congrad.c

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#include <matrices.h>
#include <clover.h>
#include <float.h>

void Q_allocate_f(Complex_f **p_f, Complex_f **x1_f, Complex_f **x2_f, Complex_f **r_f, Complex_f **X1_f){
   const char funcname[] = "Q_allocate";
#ifdef USE_GPU
#ifdef _DEBUG
   cudaMallocManaged((void **)p_f, kferm2Halo*sizeof(Complex_f),cudaMemAttachGlobal);
   cudaMallocManaged((void **)x1_f, kferm2Halo*sizeof(Complex_f),cudaMemAttachGlobal);
   cudaMallocManaged((void **)x2_f, kferm2*sizeof(Complex_f),cudaMemAttachGlobal);
 
   cudaMallocManaged((void **)r_f, kferm2*sizeof(Complex_f),cudaMemAttachGlobal);
   cudaMallocManaged((void **)X1_f, kferm2*sizeof(Complex_f),cudaMemAttachGlobal);
#else
   //First two have halo exchanges, so getting NCCL working is important
   cudaMallocAsync((void **)p_f, kferm2Halo*sizeof(Complex_f),streams[0]);
   cudaMallocAsync((void **)x1_f, kferm2Halo*sizeof(Complex_f),streams[1]);
   cudaMallocAsync((void **)x2_f, kferm2*sizeof(Complex_f),streams[2]);
 
   cudaMallocAsync((void **)r_f, kferm2*sizeof(Complex_f),streams[3]);
   cudaMallocAsync((void **)X1_f, kferm2*sizeof(Complex_f),streams[4]);
#endif
#else
   *p_f=(Complex_f *)aligned_alloc(AVX,kferm2Halo*sizeof(Complex_f));
   *x1_f=(Complex_f *)aligned_alloc(AVX,kferm2Halo*sizeof(Complex_f));
   *x2_f=(Complex_f *)aligned_alloc(AVX,kferm2*sizeof(Complex_f));
 
   *r_f=(Complex_f *)aligned_alloc(AVX,kferm2*sizeof(Complex_f));
   *X1_f=(Complex_f *)aligned_alloc(AVX,kferm2*sizeof(Complex_f));
#endif
   return;
}

void Q_allocate(Complex **p, Complex **x1, Complex **x2, Complex *clover[2]){
   const char funcname[] = "Q_allocate";
#ifdef USE_GPU
#ifdef _DEBUG
   cudaMallocManaged((void **)&clover[0], 6*kvol*sizeof(Complex),cudaMemAttachGlobal);
   cudaMallocManaged((void **)&clover[1], 6*kvol*sizeof(Complex),cudaMemAttachGlobal);
   cudaMallocManaged((void **)p, kferm2Halo*sizeof(Complex),cudaMemAttachGlobal);
   cudaMallocManaged((void **)x1, kferm2Halo*sizeof(Complex),cudaMemAttachGlobal);
   cudaMallocManaged((void **)x2, kferm2*sizeof(Complex),cudaMemAttachGlobal);
#else
   //First two have halo exchanges, so getting NCCL working is important
   cudaMallocAsync((void **)&clover[0], 6*kvol*sizeof(Complex),streams[0]);
   cudaMallocAsync((void **)&clover[1], 6*kvol*sizeof(Complex),streams[1]);
   cudaMallocAsync((void **)p, kferm2Halo*sizeof(Complex),streams[2]);
   cudaMallocAsync((void **)x1, kferm2Halo*sizeof(Complex),streams[3]);
   cudaMallocAsync((void **)x2, kferm2*sizeof(Complex),streams[4]);
#endif
#else
   clover[0]=(Complex *)aligned_alloc(AVX,6*kvol*sizeof(Complex));
   clover[1]=(Complex *)aligned_alloc(AVX,6*kvol*sizeof(Complex));
   *p=(Complex *)aligned_alloc(AVX,kferm2Halo*sizeof(Complex));
   *x1=(Complex *)aligned_alloc(AVX,kferm2Halo*sizeof(Complex));
   *x2=(Complex *)aligned_alloc(AVX,kferm2*sizeof(Complex));
#endif
   return;
}

void P_allocate_f(Complex_f **p_f,Complex_f **r_f, Complex_f **x1_f, Complex_f **x2_f, Complex_f **xi_f){
#ifdef USE_GPU
#ifdef _DEBUG
   cudaMallocManaged((void **)p_f, kfermHalo*sizeof(Complex_f),cudaMemAttachGlobal);
   cudaMallocManaged((void **)r_f, kferm*sizeof(Complex_f),cudaMemAttachGlobal);
   cudaMallocManaged((void **)x1_f, kfermHalo*sizeof(Complex_f),cudaMemAttachGlobal);
   cudaMallocManaged((void **)x2_f, kferm*sizeof(Complex_f),cudaMemAttachGlobal);
   cudaMallocManaged((void **)xi_f, kferm*sizeof(Complex_f),cudaMemAttachGlobal);
#else
   cudaMalloc((void **)p_f, kfermHalo*sizeof(Complex_f));
   cudaMalloc((void **)r_f, kferm*sizeof(Complex_f));
   cudaMalloc((void **)x1_f, kfermHalo*sizeof(Complex_f));
   cudaMalloc((void **)x2_f, kferm*sizeof(Complex_f));
   cudaMalloc((void **)xi_f, kferm*sizeof(Complex_f));
#endif
   cudaDeviceSynchronise();
#else
   *p_f  =  aligned_alloc(AVX,kfermHalo*sizeof(Complex_f));
   *r_f  =  aligned_alloc(AVX,kferm*sizeof(Complex_f));
   *x1_f =  aligned_alloc(AVX,kfermHalo*sizeof(Complex_f));
   *x2_f =  aligned_alloc(AVX,kferm*sizeof(Complex_f));
   *xi_f =  aligned_alloc(AVX,kferm*sizeof(Complex_f));
#endif
}

void P_allocate(Complex **p, Complex **r, Complex **x1, Complex **x2,Complex *clover[2]){
#ifdef USE_GPU
#ifdef _DEBUG
   cudaMallocManaged((void **)&clover[0], 6*kvol*sizeof(Complex),cudaMemAttachGlobal);
   cudaMallocManaged((void **)&clover[1], 6*kvol*sizeof(Complex),cudaMemAttachGlobal);
   cudaMallocManaged((void **)p, kfermHalo*sizeof(Complex), cudaMemAttachGlobal);
   cudaMallocManaged((void **)r, kferm*sizeof(Complex), cudaMemAttachGlobal);
   cudaMallocManaged((void **)x1, kfermHalo*sizeof(Complex), cudaMemAttachGlobal);
   cudaMallocManaged((void **)x2, kferm*sizeof(Complex), cudaMemAttachGlobal);
#else
   cudaMallocAsync((void **)&clover[0], 6*kvol*sizeof(Complex),streams[0]);
   cudaMallocAsync((void **)&clover[1], 6*kvol*sizeof(Complex),streams[1]);
   cudaMallocAsync((void **)p, kfermHalo*sizeof(Complex),streams[2]);
   cudaMallocAsync((void **)r, kferm*sizeof(Complex),streams[3]);
   cudaMallocAsync((void **)x1, kfermHalo*sizeof(Complex),streams[4]);
   cudaMallocAsync((void **)x2, kferm*sizeof(Complex),streams[5]);
#endif
   cudaDeviceSynchronise();
#else
   clover[0]=(Complex *)aligned_alloc(AVX,6*kvol*sizeof(Complex));
   clover[1]=(Complex *)aligned_alloc(AVX,6*kvol*sizeof(Complex));
   *p  = aligned_alloc(AVX, kfermHalo*sizeof(Complex));
   *r  = aligned_alloc(AVX, kferm*sizeof(Complex));
   *x1 = aligned_alloc(AVX, kfermHalo*sizeof(Complex));
   *x2 = aligned_alloc(AVX, kferm*sizeof(Complex));
#endif
}

void Q_free_f(Complex_f **p_f, Complex_f **x1_f, Complex_f **x2_f, Complex_f **r_f, Complex_f **X1_f){
   const char funcname[] = "Q_free";
#ifdef USE_GPU
#ifdef _DEBUG
   cudaDeviceSynchronise();
   cudaFree(*x1_f);cudaFree(*x2_f); cudaFree(*p_f);
   cudaFree(*r_f); cudaFree(*X1_f);
#else
   //streams match the ones that allocated them.
   cudaFreeAsync(*p_f,streams[0]);cudaFreeAsync(*x1_f,streams[1]);cudaFreeAsync(*x2_f,streams[2]);
   cudaDeviceSynchronise();
   cudaFreeAsync(*r_f,streams[3]); cudaFreeAsync(*X1_f,streams[4]);
#endif
#else
   free(*x1_f); free(*x2_f); free(*p_f); free(*r_f);free(*X1_f);
#endif
   return;
}

void Q_free(Complex **p, Complex **x1, Complex **x2, Complex *clover[2]){
   const char funcname[] = "Qree";
#ifdef USE_GPU
#ifdef _DEBUG
   cudaDeviceSynchronise();
   cudaFree(*x1);cudaFree(*x2); cudaFree(*p);
   cudaFree(clover[0]); cudaFree(clover[1]);
#else
   //streams match the ones that allocated them.
   cudaFreeAsync(clover[0],streams[0]); cudaFreeAsync(clover[1],streams[1]);
   cudaFreeAsync(*p,streams[2]);cudaFreeAsync(*x1,streams[3]);cudaFreeAsync(*x2,streams[4]);
   cudaDeviceSynchronise();
#endif
#else
   free(*x1);free(*x2); free(*p); 
   free(clover[0]); free(clover[1]);
#endif
   return;
}

void P_free_f(Complex_f **p_f,Complex_f **r_f, Complex_f **x1_f, Complex_f **x2_f, Complex_f **xi_f){
#ifdef   USE_GPU
   cudaFree(*p_f); cudaFree(*r_f);cudaFree(*x1_f); cudaFree(*x2_f); cudaFree(*xi_f); 
#else
   free(*p_f); free(*r_f); free(*x1_f); free(*x2_f); free(*xi_f); 
#endif
}

void P_free(Complex **p, Complex **r, Complex **x1, Complex **x2,Complex *clover[2]){
#ifdef USE_GPU
#ifdef _DEBUG
   cudaFree(clover[0]); cudaFree(clover[1]);
   cudaFree(*p);cudaFree(*r);cudaFree(*x1); cudaFree(*x2);
#else
   cudaFreeAsync(clover[0],streams[0]); cudaFreeAsync(clover[1],streams[1]);
   cudaFreeAsync(*p,streams[2]);cudaFreeAsync(*r,streams[3]);cudaFreeAsync(*x1,streams[4]); cudaFreeAsync(*x2,streams[5]);
#endif
#else
   free(*p); free(*r); free(*x1); free(*x2);
   free(clover[0]); free(clover[1]);
#endif
}
 
int Congradq(int na,double res,Complex *X1,Complex *r,Complex *ud[2], Complex_f *ut[2],Complex_f *clover_f[nc],
      unsigned int *iu, unsigned int *id, Complex gamval[20], Complex_f gamval_f[20],const unsigned short gamin[16],
      Complex *sigval, Complex_f *sigval_f,unsigned short *sigin, double *dk[2], float *dk_f[2],
      Complex_f jqq,float akappa,float c_sw,int *itercg){
   const char funcname[] = "Congradq";
   int ret_val=0;
   const double resid = res*res;
#ifdef _DEBUGCG
#warning "CG Debugging"
   char *endline = "\n";
#else
   char *endline = "\r";
#endif

   const float d_prec=1.0f/128.0f;
   const Complex_f fac_f = conj(jqq)*jqq*akappa*akappa;
   //These were evaluated only in the first loop of niterx so we'll just do it outside of the loop.
   //n suffix is numerator, d is denominator
   alignas(16) double alphan=1;
   //Alignment needed for cuBLAS
   alignas(16) double betad = 1.0; alignas(8) Complex_f alphad=0; alignas(16) Complex alpha = 1;
   //Because we're dealing with flattened arrays here we can call cblas safely without the halo
 
   Complex_f *p_f, *x1_f, *x2_f, *r_f, *X1_f;
   Complex   *p, *x1, *x2, *clover[2];
   Q_allocate_f(&p_f,&x1_f,&x2_f,&r_f,&X1_f);
   Q_allocate(&p,&x1,&x2,clover);
 
   //Instead of copying element-wise in a loop, use memcpy.
   //Get X1 in single precision
   //Since X1 has a halo and X1_f does not we have to do this manually
#if (nproc>1)
   for(unsigned short j=0;j<nc*ndirac;j++)
      ComplexConvert(X1_f+j*kvol,X1+j*kvolHalo,kvol,true,1);
#else
   ComplexConvert(X1_f,X1,kferm2,true,1);
#endif
   ComplexConvert(r_f,r,kferm2,true,1);
   //And clover in double
   if(c_sw){
      ComplexConvert(clover_f[0],clover[0],6*kvol,false,1);
      ComplexConvert(clover_f[1],clover[1],6*kvol,false,1);
   }
#ifdef USE_GPU
   //Ensure conversion is done
   cudaDeviceSynchronise();
   //Needs to be strided
#if (nproc>1)
   for(unsigned int j=0;j<nc*ndirac;j++)
      cudaMemcpyAsync(p_f+j*kvolHalo, X1_f+j*kvol, kvol*sizeof(Complex_f),cudaMemcpyDefault,streams[j]);
   cudaDeviceSynchronise();
#else
   cudaMemcpy(p_f, X1_f, kferm2*sizeof(Complex_f),cudaMemcpyDefault);
#endif
#else
#pragma omp parallel for simd aligned(X1_f,r_f,X1,r:AVX)
   for(unsigned int j=0;j<nc*ndirac;j++)
      memcpy(p_f+j*kvolHalo, X1_f+j*kvol, kvol*sizeof(Complex_f));
#endif
 
   alignas(16) double betan=1;double beta_max=FLT_MAX; bool do_dp=true;
   for(*itercg=0; *itercg<niterc; (*itercg)++){
      if(do_dp){
#ifdef _DEBUGCG
         if(!rank)
            printf("Going to double precision on iteration %d. betan %e\talpha %e.\n",
                  *itercg,betan,creal(alpha));
#elifdef _DEBUG
         if(!rank)
            printf("\nGoing to double precision on iteration %d. betan %e\talpha %e.\n",
                  *itercg,betan,creal(alpha));
#endif
         ComplexConvert(r_f,r,kferm2,false,1);
         ComplexConvert(p_f,p,kvol,false,nc*ndirac);
#ifdef USE_GPU
         //Update the residue vector, but not on the first call.
         //TODO: Check for multi-gpu. I fear this will get messy
         if(*itercg)
            cuMixed_Sumto((double *)X1,(float *)X1_f,2*kferm2,dimGrid,dimBlock);
         //Bring everything into double precision
         //Reset X1_f to zero.
         cudaMemset(X1_f,0,kferm2*sizeof(Complex_f));
#else
         //Update the residue vector, but not on the first call.
         if(*itercg)
#pragma omp parallel for simd collapse(2) aligned(X1,X1_f:AVX)
            for(unsigned short j=0;j<nc*ndirac;j++)
               for(unsigned int i=0;i<kvol;i++){
                  X1[i+j*kvolHalo]+=(Complex)X1_f[i+j*kvol];
               }
         memset(X1_f,0,kferm2*sizeof(Complex_f));
#endif
         //No need to synchronise here. The memcpy in Hdslash is blocking
         Hdslash(x1,p,ud,iu,id,gamval,gamin,dk,akappa);
         //Clover contribution
         if(c_sw)
            HbyClover(x1,p,clover,sigval,akappa,sigin,false);
         Hdslashd(x2,x1,ud,iu,id,gamval,gamin,dk,akappa);
         //Clover contribution
         if(c_sw)
            HbyClover(x2,x1,clover,sigval,akappa,sigin,true);
#ifdef   USE_GPU
         cudaDeviceSynchronise();
#endif
         if(fac_f!=0){
            alignas(16) const double fac=(double)fac_f;
#ifdef   USE_GPU
            //Multiple ranks means we need striding
#if (nproc>1)
            for(unsigned short j=0;j<nc*ndirac;j++) 
               cublasZaxpy(cublas_handle,kvol,(cuDoubleComplex *)&fac,(cuDoubleComplex *)p+j*kvolHalo,1,(cuDoubleComplex *)x2+j*kvol,1);
#else
            //Single GPU, no halos, so make it one call to speed things up
            cublasZaxpy(cublas_handle,kferm2,(cuDoubleComplex *)&fac,(cuDoubleComplex *)p,1,(cuDoubleComplex *)x2,1);
#endif
#elif defined USE_BLAS
            for(unsigned short j=0;j<nc*ndirac;j++) 
               cblas_zaxpy(kvol, &fac, p+j*kvolHalo, 1, x2+j*kvol, 1);
#else
#pragma omp parallel for simd collapse(2) aligned(p,x2:AVX)
            for(unsigned short j=0;j<nc*ndirac;j++) 
               for(unsigned int i=0; i<kvol; i++)
                  x2[i+j*kvol]+=fac*p[i+j*kvolHalo];
#endif
         }

         if(*itercg){
            alpha=0;
#ifdef USE_GPU
#if (nproc>1)
            for(unsigned short j=0;j<nc*ndirac;j++){
               Complex alpha_t=0;
               cublasZdotc(cublas_handle,kvol,(cuDoubleComplex *)p+j*kvolHalo,1,(cuDoubleComplex *)x2+j*kvol,1,(cuDoubleComplex *)&alpha_t);
               alpha+=alpha_t;
            }
#else
            cublasZdotc(cublas_handle,kferm2,(cuDoubleComplex *)p,1,(cuDoubleComplex *)x2,1,(cuDoubleComplex *)&alpha);
#endif
#elif defined USE_BLAS
            for(unsigned short j=0;j<nc*ndirac;j++){
               Complex alpha_t=0;
               cblas_zdotc_sub(kvol, p+j*kvolHalo, 1, x2+j*kvol, 1, &alpha_t);
               alpha+=creal(alpha_t);
            }
#else
#pragma omp parallel for simd collapse(2) aligned(p,x2:AVX) reduction(+:alpha)
            for(unsigned short j=0;j<nc*ndirac;j++) 
               for(unsigned int i=0; i<kvol; i++)
                  alpha+=conj(p[i+j*kvolHalo])*x2[i+j*kvol];
#endif
            //For now I'll cast it into a float for the reduction. Each rank only sends and writes
            //to the real part so this is fine
#if (nproc>1)
            Par_dsum((double *)&alpha);
#endif
            alpha=alphan/creal(alpha);
#ifdef USE_GPU
#if (nproc>1)
            for(unsigned short j=0;j<nc*ndirac;j++)
               cublasZaxpy(cublas_handle,kvol,(cuDoubleComplex *)&alpha,(cuDoubleComplex *)p+j*kvolHalo,1,(cuDoubleComplex *)X1+j*kvolHalo,1);
#else
            cublasZaxpy(cublas_handle,kferm2,(cuDoubleComplex *)&alpha,(cuDoubleComplex *)p,1,(cuDoubleComplex *)X1,1);
#endif
#elif defined USE_BLAS
            for(unsigned short j=0;j<nc*ndirac;j++)
               cblas_zaxpy(kvol, &alpha, p+j*kvolHalo, 1, X1+j*kvolHalo, 1);
#else
#pragma omp parallel for simd collapse(2) aligned(p,X1:AVX)
            for(unsigned short j=0;j<nc*ndirac;j++)
               for(unsigned int i=0; i<kvol; i++)
                  X1[i+j*kvolHalo]+=alpha*p[i+j*kvolHalo];
#endif
         }
 
#ifdef   USE_GPU
         alignas(16) Complex alpha_m=(Complex)(-alpha);
         cublasZaxpy(cublas_handle, kferm2,(cuDoubleComplex *)&alpha_m,(cuDoubleComplex *)x2,1,(cuDoubleComplex *)r,1);
         alignas(16) double betan_d;
         cublasDznrm2(cublas_handle,kferm2,(cuDoubleComplex *)r,1,&betan_d);
         betan=betan_d*betan_d;
#elif defined USE_BLAS
         const Complex alpha_m = (Complex)(-alpha);
         cblas_zaxpy(kferm2, &alpha_m, x2, 1, r, 1);
         //Undo the negation for the BLAS routine
         double betan_d = cblas_dznrm2(kferm2, r,1);
         //Gotta square it to "undo" the norm
         betan = betan_d*betan_d;
#else
         betan=0;
#pragma omp parallel for simd aligned(r_f,x2_f:AVX) reduction(+:betan) 
         for(unsigned int i=0; i<kferm2; i++){
            r[i]-=alpha*x2[i];
            betan += conj(r[i])*r[i];
         }
         alignas(16) double betan_d=sqrt(betan);
#endif
         //And... reduce.
#if (nproc>1)
         Par_dsum(&betan);
#endif
         betan_d=sqrt(betan);
         //Update beta_max. Mandatory for double precision.
         beta_max=betan_d;
#ifdef _DEBUG
         if(!rank) printf("DP Iter(CG)=%i\tbeta_n=%e\talpha=%e\n", *itercg, betan, creal(alpha));
         fflush(stdout);
#endif
         alignas(16) const Complex beta = (*itercg) ?  betan/betad : 0;
         betad=betan; alphan=betan;
#ifdef USE_GPU
         alpha_m=1;
         //Strided multi-gpu
#if (nproc>1)
         for(unsigned short j=0;j<nc*ndirac;j++){
            cublasZdscal(cublas_handle,kvol,(double *)&beta,(cuDoubleComplex *)p+j*kvolHalo,1);
            cublasZaxpy(cublas_handle,kvol,(cuDoubleComplex *)&alpha_m,(cuDoubleComplex *)r+j*kvol,1,(cuDoubleComplex *)p+j*kvolHalo,1);
         }
         //And single GPU
#else
         cublasZdscal(cublas_handle,kferm2,(double *)&beta,(cuDoubleComplex *)p,1);
         cublasZaxpy(cublas_handle,kferm2,(cuDoubleComplex *)&alpha_m,(cuDoubleComplex *)r,1,(cuDoubleComplex *)p,1);
#endif
#elif (defined __USE_MKL__||defined OPENBLAS||defined AMD_BLAS)
         const Complex a = 1.0;
         //There is cblas_?axpby in the MKL and AMD though, set a = 1 and b = \beta.
         //If we get a small enough \beta_n before hitting the iteration cap we break
         for(unsigned short j=0;j<nc*ndirac;j++)
            cblas_zaxpby(kvol, &a, r+j*kvol, 1, &beta,  p+j*kvolHalo, 1);
#elifdef USE_BLAS
         const Complex a = 1.0;
         for(unsigned short j=0;j<nc*ndirac;j++){
            cblas_zscal(kvol,&beta,p+j*kvolHalo,1);
            cblas_zaxpy(kvol,&a,r+j*kvol,1,p+j*kvolHalo,1);
         }
#else 
#pragma omp parallel for simd collapse(2) aligned(r,p:AVX)
         for(unsigned short j=0;j<nc*ndirac;j++)
            for(unsigned int i=0; i<kvol; i++)
               p[i+j*kvolHalo]=r[i+j*kvol]+beta*p[i+j*kvolHalo];
#endif
         ComplexConvert(p_f,p,kvol,true,nc*ndirac);
         ComplexConvert(r_f,r,kferm2,true,1);
#ifdef _DEBUGCG
         if(!rank) printf("Double precision. Iter(CG)=%i\tbeta_n=%e\talpha=%e\n", *itercg, betan, creal(alpha));
         fflush(stdout);
#endif
         if(betan<resid){ 
            (*itercg)++;
#ifdef _DEBUG
            if(!rank) printf("\nIter(CG)=%i\tResidue: %e\tTolerance: %e\n", *itercg, betan, resid);
#endif
            ret_val=0;  break;
         }
         else
            do_dp=false;
      }
      else{
         //No need to synchronise here. The memcpy in Hdslash is blocking
         Hdslash_f(x1_f,p_f,ut,iu,id,gamval_f,gamin,dk_f,akappa);
         //Clover contribution
         if(c_sw)
            HbyClover_f(x1_f,p_f,clover_f,sigval_f,akappa,sigin,false);
         Hdslashd_f(x2_f,x1_f,ut,iu,id,gamval_f,gamin,dk_f,akappa);
         //Clover contribution
         if(c_sw)
            HbyClover_f(x2_f,x1_f,clover_f,sigval_f,akappa,sigin,true);
#ifdef   USE_GPU
         cudaDeviceSynchronise();
#endif
         //No point adding zero a couple of hundred times if the diquark source is zero
         if(fac_f!=0){
#ifdef   USE_GPU
            //Strided multi-gpu
#if (nproc>1)
            for(unsigned short j=0;j<nc*ndirac;j++) 
               cublasCaxpy(cublas_handle,kvol,(cuComplex *)&fac_f,(cuComplex *)p_f+j*kvolHalo,1,(cuComplex *)x2_f+j*kvol,1);
            //Single GPU
#else
            cublasCaxpy(cublas_handle,kferm2,(cuComplex *)&fac_f,(cuComplex *)p_f,1,(cuComplex *)x2_f,1);
#endif
#elif defined USE_BLAS
            for(unsigned short j=0;j<nc*ndirac;j++) 
               cblas_caxpy(kvol, &fac_f, p_f+j*kvolHalo, 1, x2_f+j*kvol, 1);
#else
#pragma omp parallel for simd collapse(2) aligned(p_f,x2_f:AVX)
            for(unsigned short j=0;j<nc*ndirac;j++) 
               for(unsigned int i=0; i<kvol; i++)
                  x2_f[i+j*kvol]+=fac_f*p_f[i+j*kvolHalo];
#endif
         }
         if(*itercg){
            alphad=0;
#ifdef USE_GPU
#if (nproc>1)
            for(unsigned short j=0;j<nc*ndirac;j++){
               Complex alpha_t=0;
               cublasCdotc(cublas_handle,kvol,(cuComplex *)p_f+j*kvolHalo,1,(cuComplex *)x2_f+j*kvol,1,(cuComplex *)&alpha_t);
               alphad+=alpha_t;
            }
#else
            cublasCdotc(cublas_handle,kferm2,(cuComplex *)p_f,1,(cuComplex *)x2_f,1,(cuComplex *)&alphad);
#endif
#elif defined USE_BLAS
            for(unsigned short j=0;j<nc*ndirac;j++){
               Complex_f alpha_t=0;
               cblas_cdotc_sub(kvol, p_f+j*kvolHalo, 1, x2_f+j*kvol, 1, &alpha_t);
               alphad+=creal(alpha_t);
            }
#else
#pragma omp parallel for simd aligned(p_f,x2_f:AVX) reduction(alphad:+)
            for(unsigned short j=0;j<nc*ndirac;j++)
               for(unsigned int i=0; i<kvol; i++)
                  alphad+=conj(p_f[i+j*kvolHalo])*x2_f[i+j*kvol];
#endif
            //For now I'll cast it into a float for the reduction. Each rank only sends and writes
            //to the real part so this is fine
#if (nproc>1)
            Par_fsum((float *)&alphad);
#endif
            alpha=alphan/creal(alphad);
#ifdef USE_GPU
            alignas(8) Complex_f alpha_f = (Complex_f)alpha;
#if (nproc>1)
            for(unsigned short j=0;j<nc*ndirac;j++)
               cublasCaxpy(cublas_handle,kvol,(cuComplex *)&alpha_f,(cuComplex *)p_f+j*kvolHalo,1,(cuComplex *)X1_f+j*kvol,1);
#else
            cublasCaxpy(cublas_handle,kferm2,(cuComplex *)&alpha_f,(cuComplex *)p_f,1,(cuComplex *)X1_f,1);
#endif
#elif defined USE_BLAS
            Complex_f alpha_f = (Complex_f)alpha;
            for(unsigned short j=0;j<nc*ndirac;j++)
               cblas_caxpy(kvol, &alpha_f, p_f+j*kvolHalo, 1, X1_f+j*kvol, 1);
#else
#pragma omp parallel for simd collapse(2) aligned(X1_f,p_f:AVX)
            for(unsigned short j=0;j<nc*ndirac;j++)
               for(unsigned int i=0; i<kvol; i++)
                  X1_f[i+j*kvol]+=alpha*p_f[i+j*kvolHalo];
#endif
         }        
         // And no Halos here so nice and easy
#ifdef   USE_GPU
         alignas(8) __managed__ Complex_f alpha_m=(Complex_f)(-alpha);
         cublasCaxpy(cublas_handle, kferm2,(cuComplex *)&alpha_m,(cuComplex *)x2_f,1,(cuComplex *)r_f,1);
         alignas(8) float betan_f;
         cublasScnrm2(cublas_handle,kferm2,(cuComplex *)r_f,1,&betan_f);
         betan = betan_f*betan_f;
#elif defined USE_BLAS
         const Complex_f alpha_m = (Complex_f)(-alpha);
         cblas_caxpy(kferm2, &alpha_m, x2_f, 1, r_f, 1);
         //Undo the negation for the BLAS routine
         float betan_f = cblas_scnrm2(kferm2, r_f,1);
         //Gotta square it to "undo" the norm
         betan = betan_f*betan_f;
#else
         betan=0;
#pragma omp parallel for simd aligned(r_f,x2_f:AVX) reduction(+:betan) 
         for(unsigned int i=0; i<kferm2; i++){
            r_f[i]-=alpha*x2_f[i];
            betan += conj(r_f[i])*r_f[i];
         }
         alignas(8) float betan_f=sqrt(betan);
#endif
         //And... reduce.
#if (nproc>1)
         Par_dsum(&betan);
#endif
         betan_f=sqrt(betan);
         //Update beta_max if needed. On paper congrad is monotonically decreasing
         beta_max = (betan_f>beta_max) ?betan_f : beta_max;
 
#ifdef _DEBUG
         if(!rank) printf("Iter(CG)=%i\tbeta_n=%e\talpha=%e%s", *itercg, betan, creal(alpha),endline);
         fflush(stdout);
#endif
         if(betan_f<beta_max*d_prec){ 
#ifdef _DEBUG
            if(!rank)
               printf("\nResidue %e is less than %e times %e.%s",betan_f,d_prec,beta_max,endline);
#endif
            do_dp=true;
         }
         else if(betan<resid){
#ifdef _DEBUG
            if(!rank)
               printf("\nBetan %e is less than target residue %e.\n",betan,resid);
#endif
            do_dp=true;
            //break;
         }
         else if(*itercg==niterc-1){
            if(!rank) fprintf(stderr, "\nWarning %i in %s: Exceeded iteration limit %i beta_n=%e\n",\
                  ITERLIM, funcname, *itercg, betan);
            ret_val=ITERLIM;  break;
         }
         //Here we evaluate beta=(r_{k+1}.r_{k+1})/(r_k.r_k) and then shuffle our indices down the line.
         //On the first iteration we define beta to be zero.
         //Note that beta below is not the global beta and scoping is used to avoid conflict between them
         Complex beta = (*itercg) ?  betan/betad : 0;
         betad=betan; alphan=betan;
         //BLAS for p=r+\betap doesn't exist in standard BLAS. This is NOT an axpy case as we're multiplying y by
         //\beta instead of x.
#ifdef USE_GPU
         alignas(8) Complex_f beta_f=(Complex_f)beta;
         alpha_m = 1.0;
#if (nproc>1)
         for(unsigned short j=0;j<nc*ndirac;j++){
            cublasCscal(cublas_handle,kvol,(cuComplex *)&beta_f,(cuComplex *)p_f+j*kvolHalo,1);
            cublasCaxpy(cublas_handle,kvol,(cuComplex *)&alpha_m,(cuComplex *)r_f+j*kvolHalo,1,(cuComplex *)p_f+j*kvolHalo,1);
         }
#else
         cublasCscal(cublas_handle,kferm2,(cuComplex *)&beta_f,(cuComplex *)p_f,1);
         cublasCaxpy(cublas_handle,kferm2,(cuComplex *)&alpha_m,(cuComplex *)r_f,1,(cuComplex *)p_f,1);
#endif
#elif (defined __USE_MKL__||defined OPENBLAS||defined AMD_BLAS)
         Complex_f a = 1.0;
         Complex_f beta_f=(Complex_f)beta;
         //There is cblas_?axpby in the MKL and AMD though, set a = 1 and b = \beta.
         //If we get a small enough \beta_n before hitting the iteration cap we break
         for(unsigned short j=0;j<nc*ndirac;j++)
            cblas_caxpby(kvol, &a, r_f+j*kvol, 1, &beta_f,  p_f+j*kvolHalo, 1);
#elif defined USE_BLAS
         Complex_f beta_f=(Complex_f)beta;
         Complex_f a = 1.0;
         for(unsigned short j=0;j<nc*ndirac;j++){
            cblas_cscal(kvol,&beta_f,p_f+j*kvolHalo,1);
            cblas_caxpy(kvol,&a,r_f+j*kvol,1,p_f+j*kvolHalo,1);
         }
#else 
#pragma omp parallel for simd collapse(2) aligned(p_f,r_f:AVX)
         for(unsigned short j=0;j<nc*ndirac;j++)
            for(unsigned int i=0; i<kvol; i++)
               p_f[i+j*kvolHalo]=r_f[i+j*kvol]+beta*p_f[i+j*kvolHalo];
#endif
      }
   }
   Q_free_f(&p_f,&x1_f,&x2_f,&r_f,&X1_f);
   Q_free(&p,&x1,&x2,clover);
   return ret_val;
}
int Congradp(int na, double res, Complex *Phi, Complex *xi, Complex *ud[2], Complex_f *ut[2], Complex_f *clover_f[nc],
      unsigned int *iu, unsigned int *id, Complex gamval[20], Complex_f gamval_f[20], const unsigned short gamin[16],
      Complex *sigval, Complex_f *sigval_f,unsigned short *sigin, double *dk[2], float *dk_f[2],
      Complex_f jqq,float akappa,float c_sw,int *itercg){
   const char funcname[] = "Congradp";
   //Return value
   int ret_val=0;
   const double resid = res*res;
#ifdef _DEBUGCG
#warning "CG Debugging"
   char *endline = "\n";
#else
   char *endline = "\r";
#endif

   const float d_prec=1.0f/128.0f;
 
   //These were evaluated only in the first loop of niterx so we'll just do it outside of the loop.
   alignas(8) double alphan=1.0;
   //These alpha and beta terms should be double, but that causes issues with BLAS. Instead we declare
   //them Complex and work with the real part (especially for \alpha_d)
   //Give initial values Will be overwritten if niterx>0
   alignas(8) double betad = 1.0; alignas(8) Complex_f alphad=0; alignas(16)Complex alpha = 1; //Alignment needed for cuBLAS
 
   Complex_f *p_f, *r_f, *x1_f, *x2_f, *xi_f;
   Complex *p, *r, *x1, *x2, *clover[nc];
   P_allocate_f(&p_f,&r_f,&x1_f,&x2_f,&xi_f);
   P_allocate(&p, &r, &x1, &x2,clover);
 
   ComplexConvert(r_f,Phi+na*kferm,kferm,true,1);
   ComplexConvert(xi_f,xi,kferm,true,1);
   if(c_sw){
      ComplexConvert(clover_f[0],clover[0],6*kvol,false,1);
      ComplexConvert(clover_f[1],clover[1],6*kvol,false,1);
   }
   //Instead of copying element-wise in a loop, use memcpy.
#ifdef USE_GPU
   //Get r in single precision
   //Get xi  in single precision
   cudaMemcpy(r,Phi+na*kferm,kferm*sizeof(Complex),cudaMemcpyDefault);
#if (nproc>1)//strided memcpy
   for(unsigned short j=0;j<nc*ngorkov;j++){
      cudaMemcpyAsync(p+j*kvolHalo,xi+j*kvol,kvol*sizeof(Complex),cudaMemcpyDefault,streams[j]);
      cudaMemcpyAsync(p_f+j*kvolHalo,xi_f+j*kvol,kvol*sizeof(Complex_f),cudaMemcpyDefault,streams[j]);
   }
#else
   cudaMemcpyAsync(p,xi,kferm*sizeof(Complex),cudaMemcpyDefault,streams[0]);
   cudaMemcpyAsync(p_f,xi_f,kferm*sizeof(Complex_f),cudaMemcpyDefault,streams[1]);
#endif
   cudaDeviceSynchronise();
#else
   memcpy(r,Phi+na*kferm,kferm*sizeof(Complex));
   //These strided loops for MPI halos are a total pain in the arse...
   for(unsigned short j=0;j<nc*ngorkov;j++){
      memcpy(p+j*kvolHalo,xi+j*kvol,kvol*sizeof(Complex));
      memcpy(p_f+j*kvolHalo,xi_f+j*kvol,kvol*sizeof(Complex_f));
   }
#endif
 
   double betan=1;double beta_max=FLT_MAX; bool do_dp=true;
   for((*itercg)=0; (*itercg)<niterc; (*itercg)++){
      //Don't overwrite on first run. 
      if(do_dp){
#ifdef _DEBUGCG
         if(!rank)
            printf("Going to double precision on iteration %d.  %sbetan %e\talpha %e.  %s",
                  *itercg,endline,betan,creal(alpha),endline);
#elifdef _DEBUG
         if(!rank)
            printf("\nGoing to double precision on iteration %d. %sbetan %e\talpha %e.\n",
                  *itercg,endline,betan,creal(alpha));
#endif
         ComplexConvert(r_f,r,kferm,false,1);
         //TODO: Banking on converting the halo too being faster than multiple launches
         ComplexConvert(p_f,p,kvol,false,nc*ngorkov);
#ifdef USE_GPU
         //Update the residue vector, but not on the first call.
         if(*itercg)
            cuMixed_Sumto((double *)xi,(float *)xi_f,2*kferm,dimGrid,dimBlock);
         //Bring everything into double precision
         //Reset xi_f to zero.
         cudaDeviceSynchronise();
         cudaMemsetAsync(xi_f,0,kferm*sizeof(Complex_f),streams[4]);
#else
         //Update the residue vector, but not on the first call.
         if(*itercg)
#pragma omp parallel for simd aligned(xi,xi_f:AVX)
            for(unsigned int i=0;i<kferm;i++)
               xi[i]+=(Complex)xi_f[i];
         memset(xi_f,0,kferm*sizeof(Complex_f));
#endif
         //No need to synchronise here.  The memcpy in Dslash is blocking
         Dslash(x1,p,ud,iu,id,gamval,gamin,dk,jqq,akappa);
         if(c_sw)
            ByClover(x1,p,clover,sigval,akappa,sigin,false);
         Dslashd(x2,x1,ud,iu,id,gamval,gamin,dk,jqq,akappa);
         if(c_sw)
            ByClover(x2,x1,clover,sigval,akappa,sigin,true);
#ifdef   USE_GPU
         cudaDeviceSynchronise();
#endif

         if(*itercg){
            alpha=0;
#ifdef USE_GPU
#if (nproc>1)//Strided
            for(unsigned short j=0;j<nc*ngorkov;j++){
               alignas(16) Complex alpha_t=0;
               cublasZdotc(cublas_handle,kvol,(cuDoubleComplex *)p+j*kvolHalo,1,(cuDoubleComplex *)x2+j*kvol,1,(cuDoubleComplex *)&alpha_t);
               alpha+=alpha_t
            }
#else
            cublasZdotc(cublas_handle,kferm,(cuDoubleComplex *)p,1,(cuDoubleComplex *)x2,1,(cuDoubleComplex *)&alpha);
#endif
#elif defined USE_BLAS
            for(unsigned short j=0;j<nc*ngorkov;j++){
               Complex alpha_t=0;
               cblas_zdotc_sub(kvol, p+j*kvolHalo, 1, x2+j*kvol, 1, &alpha_t);
               alpha+=alpha_t;
            }
#else
#pragma omp parallel for simd collapse(2) aligned(p,x2:AVX) reduction(+:alpha)
            for(unsigned short j=0;j<nc*ngorkov;j++)
               for(unsigned int i=0; i<kvol; i++)
                  alpha+=conj(p[i+j*kvolHalo])*x2[i+j*kvol];
#endif
            //For now I'll cast it into a float for the reduction.  Each rank only sends and writes
            //to the real part so this is fine
#if (nproc>1)
            Par_dsum((double *)&alpha);
#endif
            alpha=alphan/creal(alpha);
#ifdef USE_GPU
#if (nproc>1)
            for(unsigned short j=0;j<nc*ngorkov;j++)
               cublasZaxpy(cublas_handle,kvol,(cuDoubleComplex *)&alpha,(cuDoubleComplex *)p+j*kvolHalo,1,(cuDoubleComplex *)xi+j*kvol,1);
#else
            cublasZaxpy(cublas_handle,kferm,(cuDoubleComplex *)&alpha,(cuDoubleComplex *)p,1,(cuDoubleComplex *)xi,1);
#endif
#elif defined USE_BLAS
            for(unsigned short j=0;j<nc*ngorkov;j++)
               cblas_zaxpy(kvol, &alpha, p+j*kvolHalo, 1, xi+j*kvol, 1);
#else
#pragma omp parallel for simd collapse(2) aligned(p,xi:AVX)
            for(unsigned short j=0;j<nc*ngorkov;j++)
               for(unsigned int i=0; i<kvol; i++)
                  xi[i+j*kvol]+=alpha*p[i+j*kvolHalo];
#endif
         }
 
#ifdef   USE_GPU
         Complex alpha_m=(Complex)(-alpha);
         cublasZaxpy(cublas_handle, kferm,(cuDoubleComplex *)&alpha_m,(cuDoubleComplex *)x2,1,(cuDoubleComplex *)r,1);
         double betan_d;
         cublasDznrm2(cublas_handle,kferm,(cuDoubleComplex *)r,1,&betan_d);
         betan=betan_d*betan_d;
#elif defined USE_BLAS
         const Complex alpha_m = (Complex)(-alpha);
         cblas_zaxpy(kferm, &alpha_m, x2, 1, r, 1);
         //Undo the negation for the BLAS routine
         double betan_d = cblas_dznrm2(kferm, r,1);
         //Gotta square it to "undo" the norm
         betan = betan_d*betan_d;
#else
         betan=0;
#pragma omp parallel for simd aligned(r,x2:AVX) reduction(+:betan)
         for(unsigned int i=0; i<kferm; i++){
            r[i]-=alpha*x2[i];
            betan += conj(r[i])*r[i];
         }
         double betan_d=sqrt(betan);
#endif
         //And...  reduce.
#if (nproc>1)
         Par_dsum(&betan);
#endif
         betan_d=sqrt(betan);
         //Update beta_max.  Mandatory for double precision.
         beta_max=betan_d;
#ifdef _DEBUG
         if(! rank) printf("DP Iter(CG)=%i\tbeta_n=%e\talpha=%e\n", *itercg, betan, creal(alpha));
         fflush(stdout);
#endif
         alignas(16) const Complex beta = (*itercg) ?    betan/betad :   0;
         betad=betan; alphan=betan;
#ifdef USE_GPU
         alpha_m=1;
#if (nproc>1)
         for(unsigned short j=0;j<nc*ngorkov;j++){
            cublasZdscal(cublas_handle,kvol,(double *)&beta,(cuDoubleComplex *)p+j*kvolHalo,1);
            cublasZaxpy(cublas_handle,kvol,(cuDoubleComplex *)&alpha_m,(cuDoubleComplex *)r+j*kvol,1,(cuDoubleComplex *)p+j*kvolHalo,1);
         }
#else
         cublasZdscal(cublas_handle,kferm,(double *)&beta,(cuDoubleComplex *)p,1);
         cublasZaxpy(cublas_handle,kferm,(cuDoubleComplex *)&alpha_m,(cuDoubleComplex *)r,1,(cuDoubleComplex *)p,1);
#endif
#elif (defined __USE_MKL__||defined OPENBLAS||defined AMD_BLAS)
         const Complex a = 1.0;
         //There is cblas_? axpby in the MKL and AMD though, set a = 1 and b = \beta.
         //If we get a small enough \beta_n before hitting the iteration cap we break
         for(unsigned short j=0;j<nc*ngorkov;j++)
            cblas_zaxpby(kvol, &a, r+j*kvol, 1, &beta,  p+j*kvolHalo, 1);
#elif defined USE_BLAS
         const Complex a = 1.0;
         for(unsigned short j=0;j<nc*ngorkov;j++){
            cblas_zscal(kvol,&beta,p+j*kvolHalo,1);
            cblas_zaxpy(kvol,&a,r+j*kvol,1,p+j*kvolHalo,1);
         }
#else
#pragma omp parallel for simd collapse(2) aligned(r,p:AVX)
         for(unsigned short j=0;j<nc*ngorkov;j++)
            for(unsigned int i=0; i<kvol; i++)
               p[i+j*kvolHalo]=r[i+j*kvol]+beta*p[i+j*kvolHalo];
#endif
         ComplexConvert(p_f,p,kvol,true,nc*ngorkov);
         ComplexConvert(r_f,r,kferm,true,1);
#ifdef _DEBUGCG
         if(! rank) printf("Double precision.  Iter(CG)=%i\tbeta_n=%e\talpha=%e\n", *itercg, betan, creal(alpha));
         fflush(stdout);
#endif
         if(betan<resid){
            (*itercg)++;
#ifdef _DEBUG
            if(!rank) printf("\nIter(CG)=%i\tResidue:  %e\tTolerance:  %e\n", *itercg, betan, resid);
#endif
            ret_val=0;  break;
         }
         else
            do_dp=false;
      }
      else{
         //x2=(M^\dagger)x1=(M^\dagger)Mp
         Dslash_f(x1_f,p_f,ut,iu,id,gamval_f,gamin,dk_f,jqq,akappa);
         if(c_sw)
            ByClover_f(x1_f,p_f,clover_f,sigval_f,akappa,sigin,false);
         Dslashd_f(x2_f,x1_f,ut,iu,id,gamval_f,gamin,dk_f,jqq,akappa);
         if(c_sw)
            ByClover_f(x2_f,x1_f,clover_f,sigval_f,akappa,sigin,true);
#ifdef USE_GPU
         cudaDeviceSynchronise();
#endif
         //We can't evaluate \alpha on the first niterx because we need to get \beta_n.
         if(*itercg){
            //x*.x
            alphad=0;
#ifdef USE_GPU
#if(nproc>1)//strided
            for(unsigned short j=0;j<nc*ngorkov;j++){
               alignas(8) Complex_f alpha_t=0;
               cublasCdotc(cublas_handle,kvol,(cuComplex *)p_f+j*kvolHalo,1,(cuComplex *)x2_f+j*kvol,1,(cuComplex *)&alpha_t);
               alphad+=alpha_t;
            }
#else
            cublasCdotc(cublas_handle,kferm,(cuComplex *)p_f,1,(cuComplex *)x2_f,1,(cuComplex *)&alphad);
#endif
#elifdef USE_BLAS
            for(unsigned short j=0;j<nc*ngorkov;j++){
               alignas(8) Complex_f alpha_t=0;
               cblas_cdotc_sub(kvol,p_f+j*kvolHalo,1,x2_f+j*kvol,1,&alpha_t);
               alphad+=alpha_t;
            }
#else
#pragma omp parallel for simd collapse(2) aligned(p_f,x2_f:AVX) reduction(+:alphad)
            for(unsigned short j=0;j<nc*ngorkov;j++)
               for(unsigned int i = 0; i<kvol; i++)
                  alphad+=conj(p_f[i+j*kvolHalo])*x2_f[i+j*kvol];
#endif
#if (nproc>1)
            Par_fsum((float *)&alphad);
#endif
            //alpha=(r.r)/p(M^\dagger)Mp
            alpha=alphan/creal(alphad);
            //       Complex_f alpha_f = (Complex_f)alpha;
            //x+\alpha p
#ifdef USE_BLAS
            alignas(8) Complex_f alpha_f=(float)alpha;
#ifdef USE_GPU
#if (nproc>1) //strided
            for(unsigned short j=0;j<nc*ngorkov;j++)
               cublasCaxpy(cublas_handle,kvol,(cuComplex*) &alpha_f,(cuComplex*) p_f+j*kvolHalo,1,(cuComplex*) xi_f+j*kvol,1);
#else
            cublasCaxpy(cublas_handle,kferm,(cuComplex*) &alpha_f,(cuComplex*) p_f,1,(cuComplex*) xi_f,1);
#endif
#else
            for(unsigned short j=0;j<nc*ngorkov;j++)
               cblas_caxpy(kvol, (Complex_f*)&alpha_f,(Complex_f*)p_f+j*kvolHalo, 1, (Complex_f*)xi_f+j*kvol, 1);
#endif
#else
#pragma omp parallel for simd collapse(2) aligned(xi_f,p_f:AVX)
            for(unsigned short j=0;j<nc*ngorkov;j++)
               for(unsigned int i = 0; i<kvol; i++)
                  xi_f[i+j*kvol]+=alpha*p_f[i+j*kvolHalo];
#endif
         }
 
         //r=\alpha(M^\dagger)Mp and \beta_n=r*.r
         alignas(8) float betan_f=0;
#if defined USE_BLAS
         alignas(16) Complex_f alpha_m=(Complex_f)(-alpha);
#ifdef USE_GPU
         cublasCaxpy(cublas_handle,kferm, (cuComplex *)&alpha_m,(cuComplex *) x2_f, 1,(cuComplex *) r_f, 1);
         //cudaDeviceSynchronise();
         //r*.r
         cublasScnrm2(cublas_handle,kferm,(cuComplex *) r_f,1,(float *)&betan_f);
#else
         cblas_caxpy(kferm,(Complex_f*) &alpha_m,(Complex_f*) x2_f, 1,(Complex_f*) r_f, 1);
         //r*.r
         betan_f = cblas_scnrm2(kferm, (Complex_f*)r_f,1);
#endif
         //Gotta square it to "undo" the norm
         betan=betan_f*betan_f;
#else
         //Just like Congradq, this loop could be unrolled but will need a reduction to deal with the betan 
         //addition.
         betan = 0;
         //If we get a small enough \beta_n before hitting the iteration cap we break
#pragma omp parallel for simd aligned(x2_f,r_f:AVX) reduction(+:betan)
         for(unsigned int i = 0; i<kferm;i++){
            r_f[i]-=alpha*x2_f[i];
            betan+=conj(r_f[i])*r_f[i];
         }
         betan_f=sqrt(betan);
#endif
         //This is basically just congradq at the end. Check there for comments
#if (nproc>1)
         Par_dsum(&betan);
#endif
         //Update beta_max if needed. On paper congrad is monotonically decreasing
         betan_f=sqrt(betan);
         beta_max = (betan_f>beta_max) ?betan_f : beta_max;
#ifdef _DEBUG
         if(!rank) printf("Iter (CG) = %i beta_n= %e alpha= %e%s", *itercg, betan, creal(alpha),endline);
#endif
         if(betan_f<beta_max*d_prec){
#ifdef _DEBUG
            if(!rank)
               printf("Residue %e is less than %e times %e. %s",betan_f,d_prec,beta_max,endline);
#endif
            do_dp=true;
         }
         else if(betan<resid){
            //Started counting from zero so add one to make it accurate
            (*itercg)++;
#ifdef _DEBUG
            if(!rank) printf("\nIter (CG) = %i resid = %e toler = %e\n", *itercg, betan, resid);
#endif
            //Final iteration should be in double precision.
            do_dp=true;
         }
         else if(*itercg==niterc-1){
            if(!rank) fprintf(stderr, "Warning %i in %s: Exceeded iteration limit %i beta_n=%e\n",
                  ITERLIM, funcname, niterc, betan);
            ret_val=ITERLIM;  break;
         }
         //Note that beta below is not the global beta and scoping is used to avoid conflict between them
         alignas(8) Complex beta = (*itercg) ? betan/betad : 0;
         betad=betan; alphan=betan;
         //BLAS for p=r+\betap doesn't exist in standard BLAS. This is NOT an axpy case as we're multiplying y by 
         //\beta instead of x.
         //There is cblas_zaxpby in the MKL though, set a = 1 and b = \beta.
#ifdef USE_BLAS
         alignas(8) Complex_f beta_f = (Complex_f)beta;
         alignas(8) Complex_f a = 1.0;
#ifdef USE_GPU
#if (nproc>1) //strided
         for(unsigned short j=0;j<nc*ngorkov;j++){
            cublasCscal(cublas_handle,kvol,(cuComplex *)&beta_f,(cuComplex *)p_f+j*kvolHalo,1);
            cublasCaxpy(cublas_handle,kvol,(cuComplex *)&a,(cuComplex *)r_f+j*kvol,1,(cuComplex *)p_f+j*kvolHalo,1);
         }
#else
         cublasCscal(cublas_handle,kferm,(cuComplex *)&beta_f,(cuComplex *)p_f,1);
         cublasCaxpy(cublas_handle,kferm,(cuComplex *)&a,(cuComplex *)r_f,1,(cuComplex *)p_f,1);
#endif
         cudaDeviceSynchronise();
#elif (defined __USE_MKL__||defined OPENBLAS||defined AMD_BLAS)
         for(unsigned short j=0;j<nc*ngorkov;j++)
            cblas_caxpby(kvol, &a, r_f+j*kvol, 1, &beta_f,  p_f+j*kvolHalo, 1);
#else
         for(unsigned short j=0;j<nc*ngorkov;j++){
            cblas_cscal(kvol,&beta_f,p_f+j*kvolHalo,1);
            cblas_caxpy(kvol,&a,r_f+j*kvol,1,p_f+j*kvolHalo,1);
         }
#endif
#else
#pragma omp parallel for simd aligned(r_f,p_f:AVX)
         for(unsigned short j=0;j<nc*ngorkov;j++)
            for(unsigned int i=0; i<kvol; i++)
               p_f[i+j*kvolHalo]=r_f[i+j*kvol]+beta*p_f[i+j*kvolHalo];
#endif
      }
   }
#ifdef USE_GPU
   cudaDeviceSynchronise();
#endif
   P_free_f(&p_f,&r_f,&x1_f,&x2_f,&xi_f);
   P_free(&p,&r,&x1,&x2,clover);
   return ret_val;
}