pvfmm-static-build/include/mat_utils.txx

/**
 * \file mat_utils.txx
 * \author Dhairya Malhotra, dhairya.malhotra@gmail.com
 * \date 2-11-2011
 * \brief This file contains BLAS and LAPACK wrapper functions.
 */

#include <omp.h>
#include <cmath>
#include <cassert>
#include <cstdlib>
#include <algorithm>
#include <iostream>
#include <vector>

#include <matrix.hpp>
#include <device_wrapper.hpp>
#if defined(PVFMM_HAVE_CUDA)
#include <cuda_runtime_api.h>
#include <cublas_v2.h>
#endif

namespace pvfmm{
namespace mat{

  template <class T>
  inline void gemm(char TransA, char TransB,  int M,  int N,  int K,  T alpha,  T *A,  int lda,  T *B,  int ldb,  T beta, T *C,  int ldc){
    if((TransA=='N' || TransA=='n') && (TransB=='N' || TransB=='n')){
      for(size_t n=0;n<N;n++){ // Columns of C
        for(size_t m=0;m<M;m++){ // Rows of C
            T AxB=0;
            for(size_t k=0;k<K;k++){
              AxB+=A[m+lda*k]*B[k+ldb*n];
            }
            C[m+ldc*n]=alpha*AxB+(beta==0?0:beta*C[m+ldc*n]);
        }
      }
    }else if(TransA=='N' || TransA=='n'){
      for(size_t n=0;n<N;n++){ // Columns of C
        for(size_t m=0;m<M;m++){ // Rows of C
            T AxB=0;
            for(size_t k=0;k<K;k++){
              AxB+=A[m+lda*k]*B[n+ldb*k];
            }
            C[m+ldc*n]=alpha*AxB+(beta==0?0:beta*C[m+ldc*n]);
        }
      }
    }else if(TransB=='N' || TransB=='n'){
      for(size_t n=0;n<N;n++){ // Columns of C
        for(size_t m=0;m<M;m++){ // Rows of C
            T AxB=0;
            for(size_t k=0;k<K;k++){
              AxB+=A[k+lda*m]*B[k+ldb*n];
            }
            C[m+ldc*n]=alpha*AxB+(beta==0?0:beta*C[m+ldc*n]);
        }
      }
    }else{
      for(size_t n=0;n<N;n++){ // Columns of C
        for(size_t m=0;m<M;m++){ // Rows of C
            T AxB=0;
            for(size_t k=0;k<K;k++){
              AxB+=A[k+lda*m]*B[n+ldb*k];
            }
            C[m+ldc*n]=alpha*AxB+(beta==0?0:beta*C[m+ldc*n]);
        }
      }
    }
  }

  template<>
  void gemm<float>(char TransA, char TransB,  int M,  int N,  int K,  float alpha,  float *A,  int lda,  float *B,  int ldb,  float beta, float *C,  int ldc);

  template<>
  void gemm<double>(char TransA, char TransB,  int M,  int N,  int K,  double alpha,  double *A,  int lda,  double *B,  int ldb,  double beta, double *C,  int ldc);

  #if defined(PVFMM_HAVE_CUDA)
  template<>
  inline void cublasgemm<float>(char TransA, char TransB, int M, int N, int K, float alpha, float *A, int lda, float *B, int ldb, float beta, float *C, int ldc) {
    cublasOperation_t cublasTransA, cublasTransB;
    cublasHandle_t *handle = CUDA_Lock::acquire_handle();
    if (TransA == 'T' || TransA == 't') cublasTransA = CUBLAS_OP_T;
    else if (TransA == 'N' || TransA == 'n') cublasTransA = CUBLAS_OP_N;
    if (TransB == 'T' || TransB == 't') cublasTransB = CUBLAS_OP_T;
    else if (TransB == 'N' || TransB == 'n') cublasTransB = CUBLAS_OP_N;
    cublasStatus_t status = cublasSgemm(*handle, cublasTransA, cublasTransB, M, N, K, &alpha, A, lda, B, ldb, &beta, C, ldc);
  }

  template<>
  inline void cublasgemm<double>(char TransA, char TransB, int M, int N, int K, double alpha, double *A, int lda, double *B, int ldb, double beta, double *C, int ldc){
    cublasOperation_t cublasTransA, cublasTransB;
    cublasHandle_t *handle = CUDA_Lock::acquire_handle();
    if (TransA == 'T' || TransA == 't') cublasTransA = CUBLAS_OP_T;
    else if (TransA == 'N' || TransA == 'n') cublasTransA = CUBLAS_OP_N;
    if (TransB == 'T' || TransB == 't') cublasTransB = CUBLAS_OP_T;
    else if (TransB == 'N' || TransB == 'n') cublasTransB = CUBLAS_OP_N;
    cublasStatus_t status = cublasDgemm(*handle, cublasTransA, cublasTransB, M, N, K, &alpha, A, lda, B, ldb, &beta, C, ldc);
  }
  #endif

  #define U(i,j) U_[(i)*dim[0]+(j)]
  #define S(i,j) S_[(i)*dim[1]+(j)]
  #define V(i,j) V_[(i)*dim[1]+(j)]
  //#define SVD_DEBUG

  template <class T>
  void GivensL(T* S_, const size_t dim[2], size_t m, T a, T b){
    T r=sqrt(a*a+b*b);
    T c=a/r;
    T s=-b/r;

    #pragma omp parallel for
    for(size_t i=0;i<dim[1];i++){
      T S0=S(m+0,i);
      T S1=S(m+1,i);
      S(m  ,i)+=S0*(c-1);
      S(m  ,i)+=S1*(-s );

      S(m+1,i)+=S0*( s );
      S(m+1,i)+=S1*(c-1);
    }
  }

  template <class T>
  void GivensR(T* S_, const size_t dim[2], size_t m, T a, T b){
    T r=sqrt(a*a+b*b);
    T c=a/r;
    T s=-b/r;

    #pragma omp parallel for
    for(size_t i=0;i<dim[0];i++){
      T S0=S(i,m+0);
      T S1=S(i,m+1);
      S(i,m  )+=S0*(c-1);
      S(i,m  )+=S1*(-s );

      S(i,m+1)+=S0*( s );
      S(i,m+1)+=S1*(c-1);
    }
  }

  template <class T>
  void SVD(const size_t dim[2], T* U_, T* S_, T* V_, T eps=-1){
    assert(dim[0]>=dim[1]);
    #ifdef SVD_DEBUG
    Matrix<T> M0(dim[0],dim[1],S_);
    #endif

    { // Bi-diagonalization
      size_t n=std::min(dim[0],dim[1]);
      std::vector<T> house_vec(std::max(dim[0],dim[1]));
      for(size_t i=0;i<n;i++){
        // Column Householder
        {
          T x1=S(i,i);
          if(x1<0) x1=-x1;

          T x_inv_norm=0;
          for(size_t j=i;j<dim[0];j++){
            x_inv_norm+=S(j,i)*S(j,i);
          }
          x_inv_norm=1/sqrt(x_inv_norm);

          T alpha=sqrt(1+x1*x_inv_norm);
          T beta=x_inv_norm/alpha;

          house_vec[i]=-alpha;
          for(size_t j=i+1;j<dim[0];j++){
            house_vec[j]=-beta*S(j,i);
          }
          if(S(i,i)<0) for(size_t j=i+1;j<dim[0];j++){
            house_vec[j]=-house_vec[j];
          }
        }
        #pragma omp parallel for
        for(size_t k=i;k<dim[1];k++){
          T dot_prod=0;
          for(size_t j=i;j<dim[0];j++){
            dot_prod+=S(j,k)*house_vec[j];
          }
          for(size_t j=i;j<dim[0];j++){
            S(j,k)-=dot_prod*house_vec[j];
          }
        }
        #pragma omp parallel for
        for(size_t k=0;k<dim[0];k++){
          T dot_prod=0;
          for(size_t j=i;j<dim[0];j++){
            dot_prod+=U(k,j)*house_vec[j];
          }
          for(size_t j=i;j<dim[0];j++){
            U(k,j)-=dot_prod*house_vec[j];
          }
        }

        // Row Householder
        if(i>=n-1) continue;
        {
          T x1=S(i,i+1);
          if(x1<0) x1=-x1;

          T x_inv_norm=0;
          for(size_t j=i+1;j<dim[1];j++){
            x_inv_norm+=S(i,j)*S(i,j);
          }
          x_inv_norm=1/sqrt(x_inv_norm);

          T alpha=sqrt(1+x1*x_inv_norm);
          T beta=x_inv_norm/alpha;

          house_vec[i+1]=-alpha;
          for(size_t j=i+2;j<dim[1];j++){
            house_vec[j]=-beta*S(i,j);
          }
          if(S(i,i+1)<0) for(size_t j=i+2;j<dim[1];j++){
            house_vec[j]=-house_vec[j];
          }
        }
        #pragma omp parallel for
        for(size_t k=i;k<dim[0];k++){
          T dot_prod=0;
          for(size_t j=i+1;j<dim[1];j++){
            dot_prod+=S(k,j)*house_vec[j];
          }
          for(size_t j=i+1;j<dim[1];j++){
            S(k,j)-=dot_prod*house_vec[j];
          }
        }
        #pragma omp parallel for
        for(size_t k=0;k<dim[1];k++){
          T dot_prod=0;
          for(size_t j=i+1;j<dim[1];j++){
            dot_prod+=V(j,k)*house_vec[j];
          }
          for(size_t j=i+1;j<dim[1];j++){
            V(j,k)-=dot_prod*house_vec[j];
          }
        }
      }
    }

    size_t k0=0;
    size_t iter=0;
    if(eps<0){
      eps=1.0;
      while(eps+(T)1.0>1.0) eps*=0.5;
      eps*=64.0;
    }
    while(k0<dim[1]-1){ // Diagonalization
      iter++;

      T S_max=0.0;
      for(size_t i=0;i<dim[1];i++) S_max=(S_max>S(i,i)?S_max:S(i,i));

      //while(k0<dim[1]-1 && fabs(S(k0,k0+1))<=eps*(fabs(S(k0,k0))+fabs(S(k0+1,k0+1)))) k0++;
      while(k0<dim[1]-1 && fabs(S(k0,k0+1))<=eps*S_max) k0++;
      size_t k=k0;

      size_t n=k0+1;
      //while(n<dim[1] && fabs(S(n-1,n))>eps*(fabs(S(n-1,n-1))+fabs(S(n,n)))) n++;
      while(n<dim[1] && fabs(S(n-1,n))>eps*S_max) n++;

      T mu=0;
      { // Compute mu
        T C[3][2];
        C[0][0]=S(n-2,n-2)*S(n-2,n-2)+S(n-3,n-2)*S(n-3,n-2); C[0][1]=S(n-2,n-2)*S(n-2,n-1);
        C[1][0]=S(n-2,n-2)*S(n-2,n-1); C[1][1]=S(n-1,n-1)*S(n-1,n-1)+S(n-2,n-1)*S(n-2,n-1);

        T b=-(C[0][0]+C[1][1])/2;
        T c=  C[0][0]*C[1][1] - C[0][1]*C[1][0];
        T d=sqrt(b*b-c);
        T lambda1=-b+d;
        T lambda2=-b-d;

        T d1=lambda1-C[1][1]; d1=(d1<0?-d1:d1);
        T d2=lambda2-C[1][1]; d2=(d2<0?-d2:d2);
        mu=(d1<d2?lambda1:lambda2);
      }

      T alpha=S(k,k)*S(k,k)-mu;
      T beta=S(k,k)*S(k,k+1);

      for(;k<n-1;k++)
      {
        size_t dimU[2]={dim[0],dim[0]};
        size_t dimV[2]={dim[1],dim[1]};
        GivensR(S_,dim ,k,alpha,beta);
        GivensL(V_,dimV,k,alpha,beta);

        alpha=S(k,k);
        beta=S(k+1,k);
        GivensL(S_,dim ,k,alpha,beta);
        GivensR(U_,dimU,k,alpha,beta);

        alpha=S(k,k+1);
        beta=S(k,k+2);
      }
      //std::cout<<iter<<' '<<k0<<' '<<n<<'\n';
    }

    { // Check Error
      #ifdef SVD_DEBUG
      Matrix<T> U0(dim[0],dim[0],U_);
      Matrix<T> S0(dim[0],dim[1],S_);
      Matrix<T> V0(dim[1],dim[1],V_);
      Matrix<T> E=M0-U0*S0*V0;
      T max_err=0;
      T max_nondiag0=0;
      T max_nondiag1=0;
      for(size_t i=0;i<E.Dim(0);i++)
      for(size_t j=0;j<E.Dim(1);j++){
        if(max_err<fabs(E[i][j])) max_err=fabs(E[i][j]);
        if((i>j+0 || i+0<j) && max_nondiag0<fabs(S0[i][j])) max_nondiag0=fabs(S0[i][j]);
        if((i>j+1 || i+1<j) && max_nondiag1<fabs(S0[i][j])) max_nondiag1=fabs(S0[i][j]);
      }
      std::cout<<max_err<<'\n';
      std::cout<<max_nondiag0<<'\n';
      std::cout<<max_nondiag1<<'\n';
      #endif
    }
  }

  #undef U
  #undef S
  #undef V
  #undef SVD_DEBUG

  template<class T>
  inline void svd(char *JOBU, char *JOBVT, int *M, int *N, T *A, int *LDA,
      T *S, T *U, int *LDU, T *VT, int *LDVT, T *WORK, int *LWORK,
      int *INFO){
    const size_t dim[2]={std::max(*N,*M), std::min(*N,*M)};
    T* U_=mem::aligned_new<T>(dim[0]*dim[0]); memset(U_, 0, dim[0]*dim[0]*sizeof(T));
    T* V_=mem::aligned_new<T>(dim[1]*dim[1]); memset(V_, 0, dim[1]*dim[1]*sizeof(T));
    T* S_=mem::aligned_new<T>(dim[0]*dim[1]);

    const size_t lda=*LDA;
    const size_t ldu=*LDU;
    const size_t ldv=*LDVT;

    if(dim[1]==*M){
      for(size_t i=0;i<dim[0];i++)
      for(size_t j=0;j<dim[1];j++){
        S_[i*dim[1]+j]=A[i*lda+j];
      }
    }else{
      for(size_t i=0;i<dim[0];i++)
      for(size_t j=0;j<dim[1];j++){
        S_[i*dim[1]+j]=A[j*lda+i];
      }
    }
    for(size_t i=0;i<dim[0];i++){
      U_[i*dim[0]+i]=1;
    }
    for(size_t i=0;i<dim[1];i++){
      V_[i*dim[1]+i]=1;
    }

    SVD<T>(dim, U_, S_, V_, (T)-1);

    for(size_t i=0;i<dim[1];i++){ // Set S
      S[i]=S_[i*dim[1]+i];
    }
    if(dim[1]==*M){ // Set U
      for(size_t i=0;i<dim[1];i++)
      for(size_t j=0;j<*M;j++){
        U[j+ldu*i]=V_[j+i*dim[1]]*(S[i]<0.0?-1.0:1.0);
      }
    }else{
      for(size_t i=0;i<dim[1];i++)
      for(size_t j=0;j<*M;j++){
        U[j+ldu*i]=U_[i+j*dim[0]]*(S[i]<0.0?-1.0:1.0);
      }
    }
    if(dim[0]==*N){ // Set V
      for(size_t i=0;i<*N;i++)
      for(size_t j=0;j<dim[1];j++){
        VT[j+ldv*i]=U_[j+i*dim[0]];
      }
    }else{
      for(size_t i=0;i<*N;i++)
      for(size_t j=0;j<dim[1];j++){
        VT[j+ldv*i]=V_[i+j*dim[1]];
      }
    }
    for(size_t i=0;i<dim[1];i++){
      S[i]=S[i]*(S[i]<0.0?-1.0:1.0);
    }

    mem::aligned_delete<T>(U_);
    mem::aligned_delete<T>(S_);
    mem::aligned_delete<T>(V_);

    if(0){ // Verify
      const size_t dim[2]={std::max(*N,*M), std::min(*N,*M)};
      const size_t lda=*LDA;
      const size_t ldu=*LDU;
      const size_t ldv=*LDVT;

      Matrix<T> A1(*M,*N);
      Matrix<T> S1(dim[1],dim[1]);
      Matrix<T> U1(*M,dim[1]);
      Matrix<T> V1(dim[1],*N);
      for(size_t i=0;i<*N;i++)
      for(size_t j=0;j<*M;j++){
        A1[j][i]=A[j+i*lda];
      }
      S1.SetZero();
      for(size_t i=0;i<dim[1];i++){ // Set S
        S1[i][i]=S[i];
      }
      for(size_t i=0;i<dim[1];i++)
      for(size_t j=0;j<*M;j++){
        U1[j][i]=U[j+ldu*i];
      }
      for(size_t i=0;i<*N;i++)
      for(size_t j=0;j<dim[1];j++){
        V1[j][i]=VT[j+ldv*i];
      }
      std::cout<<U1*S1*V1-A1<<'\n';
    }
  }

  template<>
  void svd<float>(char *JOBU, char *JOBVT, int *M, int *N, float *A, int *LDA,
      float *S, float *U, int *LDU, float *VT, int *LDVT, float *WORK, int *LWORK,
      int *INFO);

  template<>
  void svd<double>(char *JOBU, char *JOBVT, int *M, int *N, double *A, int *LDA,
      double *S, double *U, int *LDU, double *VT, int *LDVT, double *WORK, int *LWORK,
      int *INFO);

  /**
   * \brief Computes the pseudo inverse of matrix M(n1xn2) (in row major form)
   * and returns the output M_(n2xn1). Original contents of M are destroyed.
   */
  template <class T>
  void pinv(T* M, int n1, int n2, T eps, T* M_){
    if(n1*n2==0) return;
    int m = n2;
    int n = n1;
    int k = (m<n?m:n);

    T* tU =mem::aligned_new<T>(m*k);
    T* tS =mem::aligned_new<T>(k);
    T* tVT=mem::aligned_new<T>(k*n);

    //SVD
    int INFO=0;
    char JOBU  = 'S';
    char JOBVT = 'S';

    //int wssize = max(3*min(m,n)+max(m,n), 5*min(m,n));
    int wssize = 3*(m<n?m:n)+(m>n?m:n);
    int wssize1 = 5*(m<n?m:n);
    wssize = (wssize>wssize1?wssize:wssize1);

    T* wsbuf = mem::aligned_new<T>(wssize);

    svd(&JOBU, &JOBVT, &m, &n, &M[0], &m, &tS[0], &tU[0], &m, &tVT[0], &k,
        wsbuf, &wssize, &INFO);
    if(INFO!=0)
      std::cout<<INFO<<'\n';
    assert(INFO==0);
    mem::aligned_delete<T>(wsbuf);

    T eps_=tS[0]*eps;
    for(int i=0;i<k;i++)
      if(tS[i]<eps_)
        tS[i]=0;
      else
        tS[i]=1.0/tS[i];


    for(int i=0;i<m;i++){
      for(int j=0;j<k;j++){
        tU[i+j*m]*=tS[j];
      }
    }

    gemm<T>('T','T',n,m,k,1.0,&tVT[0],k,&tU[0],m,0.0,M_,n);
    mem::aligned_delete<T>(tU);
    mem::aligned_delete<T>(tS);
    mem::aligned_delete<T>(tVT);
  }

}//end namespace
}//end namespace