {

  }

  MultiShiftCG::~MultiShiftCG() {

  }

  void updateAlphaZeta(double *alpha, double *zeta, double *zeta_old, 
           const double *r2, const double *beta, const double pAp, 
           const double *offset, const int nShift, const int j_low) {
    double alpha_old[QUDA_MAX_MULTI_SHIFT];
    for (int j=0; j<nShift; j++) alpha_old[j] = alpha[j];

    alpha[0] = r2[0] / pAp;        
    zeta[0] = 1.0;
    for (int j=1; j<nShift; j++) {
      double c0 = zeta[j] * zeta_old[j] * alpha_old[j_low];
      double c1 = alpha[j_low] * beta[j_low] * (zeta_old[j]-zeta[j]);
      double c2 = zeta_old[j] * alpha_old[j_low] * (1.0+(offset[j]-offset[0])*alpha[j_low]);
      
      zeta_old[j] = zeta[j];
      if (c1+c2 != 0.0){
        zeta[j] = c0 / (c1 + c2);
      }
      else {
        zeta[j] = 0.0;
      }
      if (zeta[j] != 0.0){
        alpha[j] = alpha[j_low] * zeta[j] / zeta_old[j];
      }
      else {
        alpha[j] = 0.0;    
      }
    }  
  }

  void MultiShiftCG::operator()(std::vector<ColorSpinorField*>x, ColorSpinorField &b)
  {
    if (checkLocation(*(x[0]), b) != QUDA_CUDA_FIELD_LOCATION)
      errorQuda("Not supported");

    profile.TPSTART(QUDA_PROFILE_INIT);

    int num_offset = param.num_offset;
    double *offset = param.offset;
 
    if (num_offset == 0) return;

    const double b2 = blas::norm2(b);
    // Check to see that we're not trying to invert on a zero-field source
    if(b2 == 0){
      profile.TPSTOP(QUDA_PROFILE_INIT);
      printfQuda("Warning: inverting on zero-field source\n");
      for(int i=0; i<num_offset; ++i){
        *(x[i]) = b;
  param.true_res_offset[i] = 0.0;
  param.true_res_hq_offset[i] = 0.0;
      }
      return;
    }
    
    // this is the limit of precision possible
    const double prec_tol = pow(10.,(-2*(int)b.Precision()+1));

    double *zeta = new double[num_offset];
    double *zeta_old = new double[num_offset];
    double *alpha = new double[num_offset];
    double *beta = new double[num_offset];
  
    int j_low = 0;   
    int num_offset_now = num_offset;
    for (int i=0; i<num_offset; i++) {
      zeta[i] = zeta_old[i] = 1.0;
      beta[i] = 0.0;
      alpha[i] = 1.0;
    }
  
    // flag whether we will be using reliable updates or not
    bool reliable = false;
    for (int j=0; j<num_offset; j++) 
      if (param.tol_offset[j] < param.delta) reliable = true;


    cudaColorSpinorField *r = new cudaColorSpinorField(b);
    std::vector<ColorSpinorField*> x_sloppy;
    x_sloppy.resize(num_offset);
    std::vector<ColorSpinorField*> y;
  
    ColorSpinorParam csParam(b);
    csParam.create = QUDA_ZERO_FIELD_CREATE;

    if (reliable) {
      y.resize(num_offset);
      for (int i=0; i<num_offset; i++) y[i] = new cudaColorSpinorField(*r, csParam);
    }

    csParam.setPrecision(param.precision_sloppy);
  
    cudaColorSpinorField *r_sloppy;
    if (param.precision_sloppy == x[0]->Precision()) {
      r_sloppy = r;
    } else {
      csParam.create = QUDA_COPY_FIELD_CREATE;
      r_sloppy = new cudaColorSpinorField(*r, csParam);
    }
  
    if (param.precision_sloppy == x[0]->Precision() ||
  !param.use_sloppy_partial_accumulator) {
      for (int i=0; i<num_offset; i++){
  x_sloppy[i] = x[i];
  blas::zero(*x_sloppy[i]);
      }
    } else {
      csParam.create = QUDA_ZERO_FIELD_CREATE;
      for (int i=0; i<num_offset; i++)
  x_sloppy[i] = new cudaColorSpinorField(*x[i], csParam);
    }
  
    std::vector<ColorSpinorField*> p;
    p.resize(num_offset);
    for (int i=0; i<num_offset; i++) p[i] = new cudaColorSpinorField(*r_sloppy);    
  
    csParam.create = QUDA_ZERO_FIELD_CREATE;
    cudaColorSpinorField* Ap = new cudaColorSpinorField(*r_sloppy, csParam);
  
    cudaColorSpinorField tmp1(*Ap, csParam);

    // tmp2 only needed for multi-gpu Wilson-like kernels
    cudaColorSpinorField *tmp2_p = !mat.isStaggered() ?
      new cudaColorSpinorField(*Ap, csParam) : &tmp1;
    cudaColorSpinorField &tmp2 = *tmp2_p;

    // additional high-precision temporary if Wilson and mixed-precision
    csParam.setPrecision(param.precision);
    cudaColorSpinorField *tmp3_p =
      (param.precision != param.precision_sloppy && !mat.isStaggered()) ?
      new cudaColorSpinorField(*r, csParam) : &tmp1;
    cudaColorSpinorField &tmp3 = *tmp3_p;

    profile.TPSTOP(QUDA_PROFILE_INIT);
    profile.TPSTART(QUDA_PROFILE_PREAMBLE);

    // stopping condition of each shift
    double stop[QUDA_MAX_MULTI_SHIFT];
    double r2[QUDA_MAX_MULTI_SHIFT];
    int iter[QUDA_MAX_MULTI_SHIFT+1];     // record how many iterations for each shift
    for (int i=0; i<num_offset; i++) {
      r2[i] = b2;
      stop[i] = Solver::stopping(param.tol_offset[i], b2, param.residual_type);
      iter[i] = 0;
    }
    // this initial condition ensures that the heaviest shift can be removed
    iter[num_offset] = 1;

    double r2_old;
    double pAp;

    double rNorm[QUDA_MAX_MULTI_SHIFT];
    double r0Norm[QUDA_MAX_MULTI_SHIFT];
    double maxrx[QUDA_MAX_MULTI_SHIFT];
    double maxrr[QUDA_MAX_MULTI_SHIFT];
    for (int i=0; i<num_offset; i++) {
      rNorm[i] = sqrt(r2[i]);
      r0Norm[i] = rNorm[i];
      maxrx[i] = rNorm[i];
      maxrr[i] = rNorm[i];
    }
    double delta = param.delta;

    // this parameter determines how many consective reliable update
    // reisudal increases we tolerate before terminating the solver,
    // i.e., how long do we want to keep trying to converge
    const int maxResIncrease =  param.max_res_increase; // check if we reached the limit of our tolerance
    const int maxResIncreaseTotal = param.max_res_increase_total;
    
    int resIncrease = 0;
    int resIncreaseTotal[QUDA_MAX_MULTI_SHIFT];
    for (int i=0; i<num_offset; i++) {
      resIncreaseTotal[i]=0;
    }

    int k = 0;
    int rUpdate = 0;
    blas::flops = 0;

    bool aux_update = false;

    // now create the worker class for updating the shifted solutions and gradient vectors
    ShiftUpdate shift_update(r_sloppy, p, x_sloppy, alpha, beta, zeta, zeta_old, j_low, num_offset_now);
    
    profile.TPSTOP(QUDA_PROFILE_PREAMBLE);
    profile.TPSTART(QUDA_PROFILE_COMPUTE);

    if (getVerbosity() >= QUDA_VERBOSE) 
      printfQuda("MultiShift CG: %d iterations, <r,r> = %e, |r|/|b| = %e\n", k, r2[0], sqrt(r2[0]/b2));
    
    while ( !convergence(r2, stop, num_offset_now) &&  k < param.maxiter) {

      if (aux_update) dslash::aux_worker = &shift_update;
      matSloppy(*Ap, *p[0], tmp1, tmp2);
      dslash::aux_worker = NULL;
      aux_update = false;

      // update number of shifts now instead of end of previous
      // iteration so that all shifts are updated during the dslash
      shift_update.updateNshift(num_offset_now);

      // at some point we should curry these into the Dirac operator
      if (r->Nspin()==4) pAp = blas::axpyReDot(offset[0], *p[0], *Ap);
      else pAp = blas::reDotProduct(*p[0], *Ap);

      // compute zeta and alpha
      updateAlphaZeta(alpha, zeta, zeta_old, r2, beta, pAp, offset, num_offset_now, j_low);
  
      r2_old = r2[0];
      Complex cg_norm = blas::axpyCGNorm(-alpha[j_low], *Ap, *r_sloppy);
      r2[0] = real(cg_norm);
      double zn = imag(cg_norm);

      // reliable update conditions
      rNorm[0] = sqrt(r2[0]);
      for (int j=1; j<num_offset_now; j++) rNorm[j] = rNorm[0] * zeta[j];

      int updateX=0, updateR=0;
      //fixme: with the current implementation of the reliable update it is sufficient to trigger it only for shift 0
      //fixme: The loop below is unnecessary but I don't want to delete it as we still might find a better reliable update
      int reliable_shift = -1; // this is the shift that sets the reliable_shift
      for (int j=0; j>=0; j--) {
        if (rNorm[j] > maxrx[j]) maxrx[j] = rNorm[j];
        if (rNorm[j] > maxrr[j]) maxrr[j] = rNorm[j];
        updateX = (rNorm[j] < delta*r0Norm[j] && r0Norm[j] <= maxrx[j]) ? 1 : updateX;
        updateR = ((rNorm[j] < delta*maxrr[j] && r0Norm[j] <= maxrr[j]) || updateX) ? 1 : updateR;
        if ((updateX || updateR) && reliable_shift == -1) reliable_shift = j;
      }

      if ( !(updateR || updateX) || !reliable) {
  //beta[0] = r2[0] / r2_old; 
  beta[0] = zn / r2_old;
  // update p[0] and x[0]
  blas::axpyZpbx(alpha[0], *p[0], *x_sloppy[0], *r_sloppy, beta[0]);  

  // this should trigger the shift update in the subsequent sloppy dslash
  aux_update = true;
  /*
    for (int j=1; j<num_offset_now; j++) {
    beta[j] = beta[j_low] * zeta[j] * alpha[j] / (zeta_old[j] * alpha[j_low]);
    // update p[i] and x[i]
    blas::axpyBzpcx(alpha[j], *p[j], *x_sloppy[j], zeta[j], *r_sloppy, beta[j]);
    }
  */
      } else {
  for (int j=0; j<num_offset_now; j++) {
    blas::axpy(alpha[j], *p[j], *x_sloppy[j]);
    blas::xpy(*x_sloppy[j], *y[j]);
  }

  mat(*r, *y[0], *x[0], tmp3); // here we can use x as tmp
  if (r->Nspin()==4) blas::axpy(offset[0], *y[0], *r);

  r2[0] = blas::xmyNorm(b, *r);
  for (int j=1; j<num_offset_now; j++) r2[j] = zeta[j] * zeta[j] * r2[0];
  for (int j=0; j<num_offset_now; j++) blas::zero(*x_sloppy[j]);

  blas::copy(*r_sloppy, *r);            

  // break-out check if we have reached the limit of the precision
  if (sqrt(r2[reliable_shift]) > r0Norm[reliable_shift]) { // reuse r0Norm for this
    resIncrease++;
    resIncreaseTotal[reliable_shift]++;
    warningQuda("MultiShiftCG: Shift %d, updated residual %e is greater than previous residual %e (total #inc %i)", 
          reliable_shift, sqrt(r2[reliable_shift]), r0Norm[reliable_shift], resIncreaseTotal[reliable_shift]);

    if (resIncrease > maxResIncrease or resIncreaseTotal[reliable_shift] > maxResIncreaseTotal) {
      warningQuda("MultiShiftCG: solver exiting due to too many true residual norm increases");
      break;
    }
  } else {
    resIncrease = 0;
  }

  // explicitly restore the orthogonality of the gradient vector
  for (int j=0; j<num_offset_now; j++) {
    Complex rp = blas::cDotProduct(*r_sloppy, *p[j]) / (r2[0]);
    blas::caxpy(-rp, *r_sloppy, *p[j]);
  }

  // update beta and p
  beta[0] = r2[0] / r2_old; 
  blas::xpay(*r_sloppy, beta[0], *p[0]);
  for (int j=1; j<num_offset_now; j++) {
    beta[j] = beta[j_low] * zeta[j] * alpha[j] / (zeta_old[j] * alpha[j_low]);
    blas::axpby(zeta[j], *r_sloppy, beta[j], *p[j]);
  }    

  // update reliable update parameters for the system that triggered the update
  int m = reliable_shift;
  rNorm[m] = sqrt(r2[0]) * zeta[m];
  maxrr[m] = rNorm[m];
  maxrx[m] = rNorm[m];
  r0Norm[m] = rNorm[m];      
  rUpdate++;
      }

      // now we can check if any of the shifts have converged and remove them
      int converged = 0;
      for (int j=num_offset_now-1; j>=1; j--) {
        if (zeta[j] == 0.0 && r2[j+1] < stop[j+1]) {
          converged++;
          if (getVerbosity() >= QUDA_VERBOSE)
              printfQuda("MultiShift CG: Shift %d converged after %d iterations\n", j, k+1);
        } else {
    r2[j] = zeta[j] * zeta[j] * r2[0];
    // only remove if shift above has converged
    if ((r2[j] < stop[j] || sqrt(r2[j] / b2) < prec_tol) && iter[j+1] ) {
      converged++;
      iter[j] = k+1;
      if (getVerbosity() >= QUDA_VERBOSE)
        printfQuda("MultiShift CG: Shift %d converged after %d iterations\n", j, k+1);
          }
  }
      }
      num_offset_now -= converged;

      // this ensure we do the update on any shifted systems that
      // happen to converge when the un-shifted system converges
      if ( (convergence(r2, stop, num_offset_now) ||  k == param.maxiter) && aux_update == true) {
  if (getVerbosity() >= QUDA_VERBOSE) 
    printfQuda("Convergence of unshifted system so trigger shiftUpdate\n");
  
  // set worker to do all updates at once
  shift_update.updateNupdate(1);
  shift_update.apply(0);

  for (int j=0; j<num_offset_now; j++) iter[j] = k+1;
      }
      
      k++;

      if (getVerbosity() >= QUDA_VERBOSE) 
  printfQuda("MultiShift CG: %d iterations, <r,r> = %e, |r|/|b| = %e\n", k, r2[0], sqrt(r2[0]/b2));
    }
    
    for (int i=0; i<num_offset; i++) {
      if (iter[i] == 0) iter[i] = k;
      blas::copy(*x[i], *x_sloppy[i]);
      if (reliable) blas::xpy(*y[i], *x[i]);
    }

    profile.TPSTOP(QUDA_PROFILE_COMPUTE);
    profile.TPSTART(QUDA_PROFILE_EPILOGUE);

    if (getVerbosity() >= QUDA_VERBOSE)
      printfQuda("MultiShift CG: Reliable updates = %d\n", rUpdate);

    if (k==param.maxiter) warningQuda("Exceeded maximum iterations %d\n", param.maxiter);
    
    param.secs = profile.Last(QUDA_PROFILE_COMPUTE);
    double gflops = (blas::flops + mat.flops() + matSloppy.flops())*1e-9;
    param.gflops = gflops;
    param.iter += k;

    if (param.compute_true_res) {
      // only allocate temporaries if necessary
      csParam.setPrecision(param.precision);
      ColorSpinorField *tmp4_p = reliable ? y[0] : tmp1.Precision() == x[0]->Precision() ? &tmp1 : ColorSpinorField::Create(csParam);
      ColorSpinorField *tmp5_p = mat.isStaggered() ? tmp4_p :
  reliable ? y[1] : (tmp2.Precision() == x[0]->Precision() && &tmp1 != tmp2_p) ? tmp2_p : ColorSpinorField::Create(csParam);

      for(int i=0; i < num_offset; i++) {
  mat(*r, *x[i], *tmp4_p, *tmp5_p);
  if (r->Nspin()==4) {
    blas::axpy(offset[i], *x[i], *r); // Offset it.
  } else if (i!=0) {
    blas::axpy(offset[i]-offset[0], *x[i], *r); // Offset it.
  }
  double true_res = blas::xmyNorm(b, *r);
  param.true_res_offset[i] = sqrt(true_res/b2);
  param.iter_res_offset[i] = sqrt(r2[i]/b2);
  param.true_res_hq_offset[i] = sqrt(blas::HeavyQuarkResidualNorm(*x[i], *r).z);
      }

      if (getVerbosity() >= QUDA_SUMMARIZE){
  printfQuda("MultiShift CG: Converged after %d iterations\n", k);
  for(int i=0; i < num_offset; i++) {
    printfQuda(" shift=%d, %d iterations, relative residual: iterated = %e, true = %e\n",
         i, iter[i], param.iter_res_offset[i], param.true_res_offset[i]);
  }
      }

      if (tmp5_p != tmp4_p && tmp5_p != tmp2_p && (reliable ? tmp5_p != y[1] : 1)) delete tmp5_p;
      if (tmp4_p != &tmp1 && (reliable ? tmp4_p != y[0] : 1)) delete tmp4_p;
    } else {
      if (getVerbosity() >= QUDA_SUMMARIZE) {
  printfQuda("MultiShift CG: Converged after %d iterations\n", k);
  for(int i=0; i < num_offset; i++) {
    param.iter_res_offset[i] = sqrt(r2[i]/b2);
    printfQuda(" shift=%d, %d iterations, relative residual: iterated = %e\n",
         i, iter[i], param.iter_res_offset[i]);
  }
      }
    }

    // reset the flops counters
    blas::flops = 0;
    mat.flops();
    matSloppy.flops();

    profile.TPSTOP(QUDA_PROFILE_EPILOGUE);
    profile.TPSTART(QUDA_PROFILE_FREE);

    if (&tmp3 != &tmp1) delete tmp3_p;
    if (&tmp2 != &tmp1) delete tmp2_p;

    if (r_sloppy->Precision() != r->Precision()) delete r_sloppy;
    for (int i=0; i<num_offset; i++) 
       if (x_sloppy[i]->Precision() != x[i]->Precision()) delete x_sloppy[i];
  
    delete r;
    for (int i=0; i<num_offset; i++) delete p[i];

    if (reliable) for (int i=0; i<num_offset; i++) delete y[i];

    delete Ap;
  
    delete []zeta_old;
    delete []zeta;
    delete []alpha;
    delete []beta;

    profile.TPSTOP(QUDA_PROFILE_FREE);

    return;
  }

} // namespace quda