示例#1
0
bool IterativeSolvers::pcg(const IRCMatrix &A,
                           Vector &x,
                           const Vector &b,
                           const Preconditioner &M) {
    /*!
      Solves Ax=b using the preconditioned conjugate gradient method.
      */
    const idx N = x.getLength();
    real resid(100.0);
    Vector p(N), z(N), q(N);
    real alpha;
    real normr(0);
    real normb = norm(b);
    real rho(0), rho_1(0), beta(0);
    Vector r = b - A * x;
    if (normb == 0.0)
        normb = 1;
    resid = norm(r) / normb;
    if (resid <= IterativeSolvers::toler) {
        IterativeSolvers::toler = resid;
        IterativeSolvers::maxIter = 0;
        return true;
    }
    // MAIN LOOP
    idx i = 1;
    for (; i <= IterativeSolvers::maxIter; i++) {
        M.solveMxb(z, r);
        rho = dot(r, z);
        if (i == 1)
            p = z;
        else {
            beta = rho / rho_1;
            aypx(beta, p, z); // p = beta*p + z;
        }
        // CALCULATES q = A*p AND dp = dot(q,p)
        real dp = multiply_dot(A, p, q);
        alpha = rho / dp;
        normr = 0;
#ifdef USES_OPENMP
        #pragma omp parallel for reduction(+:normr)
#endif
        for (idx j = 0 ; j < N ; ++j) {
            x[j] += alpha * p[j]; // x + alpha(0) * p;
            r[j] -= alpha * q[j]; // r - alpha(0) * q;
            normr += r[j] * r[j];
        }
        normr = sqrt(normr);
        resid = normr / normb;
        if (resid <= IterativeSolvers::toler) {
            IterativeSolvers::toler = resid;
            IterativeSolvers::maxIter = i;
            return true;
        }
        rho_1 = rho;
    }
    IterativeSolvers::toler = resid;
    return false;
}
示例#2
0
bool IterativeSolvers::gmres(const IRCMatrix &A,
                             Vector &x,
                             const Vector &b,
                             const Preconditioner &M) {
    const idx N = x.getLength();
    idx i, j = 1, k;
    Vector s(maxInnerIter + 1);
    Vector cs(maxInnerIter + 1);
    Vector sn(maxInnerIter + 1);
    Vector w(N);
    real normb = norm(M.solve(b));
    Vector r = M.solve(b - A * x);
    real beta = norm(r);
    if (normb == 0.0)
        normb = 1;
    real res(norm(r) / normb);
    if (res <= toler) {
        toler = res;
        maxIter = 0;
        return true;
    }
    Vector *v = new Vector[maxInnerIter + 1];
    for (idx id = 0; id < maxInnerIter + 1; ++id)
        v[id] = Vector(N);
    // CREATE HESSENBERG MATRIX NEEDED TO STORE INTERMEDIATES
    DenseMatrix H(maxInnerIter + 1, maxInnerIter);
    Vector temp(N);
    Vector temp2(maxInnerIter + 1);
    // MAIN LOOP
    while (j <= maxIter) {
        v[0] = r * (1.0 / beta);
        s = 0.0;
        s(0) = beta;
        // INNER ITERATIONS
        for (i = 0; i < maxInnerIter && j <= maxIter; i++, j++) {
            // CALCULATE w = M^{-1}(A*v[i])
            multiply(A, v[i], temp);
            M.solveMxb(w, temp);
            // PRE-CALCULATE DOT PRODUCTS IN PARALLEL
            // H(k,i) = dot( v[k], w)
#ifdef USES_OPENMP
            #pragma omp parallel for
#endif
            for (k = 0; k <= i ; ++k) {
                register real dp(0);
                for (idx id = 0 ; id < N ; ++id)
                    dp += w[id] * v[k][id];
                H(k, i) = dp; //dot(w,v[k]);
            }
            for (k = 0; k <= i; ++k) {
                // w -= v[k]*H(k,i) without temporaries
                register real tempr = H(k, i);
#ifdef USES_OPENMP
                #pragma omp parallel for // why is this loop so critical??
#endif
                for (idx id = 0 ; id < N ; ++id)
                    w[id] -= v[k][id] * tempr;
            }
            // BELOW PARALLEL REGION CALCULATES:
            // H(i+1,i) = norm(w);
            // v[i+1] = w * (1.0 / H(i+1, i));
            H(i + 1, i) = 0;
            real tempr(0);
#ifdef USES_OPENMP
            #pragma omp parallel shared(tempr)
#endif
            {
#ifdef USES_OPENMP
                #pragma omp for reduction(+:tempr)
#endif
                for (idx id = 0 ; id < N ; ++id)
                    tempr += w[id] * w[id]; //norm(w);
#ifdef USES_OPENMP
                #pragma omp single
#endif
                {
                    H(i + 1, i) = sqrt(tempr);
                    tempr = (1.0 / H(i + 1, i));
                }
#ifdef USES_OPENMP
                #pragma omp for
#endif
                for (idx id = 0 ; id < N ; ++id)
                    v[i + 1][id] = w[id] * tempr;
            }// end for omp parallel
            for (k = 0; k < i; k++)
                ApplyPlaneRotation(H(k, i), H(k + 1, i), cs(k), sn(k));
            GeneratePlaneRotation(H(i, i), H(i + 1, i), cs(i), sn(i));
            ApplyPlaneRotation(H(i, i), H(i + 1, i), cs(i), sn(i));
            ApplyPlaneRotation(s(i), s(i + 1), cs(i), sn(i));
            res = fabs(s(i + 1)) / normb;
            if (res < toler) {
                // COPY S INTO temp WITHOUT RESIZING
                for (idx id = 0 ; id < maxInnerIter + 1 ; ++id)
                    temp2[id] = s[id];
                Update(x, i, H, temp2, v);
                toler = res;
                maxIter = j;
                delete [] v;
                return true;
            }
        }// end for i IINNER ITERATIONS
        // COPY S INTO temp WITHOUT RESIZING
        for (idx id = 0 ; id < maxInnerIter + 1 ; ++id)
            temp2[id] = s[id];
        Update(x, maxInnerIter - 1, H, temp2, v);
        //multiply(A, x, temp);     //r = M.solve(b - A * x);
        M.solveMxb(r, b - A * x);
        beta = norm(r);
        res = beta / normb;
        if (res < toler) {
            toler = res;
            maxIter = j;
            delete [] v;
            return true;
        }
    }
    toler = res;
    delete [] v;
    return false;
}