void DiracStaggered::checkParitySpinor(const cudaColorSpinorField &in, const cudaColorSpinorField &out) const
{
if (in.Precision() != out.Precision()) {
errorQuda("Input and output spinor precisions don't match in dslash_quda");
}
if (in.Stride() != out.Stride()) {
errorQuda("Input %d and output %d spinor strides don't match in dslash_quda", in.Stride(), out.Stride());
}
if (in.SiteSubset() != QUDA_PARITY_SITE_SUBSET || out.SiteSubset() != QUDA_PARITY_SITE_SUBSET) {
errorQuda("ColorSpinorFields are not single parity, in = %d, out = %d",
in.SiteSubset(), out.SiteSubset());
}
}
void DiracStaggered::checkParitySpinor(const cudaColorSpinorField &in, const cudaColorSpinorField &out) const
{
if (in.Precision() != out.Precision()) {
errorQuda("Input and output spinor precisions don't match in dslash_quda");
}
if (in.Stride() != out.Stride()) {
errorQuda("Input %d and output %d spinor strides don't match in dslash_quda", in.Stride(), out.Stride());
}
if (in.SiteSubset() != QUDA_PARITY_SITE_SUBSET || out.SiteSubset() != QUDA_PARITY_SITE_SUBSET) {
errorQuda("ColorSpinorFields are not single parity, in = %d, out = %d",
in.SiteSubset(), out.SiteSubset());
}
if ((out.Volume() != 2*fatGauge->VolumeCB() && out.SiteSubset() == QUDA_FULL_SITE_SUBSET) ||
(out.Volume() != fatGauge->VolumeCB() && out.SiteSubset() == QUDA_PARITY_SITE_SUBSET) ) {
errorQuda("Spinor volume %d doesn't match gauge volume %d", out.Volume(), fatGauge->VolumeCB());
}
}
void Dirac::checkParitySpinor(const cudaColorSpinorField &out, const cudaColorSpinorField &in) const
{
if (in.GammaBasis() != QUDA_UKQCD_GAMMA_BASIS ||
out.GammaBasis() != QUDA_UKQCD_GAMMA_BASIS) {
errorQuda("CUDA Dirac operator requires UKQCD basis, out = %d, in = %d",
out.GammaBasis(), in.GammaBasis());
}
if (in.Precision() != out.Precision()) {
errorQuda("Input precision %d and output spinor precision %d don't match in dslash_quda",
in.Precision(), out.Precision());
}
if (in.Stride() != out.Stride()) {
errorQuda("Input %d and output %d spinor strides don't match in dslash_quda",
in.Stride(), out.Stride());
}
if (in.SiteSubset() != QUDA_PARITY_SITE_SUBSET || out.SiteSubset() != QUDA_PARITY_SITE_SUBSET) {
errorQuda("ColorSpinorFields are not single parity: in = %d, out = %d",
in.SiteSubset(), out.SiteSubset());
}
if (out.Ndim() != 5) {
if ((out.Volume() != gauge.Volume() && out.SiteSubset() == QUDA_FULL_SITE_SUBSET) ||
(out.Volume() != gauge.VolumeCB() && out.SiteSubset() == QUDA_PARITY_SITE_SUBSET) ) {
errorQuda("Spinor volume %d doesn't match gauge volume %d", out.Volume(), gauge.VolumeCB());
}
} else {
// Domain wall fermions, compare 4d volumes not 5d
if ((out.Volume()/out.X(4) != gauge.Volume() && out.SiteSubset() == QUDA_FULL_SITE_SUBSET) ||
(out.Volume()/out.X(4) != gauge.VolumeCB() && out.SiteSubset() == QUDA_PARITY_SITE_SUBSET) ) {
errorQuda("Spinor volume %d doesn't match gauge volume %d", out.Volume(), gauge.VolumeCB());
}
}
}
void CG::operator()(cudaColorSpinorField &x, cudaColorSpinorField &b)
{
int k=0;
int rUpdate = 0;
cudaColorSpinorField r(b);
ColorSpinorParam param(x);
param.create = QUDA_ZERO_FIELD_CREATE;
cudaColorSpinorField y(b, param);
mat(r, x, y);
zeroCuda(y);
double r2 = xmyNormCuda(b, r);
rUpdate ++;
param.precision = invParam.cuda_prec_sloppy;
cudaColorSpinorField Ap(x, param);
cudaColorSpinorField tmp(x, param);
cudaColorSpinorField tmp2(x, param); // only needed for clover and twisted mass
cudaColorSpinorField *x_sloppy, *r_sloppy;
if (invParam.cuda_prec_sloppy == x.Precision()) {
param.create = QUDA_REFERENCE_FIELD_CREATE;
x_sloppy = &x;
r_sloppy = &r;
} else {
param.create = QUDA_COPY_FIELD_CREATE;
x_sloppy = new cudaColorSpinorField(x, param);
r_sloppy = new cudaColorSpinorField(r, param);
}
cudaColorSpinorField &xSloppy = *x_sloppy;
cudaColorSpinorField &rSloppy = *r_sloppy;
cudaColorSpinorField p(rSloppy);
double r2_old;
double src_norm = norm2(b);
double stop = src_norm*invParam.tol*invParam.tol; // stopping condition of solver
double alpha, beta;
double pAp;
double rNorm = sqrt(r2);
double r0Norm = rNorm;
double maxrx = rNorm;
double maxrr = rNorm;
double delta = invParam.reliable_delta;
if (invParam.verbosity >= QUDA_VERBOSE) printfQuda("CG: %d iterations, r2 = %e\n", k, r2);
quda::blas_flops = 0;
stopwatchStart();
while (r2 > stop && k<invParam.maxiter) {
matSloppy(Ap, p, tmp, tmp2); // tmp as tmp
pAp = reDotProductCuda(p, Ap);
alpha = r2 / pAp;
r2_old = r2;
r2 = axpyNormCuda(-alpha, Ap, rSloppy);
// reliable update conditions
rNorm = sqrt(r2);
if (rNorm > maxrx) maxrx = rNorm;
if (rNorm > maxrr) maxrr = rNorm;
int updateX = (rNorm < delta*r0Norm && r0Norm <= maxrx) ? 1 : 0;
int updateR = ((rNorm < delta*maxrr && r0Norm <= maxrr) || updateX) ? 1 : 0;
if (!(updateR || updateX)) {
beta = r2 / r2_old;
axpyZpbxCuda(alpha, p, xSloppy, rSloppy, beta);
} else {
axpyCuda(alpha, p, xSloppy);
if (x.Precision() != xSloppy.Precision()) copyCuda(x, xSloppy);
xpyCuda(x, y); // swap these around?
mat(r, y, x); // here we can use x as tmp
r2 = xmyNormCuda(b, r);
if (x.Precision() != rSloppy.Precision()) copyCuda(rSloppy, r);
zeroCuda(xSloppy);
rNorm = sqrt(r2);
maxrr = rNorm;
maxrx = rNorm;
r0Norm = rNorm;
rUpdate++;
beta = r2 / r2_old;
xpayCuda(rSloppy, beta, p);
}
k++;
if (invParam.verbosity >= QUDA_VERBOSE)
printfQuda("CG: %d iterations, r2 = %e\n", k, r2);
}
if (x.Precision() != xSloppy.Precision()) copyCuda(x, xSloppy);
xpyCuda(y, x);
invParam.secs = stopwatchReadSeconds();
if (k==invParam.maxiter)
warningQuda("Exceeded maximum iterations %d", invParam.maxiter);
if (invParam.verbosity >= QUDA_SUMMARIZE)
printfQuda("CG: Reliable updates = %d\n", rUpdate);
double gflops = (quda::blas_flops + mat.flops() + matSloppy.flops())*1e-9;
reduceDouble(gflops);
// printfQuda("%f gflops\n", gflops / stopwatchReadSeconds());
invParam.gflops = gflops;
invParam.iter = k;
quda::blas_flops = 0;
if (invParam.verbosity >= QUDA_SUMMARIZE){
mat(r, x, y);
double true_res = xmyNormCuda(b, r);
printfQuda("CG: Converged after %d iterations, relative residua: iterated = %e, true = %e\n",
k, sqrt(r2/src_norm), sqrt(true_res / src_norm));
}
if (invParam.cuda_prec_sloppy != x.Precision()) {
delete r_sloppy;
delete x_sloppy;
}
return;
}
void CG::operator()(cudaColorSpinorField &x, cudaColorSpinorField &b)
{
profile.Start(QUDA_PROFILE_INIT);
// Check to see that we're not trying to invert on a zero-field source
const double b2 = norm2(b);
if(b2 == 0){
profile.Stop(QUDA_PROFILE_INIT);
printfQuda("Warning: inverting on zero-field source\n");
x=b;
param.true_res = 0.0;
param.true_res_hq = 0.0;
return;
}
cudaColorSpinorField r(b);
ColorSpinorParam csParam(x);
csParam.create = QUDA_ZERO_FIELD_CREATE;
cudaColorSpinorField y(b, csParam);
mat(r, x, y);
// zeroCuda(y);
double r2 = xmyNormCuda(b, r);
csParam.setPrecision(param.precision_sloppy);
cudaColorSpinorField Ap(x, csParam);
cudaColorSpinorField tmp(x, csParam);
cudaColorSpinorField *tmp2_p = &tmp;
// tmp only needed for multi-gpu Wilson-like kernels
if (mat.Type() != typeid(DiracStaggeredPC).name() &&
mat.Type() != typeid(DiracStaggered).name()) {
tmp2_p = new cudaColorSpinorField(x, csParam);
}
cudaColorSpinorField &tmp2 = *tmp2_p;
cudaColorSpinorField *x_sloppy, *r_sloppy;
if (param.precision_sloppy == x.Precision()) {
csParam.create = QUDA_REFERENCE_FIELD_CREATE;
x_sloppy = &x;
r_sloppy = &r;
} else {
csParam.create = QUDA_COPY_FIELD_CREATE;
x_sloppy = new cudaColorSpinorField(x, csParam);
r_sloppy = new cudaColorSpinorField(r, csParam);
}
cudaColorSpinorField &xSloppy = *x_sloppy;
cudaColorSpinorField &rSloppy = *r_sloppy;
cudaColorSpinorField p(rSloppy);
if(&x != &xSloppy){
copyCuda(y,x);
zeroCuda(xSloppy);
}else{
zeroCuda(y);
}
const bool use_heavy_quark_res =
(param.residual_type & QUDA_HEAVY_QUARK_RESIDUAL) ? true : false;
profile.Stop(QUDA_PROFILE_INIT);
profile.Start(QUDA_PROFILE_PREAMBLE);
double r2_old;
double stop = b2*param.tol*param.tol; // stopping condition of solver
double heavy_quark_res = 0.0; // heavy quark residual
if(use_heavy_quark_res) heavy_quark_res = sqrt(HeavyQuarkResidualNormCuda(x,r).z);
int heavy_quark_check = 10; // how often to check the heavy quark residual
double alpha=0.0, beta=0.0;
double pAp;
int rUpdate = 0;
double rNorm = sqrt(r2);
double r0Norm = rNorm;
double maxrx = rNorm;
double maxrr = rNorm;
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
int maxResIncrease = 0; // 0 means we have no tolerance
profile.Stop(QUDA_PROFILE_PREAMBLE);
profile.Start(QUDA_PROFILE_COMPUTE);
blas_flops = 0;
int k=0;
PrintStats("CG", k, r2, b2, heavy_quark_res);
int steps_since_reliable = 1;
while ( !convergence(r2, heavy_quark_res, stop, param.tol_hq) &&
k < param.maxiter) {
matSloppy(Ap, p, tmp, tmp2); // tmp as tmp
double sigma;
bool breakdown = false;
if (param.pipeline) {
double3 triplet = tripleCGReductionCuda(rSloppy, Ap, p);
r2 = triplet.x; double Ap2 = triplet.y; pAp = triplet.z;
r2_old = r2;
alpha = r2 / pAp;
sigma = alpha*(alpha * Ap2 - pAp);
if (sigma < 0.0 || steps_since_reliable==0) { // sigma condition has broken down
r2 = axpyNormCuda(-alpha, Ap, rSloppy);
sigma = r2;
breakdown = true;
}
r2 = sigma;
} else {
r2_old = r2;
pAp = reDotProductCuda(p, Ap);
alpha = r2 / pAp;
// here we are deploying the alternative beta computation
Complex cg_norm = axpyCGNormCuda(-alpha, Ap, rSloppy);
r2 = real(cg_norm); // (r_new, r_new)
sigma = imag(cg_norm) >= 0.0 ? imag(cg_norm) : r2; // use r2 if (r_k+1, r_k+1-r_k) breaks
}
// reliable update conditions
rNorm = sqrt(r2);
if (rNorm > maxrx) maxrx = rNorm;
if (rNorm > maxrr) maxrr = rNorm;
int updateX = (rNorm < delta*r0Norm && r0Norm <= maxrx) ? 1 : 0;
int updateR = ((rNorm < delta*maxrr && r0Norm <= maxrr) || updateX) ? 1 : 0;
// force a reliable update if we are within target tolerance (only if doing reliable updates)
if ( convergence(r2, heavy_quark_res, stop, param.tol_hq) && delta >= param.tol) updateX = 1;
if ( !(updateR || updateX)) {
//beta = r2 / r2_old;
beta = sigma / r2_old; // use the alternative beta computation
if (param.pipeline && !breakdown) tripleCGUpdateCuda(alpha, beta, Ap, rSloppy, xSloppy, p);
else axpyZpbxCuda(alpha, p, xSloppy, rSloppy, beta);
if (use_heavy_quark_res && k%heavy_quark_check==0) {
copyCuda(tmp,y);
heavy_quark_res = sqrt(xpyHeavyQuarkResidualNormCuda(xSloppy, tmp, rSloppy).z);
}
steps_since_reliable++;
} else {
axpyCuda(alpha, p, xSloppy);
if (x.Precision() != xSloppy.Precision()) copyCuda(x, xSloppy);
xpyCuda(x, y); // swap these around?
mat(r, y, x); // here we can use x as tmp
r2 = xmyNormCuda(b, r);
if (x.Precision() != rSloppy.Precision()) copyCuda(rSloppy, r);
zeroCuda(xSloppy);
// break-out check if we have reached the limit of the precision
static int resIncrease = 0;
if (sqrt(r2) > r0Norm && updateX) { // reuse r0Norm for this
warningQuda("CG: new reliable residual norm %e is greater than previous reliable residual norm %e", sqrt(r2), r0Norm);
k++;
rUpdate++;
if (++resIncrease > maxResIncrease) break;
} else {
resIncrease = 0;
}
rNorm = sqrt(r2);
maxrr = rNorm;
maxrx = rNorm;
r0Norm = rNorm;
rUpdate++;
// explicitly restore the orthogonality of the gradient vector
double rp = reDotProductCuda(rSloppy, p) / (r2);
axpyCuda(-rp, rSloppy, p);
beta = r2 / r2_old;
xpayCuda(rSloppy, beta, p);
if(use_heavy_quark_res) heavy_quark_res = sqrt(HeavyQuarkResidualNormCuda(y,r).z);
steps_since_reliable = 0;
}
breakdown = false;
k++;
PrintStats("CG", k, r2, b2, heavy_quark_res);
}
if (x.Precision() != xSloppy.Precision()) copyCuda(x, xSloppy);
xpyCuda(y, x);
profile.Stop(QUDA_PROFILE_COMPUTE);
profile.Start(QUDA_PROFILE_EPILOGUE);
param.secs = profile.Last(QUDA_PROFILE_COMPUTE);
double gflops = (quda::blas_flops + mat.flops() + matSloppy.flops())*1e-9;
reduceDouble(gflops);
param.gflops = gflops;
param.iter += k;
if (k==param.maxiter)
warningQuda("Exceeded maximum iterations %d", param.maxiter);
if (getVerbosity() >= QUDA_VERBOSE)
printfQuda("CG: Reliable updates = %d\n", rUpdate);
// compute the true residuals
mat(r, x, y);
param.true_res = sqrt(xmyNormCuda(b, r) / b2);
#if (__COMPUTE_CAPABILITY__ >= 200)
param.true_res_hq = sqrt(HeavyQuarkResidualNormCuda(x,r).z);
#else
param.true_res_hq = 0.0;
#endif
PrintSummary("CG", k, r2, b2);
// reset the flops counters
quda::blas_flops = 0;
mat.flops();
matSloppy.flops();
profile.Stop(QUDA_PROFILE_EPILOGUE);
profile.Start(QUDA_PROFILE_FREE);
if (&tmp2 != &tmp) delete tmp2_p;
if (param.precision_sloppy != x.Precision()) {
delete r_sloppy;
delete x_sloppy;
}
profile.Stop(QUDA_PROFILE_FREE);
return;
}
void PreconCG::operator()(cudaColorSpinorField &x, cudaColorSpinorField &b)
{
profile.Start(QUDA_PROFILE_INIT);
// Check to see that we're not trying to invert on a zero-field source
const double b2 = norm2(b);
if(b2 == 0){
profile.Stop(QUDA_PROFILE_INIT);
printfQuda("Warning: inverting on zero-field source\n");
x=b;
param.true_res = 0.0;
param.true_res_hq = 0.0;
}
int k=0;
int rUpdate=0;
cudaColorSpinorField* minvrPre;
cudaColorSpinorField* rPre;
cudaColorSpinorField* minvr;
cudaColorSpinorField* minvrSloppy;
cudaColorSpinorField* p;
ColorSpinorParam csParam(b);
cudaColorSpinorField r(b);
if(K) minvr = new cudaColorSpinorField(b);
csParam.create = QUDA_ZERO_FIELD_CREATE;
cudaColorSpinorField y(b,csParam);
mat(r, x, y); // => r = A*x;
double r2 = xmyNormCuda(b,r);
csParam.setPrecision(param.precision_sloppy);
cudaColorSpinorField tmpSloppy(x,csParam);
cudaColorSpinorField Ap(x,csParam);
cudaColorSpinorField *r_sloppy;
if(param.precision_sloppy == x.Precision())
{
r_sloppy = &r;
minvrSloppy = minvr;
}else{
csParam.create = QUDA_COPY_FIELD_CREATE;
r_sloppy = new cudaColorSpinorField(r,csParam);
if(K) minvrSloppy = new cudaColorSpinorField(*minvr,csParam);
}
cudaColorSpinorField *x_sloppy;
if(param.precision_sloppy == x.Precision() ||
!param.use_sloppy_partial_accumulator) {
csParam.create = QUDA_REFERENCE_FIELD_CREATE;
x_sloppy = &x;
}else{
csParam.create = QUDA_COPY_FIELD_CREATE;
x_sloppy = new cudaColorSpinorField(x,csParam);
}
cudaColorSpinorField &xSloppy = *x_sloppy;
cudaColorSpinorField &rSloppy = *r_sloppy;
if(&x != &xSloppy){
copyCuda(y, x); // copy x to y
zeroCuda(xSloppy);
}else{
zeroCuda(y); // no reliable updates // NB: check this
}
const bool use_heavy_quark_res = (param.residual_type & QUDA_HEAVY_QUARK_RESIDUAL) ? true : false;
if(K){
csParam.create = QUDA_COPY_FIELD_CREATE;
csParam.setPrecision(param.precision_precondition);
rPre = new cudaColorSpinorField(rSloppy,csParam);
// Create minvrPre
minvrPre = new cudaColorSpinorField(*rPre);
globalReduce = false;
(*K)(*minvrPre, *rPre);
globalReduce = true;
*minvrSloppy = *minvrPre;
p = new cudaColorSpinorField(*minvrSloppy);
}else{
p = new cudaColorSpinorField(rSloppy);
}
profile.Stop(QUDA_PROFILE_INIT);
profile.Start(QUDA_PROFILE_PREAMBLE);
double stop = stopping(param.tol, b2, param.residual_type); // stopping condition of solver
double heavy_quark_res = 0.0; // heavy quark residual
if(use_heavy_quark_res) heavy_quark_res = sqrt(HeavyQuarkResidualNormCuda(x,r).z);
int heavy_quark_check = 10; // how often to check the heavy quark residual
double alpha = 0.0, beta=0.0;
double pAp;
double rMinvr = 0;
double rMinvr_old = 0.0;
double r_new_Minvr_old = 0.0;
double r2_old = 0;
r2 = norm2(r);
double rNorm = sqrt(r2);
double r0Norm = rNorm;
double maxrx = rNorm;
double maxrr = rNorm;
double delta = param.delta;
if(K) rMinvr = reDotProductCuda(rSloppy,*minvrSloppy);
profile.Stop(QUDA_PROFILE_PREAMBLE);
profile.Start(QUDA_PROFILE_COMPUTE);
quda::blas_flops = 0;
int steps_since_reliable = 1;
const int maxResIncrease = 0;
while(!convergence(r2, heavy_quark_res, stop, param.tol_hq) && k < param.maxiter){
matSloppy(Ap, *p, tmpSloppy);
double sigma;
bool breakdown = false;
pAp = reDotProductCuda(*p,Ap);
alpha = (K) ? rMinvr/pAp : r2/pAp;
Complex cg_norm = axpyCGNormCuda(-alpha, Ap, rSloppy);
// r --> r - alpha*A*p
r2_old = r2;
r2 = real(cg_norm);
sigma = imag(cg_norm) >= 0.0 ? imag(cg_norm) : r2; // use r2 if (r_k+1, r_k-1 - r_k) breaks
if(K) rMinvr_old = rMinvr;
rNorm = sqrt(r2);
if(rNorm > maxrx) maxrx = rNorm;
if(rNorm > maxrr) maxrr = rNorm;
int updateX = (rNorm < delta*r0Norm && r0Norm <= maxrx) ? 1 : 0;
int updateR = ((rNorm < delta*maxrr && r0Norm <= maxrr) || updateX) ? 1 : 0;
// force a reliable update if we are within target tolerance (only if doing reliable updates)
if( convergence(r2, heavy_quark_res, stop, param.tol_hq) && delta >= param.tol) updateX = 1;
if( !(updateR || updateX) ){
if(K){
r_new_Minvr_old = reDotProductCuda(rSloppy,*minvrSloppy);
*rPre = rSloppy;
globalReduce = false;
(*K)(*minvrPre, *rPre);
globalReduce = true;
*minvrSloppy = *minvrPre;
rMinvr = reDotProductCuda(rSloppy,*minvrSloppy);
beta = (rMinvr - r_new_Minvr_old)/rMinvr_old;
axpyZpbxCuda(alpha, *p, xSloppy, *minvrSloppy, beta);
}else{
beta = sigma/r2_old; // use the alternative beta computation
axpyZpbxCuda(alpha, *p, xSloppy, rSloppy, beta);
}
} else { // reliable update
axpyCuda(alpha, *p, xSloppy); // xSloppy += alpha*p
copyCuda(x, xSloppy);
xpyCuda(x, y); // y += x
// Now compute r
mat(r, y, x); // x is just a temporary here
r2 = xmyNormCuda(b, r);
copyCuda(rSloppy, r); // copy r to rSloppy
zeroCuda(xSloppy);
// break-out check if we have reached the limit of the precision
static int resIncrease = 0;
if(sqrt(r2) > r0Norm && updateX) { // reuse r0Norm for this
warningQuda("PCG: new reliable residual norm %e is greater than previous reliable residual norm %e", sqrt(r2), r0Norm);
k++;
rUpdate++;
if(++resIncrease > maxResIncrease) break;
}else{
resIncrease = 0;
}
rNorm = sqrt(r2);
maxrr = rNorm;
maxrx = rNorm;
r0Norm = rNorm;
++rUpdate;
if(K){
*rPre = rSloppy;
globalReduce = false;
(*K)(*minvrPre, *rPre);
globalReduce = true;
*minvrSloppy = *minvrPre;
rMinvr = reDotProductCuda(rSloppy,*minvrSloppy);
beta = rMinvr/rMinvr_old;
xpayCuda(*minvrSloppy, beta, *p); // p = minvrSloppy + beta*p
}else{ // standard CG - no preconditioning
// explicitly restore the orthogonality of the gradient vector
double rp = reDotProductCuda(rSloppy, *p)/(r2);
axpyCuda(-rp, rSloppy, *p);
beta = r2/r2_old;
xpayCuda(rSloppy, beta, *p);
steps_since_reliable = 0;
}
}
breakdown = false;
++k;
PrintStats("PCG", k, r2, b2, heavy_quark_res);
}
profile.Stop(QUDA_PROFILE_COMPUTE);
profile.Start(QUDA_PROFILE_EPILOGUE);
if(x.Precision() != param.precision_sloppy) copyCuda(x, xSloppy);
xpyCuda(y, x); // x += y
param.secs = profile.Last(QUDA_PROFILE_COMPUTE);
double gflops = (quda::blas_flops + mat.flops() + matSloppy.flops() + matPrecon.flops())*1e-9;
reduceDouble(gflops);
param.gflops = gflops;
param.iter += k;
if (k==param.maxiter)
warningQuda("Exceeded maximum iterations %d", param.maxiter);
if (getVerbosity() >= QUDA_VERBOSE)
printfQuda("CG: Reliable updates = %d\n", rUpdate);
// compute the true residual
mat(r, x, y);
double true_res = xmyNormCuda(b, r);
param.true_res = sqrt(true_res / b2);
// reset the flops counters
quda::blas_flops = 0;
mat.flops();
matSloppy.flops();
matPrecon.flops();
profile.Stop(QUDA_PROFILE_EPILOGUE);
profile.Start(QUDA_PROFILE_FREE);
if(K){ // These are only needed if preconditioning is used
delete minvrPre;
delete rPre;
delete minvr;
if(x.Precision() != param.precision_sloppy) delete minvrSloppy;
}
delete p;
if(x.Precision() != param.precision_sloppy){
delete x_sloppy;
delete r_sloppy;
}
profile.Stop(QUDA_PROFILE_FREE);
return;
}
