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https://github.com/tildearrow/furnace.git
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54e93db207
not reliable yet
777 lines
22 KiB
C
777 lines
22 KiB
C
/*
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* Copyright (c) 2003, 2007-14 Matteo Frigo
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* Copyright (c) 2003, 2007-14 Massachusetts Institute of Technology
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*
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* This program is free software; you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation; either version 2 of the License, or
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* (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program; if not, write to the Free Software
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* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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*
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*/
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/* rank-0, vector-rank-3, non-square in-place transposition
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(see rank0.c for square transposition) */
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#include "rdft/rdft.h"
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#ifdef HAVE_STRING_H
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#include <string.h> /* for memcpy() */
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#endif
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struct P_s;
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typedef struct {
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rdftapply apply;
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int (*applicable)(const problem_rdft *p, planner *plnr,
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int dim0, int dim1, int dim2, INT *nbuf);
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int (*mkcldrn)(const problem_rdft *p, planner *plnr, struct P_s *ego);
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const char *nam;
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} transpose_adt;
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typedef struct {
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solver super;
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const transpose_adt *adt;
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} S;
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typedef struct P_s {
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plan_rdft super;
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INT n, m, vl; /* transpose n x m matrix of vl-tuples */
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INT nbuf; /* buffer size */
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INT nd, md, d; /* transpose-gcd params */
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INT nc, mc; /* transpose-cut params */
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plan *cld1, *cld2, *cld3; /* children, null if unused */
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const S *slv;
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} P;
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/*************************************************************************/
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/* some utilities for the solvers */
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static INT gcd(INT a, INT b)
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{
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INT r;
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do {
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r = a % b;
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a = b;
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b = r;
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} while (r != 0);
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return a;
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}
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/* whether we can transpose with one of our routines expecting
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contiguous Ntuples */
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static int Ntuple_transposable(const iodim *a, const iodim *b, INT vl, INT vs)
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{
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return (vs == 1 && b->is == vl && a->os == vl &&
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((a->n == b->n && a->is == b->os
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&& a->is >= b->n && a->is % vl == 0)
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|| (a->is == b->n * vl && b->os == a->n * vl)));
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}
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/* check whether a and b correspond to the first and second dimensions
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of a transpose of tuples with vector length = vl, stride = vs. */
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static int transposable(const iodim *a, const iodim *b, INT vl, INT vs)
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{
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return ((a->n == b->n && a->os == b->is && a->is == b->os)
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|| Ntuple_transposable(a, b, vl, vs));
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}
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static int pickdim(const tensor *s, int *pdim0, int *pdim1, int *pdim2)
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{
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int dim0, dim1;
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for (dim0 = 0; dim0 < s->rnk; ++dim0)
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for (dim1 = 0; dim1 < s->rnk; ++dim1) {
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int dim2 = 3 - dim0 - dim1;
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if (dim0 == dim1) continue;
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if ((s->rnk == 2 || s->dims[dim2].is == s->dims[dim2].os)
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&& transposable(s->dims + dim0, s->dims + dim1,
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s->rnk == 2 ? (INT)1 : s->dims[dim2].n,
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s->rnk == 2 ? (INT)1 : s->dims[dim2].is)) {
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*pdim0 = dim0;
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*pdim1 = dim1;
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*pdim2 = dim2;
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return 1;
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}
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}
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return 0;
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}
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#define MINBUFDIV 9 /* min factor by which buffer is smaller than data */
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#define MAXBUF 65536 /* maximum non-ugly buffer */
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/* generic applicability function */
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static int applicable(const solver *ego_, const problem *p_, planner *plnr,
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int *dim0, int *dim1, int *dim2, INT *nbuf)
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{
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const S *ego = (const S *) ego_;
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const problem_rdft *p = (const problem_rdft *) p_;
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return (1
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&& p->I == p->O
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&& p->sz->rnk == 0
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&& (p->vecsz->rnk == 2 || p->vecsz->rnk == 3)
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&& pickdim(p->vecsz, dim0, dim1, dim2)
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/* UGLY if vecloop in wrong order for locality */
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&& (!NO_UGLYP(plnr) ||
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p->vecsz->rnk == 2 ||
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X(iabs)(p->vecsz->dims[*dim2].is)
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< X(imax)(X(iabs)(p->vecsz->dims[*dim0].is),
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X(iabs)(p->vecsz->dims[*dim0].os)))
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/* SLOW if non-square */
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&& (!NO_SLOWP(plnr)
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|| p->vecsz->dims[*dim0].n == p->vecsz->dims[*dim1].n)
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&& ego->adt->applicable(p, plnr, *dim0,*dim1,*dim2,nbuf)
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/* buffers too big are UGLY */
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&& ((!NO_UGLYP(plnr) && !CONSERVE_MEMORYP(plnr))
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|| *nbuf <= MAXBUF
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|| *nbuf * MINBUFDIV <= X(tensor_sz)(p->vecsz))
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);
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}
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static void get_transpose_vec(const problem_rdft *p, int dim2, INT *vl,INT *vs)
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{
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if (p->vecsz->rnk == 2) {
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*vl = 1; *vs = 1;
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}
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else {
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*vl = p->vecsz->dims[dim2].n;
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*vs = p->vecsz->dims[dim2].is; /* == os */
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}
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}
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/*************************************************************************/
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/* Cache-oblivious in-place transpose of non-square matrices, based
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on transposes of blocks given by the gcd of the dimensions.
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This algorithm is related to algorithm V5 from Murray Dow,
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"Transposing a matrix on a vector computer," Parallel Computing 21
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(12), 1997-2005 (1995), with the modification that we use
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cache-oblivious recursive transpose subroutines (and we derived
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it independently).
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For a p x q matrix, this requires scratch space equal to the size
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of the matrix divided by gcd(p,q). Alternatively, see also the
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"cut" algorithm below, if |p-q| * gcd(p,q) < max(p,q). */
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static void apply_gcd(const plan *ego_, R *I, R *O)
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{
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const P *ego = (const P *) ego_;
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INT n = ego->nd, m = ego->md, d = ego->d;
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INT vl = ego->vl;
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R *buf = (R *)MALLOC(sizeof(R) * ego->nbuf, BUFFERS);
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INT i, num_el = n*m*d*vl;
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A(ego->n == n * d && ego->m == m * d);
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UNUSED(O);
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/* Transpose the matrix I in-place, where I is an (n*d) x (m*d) matrix
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of vl-tuples and buf contains n*m*d*vl elements.
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In general, to transpose a p x q matrix, you should call this
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routine with d = gcd(p, q), n = p/d, and m = q/d. */
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A(n > 0 && m > 0 && vl > 0);
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A(d > 1);
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/* treat as (d x n) x (d' x m) matrix. (d' = d) */
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/* First, transpose d x (n x d') x m to d x (d' x n) x m,
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using the buf matrix. This consists of d transposes
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of contiguous n x d' matrices of m-tuples. */
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if (n > 1) {
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rdftapply cldapply = ((plan_rdft *) ego->cld1)->apply;
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for (i = 0; i < d; ++i) {
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cldapply(ego->cld1, I + i*num_el, buf);
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memcpy(I + i*num_el, buf, num_el*sizeof(R));
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}
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}
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/* Now, transpose (d x d') x (n x m) to (d' x d) x (n x m), which
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is a square in-place transpose of n*m-tuples: */
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{
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rdftapply cldapply = ((plan_rdft *) ego->cld2)->apply;
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cldapply(ego->cld2, I, I);
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}
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/* Finally, transpose d' x ((d x n) x m) to d' x (m x (d x n)),
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using the buf matrix. This consists of d' transposes
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of contiguous d*n x m matrices. */
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if (m > 1) {
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rdftapply cldapply = ((plan_rdft *) ego->cld3)->apply;
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for (i = 0; i < d; ++i) {
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cldapply(ego->cld3, I + i*num_el, buf);
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memcpy(I + i*num_el, buf, num_el*sizeof(R));
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}
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}
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X(ifree)(buf);
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}
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static int applicable_gcd(const problem_rdft *p, planner *plnr,
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int dim0, int dim1, int dim2, INT *nbuf)
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{
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INT n = p->vecsz->dims[dim0].n;
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INT m = p->vecsz->dims[dim1].n;
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INT d, vl, vs;
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get_transpose_vec(p, dim2, &vl, &vs);
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d = gcd(n, m);
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*nbuf = n * (m / d) * vl;
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return (!NO_SLOWP(plnr) /* FIXME: not really SLOW for large 1d ffts */
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&& n != m
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&& d > 1
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&& Ntuple_transposable(p->vecsz->dims + dim0,
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p->vecsz->dims + dim1,
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vl, vs));
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}
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static int mkcldrn_gcd(const problem_rdft *p, planner *plnr, P *ego)
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{
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INT n = ego->nd, m = ego->md, d = ego->d;
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INT vl = ego->vl;
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R *buf = (R *)MALLOC(sizeof(R) * ego->nbuf, BUFFERS);
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INT num_el = n*m*d*vl;
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if (n > 1) {
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ego->cld1 = X(mkplan_d)(plnr,
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X(mkproblem_rdft_0_d)(
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X(mktensor_3d)(n, d*m*vl, m*vl,
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d, m*vl, n*m*vl,
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m*vl, 1, 1),
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TAINT(p->I, num_el), buf));
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if (!ego->cld1)
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goto nada;
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X(ops_madd)(d, &ego->cld1->ops, &ego->super.super.ops,
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&ego->super.super.ops);
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ego->super.super.ops.other += num_el * d * 2;
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}
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ego->cld2 = X(mkplan_d)(plnr,
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X(mkproblem_rdft_0_d)(
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X(mktensor_3d)(d, d*n*m*vl, n*m*vl,
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d, n*m*vl, d*n*m*vl,
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n*m*vl, 1, 1),
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p->I, p->I));
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if (!ego->cld2)
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goto nada;
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X(ops_add2)(&ego->cld2->ops, &ego->super.super.ops);
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if (m > 1) {
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ego->cld3 = X(mkplan_d)(plnr,
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X(mkproblem_rdft_0_d)(
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X(mktensor_3d)(d*n, m*vl, vl,
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m, vl, d*n*vl,
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vl, 1, 1),
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TAINT(p->I, num_el), buf));
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if (!ego->cld3)
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goto nada;
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X(ops_madd2)(d, &ego->cld3->ops, &ego->super.super.ops);
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ego->super.super.ops.other += num_el * d * 2;
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}
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X(ifree)(buf);
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return 1;
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nada:
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X(ifree)(buf);
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return 0;
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}
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static const transpose_adt adt_gcd =
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{
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apply_gcd, applicable_gcd, mkcldrn_gcd,
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"rdft-transpose-gcd"
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};
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/*************************************************************************/
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/* Cache-oblivious in-place transpose of non-square n x m matrices,
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based on transposing a sub-matrix first and then transposing the
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remainder(s) with the help of a buffer. See also transpose-gcd,
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above, if gcd(n,m) is large.
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This algorithm is related to algorithm V3 from Murray Dow,
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"Transposing a matrix on a vector computer," Parallel Computing 21
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(12), 1997-2005 (1995), with the modifications that we use
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cache-oblivious recursive transpose subroutines and we have the
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generalization for large |n-m| below.
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The best case, and the one described by Dow, is for |n-m| small, in
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which case we transpose a square sub-matrix of size min(n,m),
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handling the remainder via a buffer. This requires scratch space
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equal to the size of the matrix times |n-m| / max(n,m).
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As a generalization when |n-m| is not small, we also support cutting
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*both* dimensions to an nc x mc matrix which is *not* necessarily
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square, but has a large gcd (and can therefore use transpose-gcd).
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*/
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static void apply_cut(const plan *ego_, R *I, R *O)
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{
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const P *ego = (const P *) ego_;
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INT n = ego->n, m = ego->m, nc = ego->nc, mc = ego->mc, vl = ego->vl;
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INT i;
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R *buf1 = (R *)MALLOC(sizeof(R) * ego->nbuf, BUFFERS);
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UNUSED(O);
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if (m > mc) {
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((plan_rdft *) ego->cld1)->apply(ego->cld1, I + mc*vl, buf1);
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for (i = 0; i < nc; ++i)
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memmove(I + (mc*vl) * i, I + (m*vl) * i, sizeof(R) * (mc*vl));
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}
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((plan_rdft *) ego->cld2)->apply(ego->cld2, I, I); /* nc x mc transpose */
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if (n > nc) {
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R *buf2 = buf1 + (m-mc)*(nc*vl); /* FIXME: force better alignment? */
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memcpy(buf2, I + nc*(m*vl), (n-nc)*(m*vl)*sizeof(R));
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for (i = mc-1; i >= 0; --i)
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memmove(I + (n*vl) * i, I + (nc*vl) * i, sizeof(R) * (n*vl));
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((plan_rdft *) ego->cld3)->apply(ego->cld3, buf2, I + nc*vl);
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}
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if (m > mc) {
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if (n > nc)
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for (i = mc; i < m; ++i)
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memcpy(I + i*(n*vl), buf1 + (i-mc)*(nc*vl),
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(nc*vl)*sizeof(R));
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else
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memcpy(I + mc*(n*vl), buf1, (m-mc)*(n*vl)*sizeof(R));
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}
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X(ifree)(buf1);
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}
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/* only cut one dimension if the resulting buffer is small enough */
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static int cut1(INT n, INT m, INT vl)
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{
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return (X(imax)(n,m) >= X(iabs)(n-m) * MINBUFDIV
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|| X(imin)(n,m) * X(iabs)(n-m) * vl <= MAXBUF);
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}
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#define CUT_NSRCH 32 /* range of sizes to search for possible cuts */
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static int applicable_cut(const problem_rdft *p, planner *plnr,
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int dim0, int dim1, int dim2, INT *nbuf)
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{
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INT n = p->vecsz->dims[dim0].n;
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INT m = p->vecsz->dims[dim1].n;
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INT vl, vs;
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get_transpose_vec(p, dim2, &vl, &vs);
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*nbuf = 0; /* always small enough to be non-UGLY (?) */
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A(MINBUFDIV <= CUT_NSRCH); /* assumed to avoid inf. loops below */
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return (!NO_SLOWP(plnr) /* FIXME: not really SLOW for large 1d ffts? */
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&& n != m
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/* Don't call transpose-cut recursively (avoid inf. loops):
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the non-square sub-transpose produced when !cut1
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should always have gcd(n,m) >= min(CUT_NSRCH,n,m),
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for which transpose-gcd is applicable */
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&& (cut1(n, m, vl)
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|| gcd(n, m) < X(imin)(MINBUFDIV, X(imin)(n,m)))
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&& Ntuple_transposable(p->vecsz->dims + dim0,
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p->vecsz->dims + dim1,
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vl, vs));
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}
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static int mkcldrn_cut(const problem_rdft *p, planner *plnr, P *ego)
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{
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INT n = ego->n, m = ego->m, nc, mc;
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INT vl = ego->vl;
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R *buf;
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/* pick the "best" cut */
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if (cut1(n, m, vl)) {
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nc = mc = X(imin)(n,m);
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}
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else {
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INT dc, ns, ms;
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dc = gcd(m, n); nc = n; mc = m;
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/* search for cut with largest gcd
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(TODO: different optimality criteria? different search range?) */
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for (ms = m; ms > 0 && ms > m - CUT_NSRCH; --ms) {
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for (ns = n; ns > 0 && ns > n - CUT_NSRCH; --ns) {
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INT ds = gcd(ms, ns);
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if (ds > dc) {
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dc = ds; nc = ns; mc = ms;
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if (dc == X(imin)(ns, ms))
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break; /* cannot get larger than this */
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}
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}
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if (dc == X(imin)(n, ms))
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break; /* cannot get larger than this */
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}
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A(dc >= X(imin)(CUT_NSRCH, X(imin)(n, m)));
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}
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ego->nc = nc;
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ego->mc = mc;
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ego->nbuf = (m-mc)*(nc*vl) + (n-nc)*(m*vl);
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buf = (R *)MALLOC(sizeof(R) * ego->nbuf, BUFFERS);
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if (m > mc) {
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ego->cld1 = X(mkplan_d)(plnr,
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X(mkproblem_rdft_0_d)(
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X(mktensor_3d)(nc, m*vl, vl,
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m-mc, vl, nc*vl,
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vl, 1, 1),
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p->I + mc*vl, buf));
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if (!ego->cld1)
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goto nada;
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X(ops_add2)(&ego->cld1->ops, &ego->super.super.ops);
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}
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ego->cld2 = X(mkplan_d)(plnr,
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X(mkproblem_rdft_0_d)(
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X(mktensor_3d)(nc, mc*vl, vl,
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mc, vl, nc*vl,
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vl, 1, 1),
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p->I, p->I));
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if (!ego->cld2)
|
|
goto nada;
|
|
X(ops_add2)(&ego->cld2->ops, &ego->super.super.ops);
|
|
|
|
if (n > nc) {
|
|
ego->cld3 = X(mkplan_d)(plnr,
|
|
X(mkproblem_rdft_0_d)(
|
|
X(mktensor_3d)(n-nc, m*vl, vl,
|
|
m, vl, n*vl,
|
|
vl, 1, 1),
|
|
buf + (m-mc)*(nc*vl), p->I + nc*vl));
|
|
if (!ego->cld3)
|
|
goto nada;
|
|
X(ops_add2)(&ego->cld3->ops, &ego->super.super.ops);
|
|
}
|
|
|
|
/* memcpy/memmove operations */
|
|
ego->super.super.ops.other += 2 * vl * (nc*mc * ((m > mc) + (n > nc))
|
|
+ (n-nc)*m + (m-mc)*nc);
|
|
|
|
X(ifree)(buf);
|
|
return 1;
|
|
|
|
nada:
|
|
X(ifree)(buf);
|
|
return 0;
|
|
}
|
|
|
|
static const transpose_adt adt_cut =
|
|
{
|
|
apply_cut, applicable_cut, mkcldrn_cut,
|
|
"rdft-transpose-cut"
|
|
};
|
|
|
|
/*************************************************************************/
|
|
/* In-place transpose routine from TOMS, which follows the cycles of
|
|
the permutation so that it writes to each location only once.
|
|
Because of cache-line and other issues, however, this routine is
|
|
typically much slower than transpose-gcd or transpose-cut, even
|
|
though the latter do some extra writes. On the other hand, if the
|
|
vector length is large then the TOMS routine is best.
|
|
|
|
The TOMS routine also has the advantage of requiring less buffer
|
|
space for the case of gcd(nx,ny) small. However, in this case it
|
|
has been superseded by the combination of the generalized
|
|
transpose-cut method with the transpose-gcd method, which can
|
|
always transpose with buffers a small fraction of the array size
|
|
regardless of gcd(nx,ny). */
|
|
|
|
/*
|
|
* TOMS Transpose. Algorithm 513 (Revised version of algorithm 380).
|
|
*
|
|
* These routines do in-place transposes of arrays.
|
|
*
|
|
* [ Cate, E.G. and Twigg, D.W., ACM Transactions on Mathematical Software,
|
|
* vol. 3, no. 1, 104-110 (1977) ]
|
|
*
|
|
* C version by Steven G. Johnson (February 1997).
|
|
*/
|
|
|
|
/*
|
|
* "a" is a 1D array of length ny*nx*N which constains the nx x ny
|
|
* matrix of N-tuples to be transposed. "a" is stored in row-major
|
|
* order (last index varies fastest). move is a 1D array of length
|
|
* move_size used to store information to speed up the process. The
|
|
* value move_size=(ny+nx)/2 is recommended. buf should be an array
|
|
* of length 2*N.
|
|
*
|
|
*/
|
|
|
|
static void transpose_toms513(R *a, INT nx, INT ny, INT N,
|
|
char *move, INT move_size, R *buf)
|
|
{
|
|
INT i, im, mn;
|
|
R *b, *c, *d;
|
|
INT ncount;
|
|
INT k;
|
|
|
|
/* check arguments and initialize: */
|
|
A(ny > 0 && nx > 0 && N > 0 && move_size > 0);
|
|
|
|
b = buf;
|
|
|
|
/* Cate & Twigg have a special case for nx == ny, but we don't
|
|
bother, since we already have special code for this case elsewhere. */
|
|
|
|
c = buf + N;
|
|
ncount = 2; /* always at least 2 fixed points */
|
|
k = (mn = ny * nx) - 1;
|
|
|
|
for (i = 0; i < move_size; ++i)
|
|
move[i] = 0;
|
|
|
|
if (ny >= 3 && nx >= 3)
|
|
ncount += gcd(ny - 1, nx - 1) - 1; /* # fixed points */
|
|
|
|
i = 1;
|
|
im = ny;
|
|
|
|
while (1) {
|
|
INT i1, i2, i1c, i2c;
|
|
INT kmi;
|
|
|
|
/** Rearrange the elements of a loop
|
|
and its companion loop: **/
|
|
|
|
i1 = i;
|
|
kmi = k - i;
|
|
i1c = kmi;
|
|
switch (N) {
|
|
case 1:
|
|
b[0] = a[i1];
|
|
c[0] = a[i1c];
|
|
break;
|
|
case 2:
|
|
b[0] = a[2*i1];
|
|
b[1] = a[2*i1+1];
|
|
c[0] = a[2*i1c];
|
|
c[1] = a[2*i1c+1];
|
|
break;
|
|
default:
|
|
memcpy(b, &a[N * i1], N * sizeof(R));
|
|
memcpy(c, &a[N * i1c], N * sizeof(R));
|
|
}
|
|
while (1) {
|
|
i2 = ny * i1 - k * (i1 / nx);
|
|
i2c = k - i2;
|
|
if (i1 < move_size)
|
|
move[i1] = 1;
|
|
if (i1c < move_size)
|
|
move[i1c] = 1;
|
|
ncount += 2;
|
|
if (i2 == i)
|
|
break;
|
|
if (i2 == kmi) {
|
|
d = b;
|
|
b = c;
|
|
c = d;
|
|
break;
|
|
}
|
|
switch (N) {
|
|
case 1:
|
|
a[i1] = a[i2];
|
|
a[i1c] = a[i2c];
|
|
break;
|
|
case 2:
|
|
a[2*i1] = a[2*i2];
|
|
a[2*i1+1] = a[2*i2+1];
|
|
a[2*i1c] = a[2*i2c];
|
|
a[2*i1c+1] = a[2*i2c+1];
|
|
break;
|
|
default:
|
|
memcpy(&a[N * i1], &a[N * i2],
|
|
N * sizeof(R));
|
|
memcpy(&a[N * i1c], &a[N * i2c],
|
|
N * sizeof(R));
|
|
}
|
|
i1 = i2;
|
|
i1c = i2c;
|
|
}
|
|
switch (N) {
|
|
case 1:
|
|
a[i1] = b[0];
|
|
a[i1c] = c[0];
|
|
break;
|
|
case 2:
|
|
a[2*i1] = b[0];
|
|
a[2*i1+1] = b[1];
|
|
a[2*i1c] = c[0];
|
|
a[2*i1c+1] = c[1];
|
|
break;
|
|
default:
|
|
memcpy(&a[N * i1], b, N * sizeof(R));
|
|
memcpy(&a[N * i1c], c, N * sizeof(R));
|
|
}
|
|
if (ncount >= mn)
|
|
break; /* we've moved all elements */
|
|
|
|
/** Search for loops to rearrange: **/
|
|
|
|
while (1) {
|
|
INT max = k - i;
|
|
++i;
|
|
A(i <= max);
|
|
im += ny;
|
|
if (im > k)
|
|
im -= k;
|
|
i2 = im;
|
|
if (i == i2)
|
|
continue;
|
|
if (i >= move_size) {
|
|
while (i2 > i && i2 < max) {
|
|
i1 = i2;
|
|
i2 = ny * i1 - k * (i1 / nx);
|
|
}
|
|
if (i2 == i)
|
|
break;
|
|
} else if (!move[i])
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
|
|
static void apply_toms513(const plan *ego_, R *I, R *O)
|
|
{
|
|
const P *ego = (const P *) ego_;
|
|
INT n = ego->n, m = ego->m;
|
|
INT vl = ego->vl;
|
|
R *buf = (R *)MALLOC(sizeof(R) * ego->nbuf, BUFFERS);
|
|
UNUSED(O);
|
|
transpose_toms513(I, n, m, vl, (char *) (buf + 2*vl), (n+m)/2, buf);
|
|
X(ifree)(buf);
|
|
}
|
|
|
|
static int applicable_toms513(const problem_rdft *p, planner *plnr,
|
|
int dim0, int dim1, int dim2, INT *nbuf)
|
|
{
|
|
INT n = p->vecsz->dims[dim0].n;
|
|
INT m = p->vecsz->dims[dim1].n;
|
|
INT vl, vs;
|
|
get_transpose_vec(p, dim2, &vl, &vs);
|
|
*nbuf = 2*vl
|
|
+ ((n + m) / 2 * sizeof(char) + sizeof(R) - 1) / sizeof(R);
|
|
return (!NO_SLOWP(plnr)
|
|
&& (vl > 8 || !NO_UGLYP(plnr)) /* UGLY for small vl */
|
|
&& n != m
|
|
&& Ntuple_transposable(p->vecsz->dims + dim0,
|
|
p->vecsz->dims + dim1,
|
|
vl, vs));
|
|
}
|
|
|
|
static int mkcldrn_toms513(const problem_rdft *p, planner *plnr, P *ego)
|
|
{
|
|
UNUSED(p); UNUSED(plnr);
|
|
/* heuristic so that TOMS algorithm is last resort for small vl */
|
|
ego->super.super.ops.other += ego->n * ego->m * 2 * (ego->vl + 30);
|
|
return 1;
|
|
}
|
|
|
|
static const transpose_adt adt_toms513 =
|
|
{
|
|
apply_toms513, applicable_toms513, mkcldrn_toms513,
|
|
"rdft-transpose-toms513"
|
|
};
|
|
|
|
/*-----------------------------------------------------------------------*/
|
|
/*-----------------------------------------------------------------------*/
|
|
/* generic stuff: */
|
|
|
|
static void awake(plan *ego_, enum wakefulness wakefulness)
|
|
{
|
|
P *ego = (P *) ego_;
|
|
X(plan_awake)(ego->cld1, wakefulness);
|
|
X(plan_awake)(ego->cld2, wakefulness);
|
|
X(plan_awake)(ego->cld3, wakefulness);
|
|
}
|
|
|
|
static void print(const plan *ego_, printer *p)
|
|
{
|
|
const P *ego = (const P *) ego_;
|
|
p->print(p, "(%s-%Dx%D%v", ego->slv->adt->nam,
|
|
ego->n, ego->m, ego->vl);
|
|
if (ego->cld1) p->print(p, "%(%p%)", ego->cld1);
|
|
if (ego->cld2) p->print(p, "%(%p%)", ego->cld2);
|
|
if (ego->cld3) p->print(p, "%(%p%)", ego->cld3);
|
|
p->print(p, ")");
|
|
}
|
|
|
|
static void destroy(plan *ego_)
|
|
{
|
|
P *ego = (P *) ego_;
|
|
X(plan_destroy_internal)(ego->cld3);
|
|
X(plan_destroy_internal)(ego->cld2);
|
|
X(plan_destroy_internal)(ego->cld1);
|
|
}
|
|
|
|
static plan *mkplan(const solver *ego_, const problem *p_, planner *plnr)
|
|
{
|
|
const S *ego = (const S *) ego_;
|
|
const problem_rdft *p;
|
|
int dim0, dim1, dim2;
|
|
INT nbuf, vs;
|
|
P *pln;
|
|
|
|
static const plan_adt padt = {
|
|
X(rdft_solve), awake, print, destroy
|
|
};
|
|
|
|
if (!applicable(ego_, p_, plnr, &dim0, &dim1, &dim2, &nbuf))
|
|
return (plan *) 0;
|
|
|
|
p = (const problem_rdft *) p_;
|
|
pln = MKPLAN_RDFT(P, &padt, ego->adt->apply);
|
|
|
|
pln->n = p->vecsz->dims[dim0].n;
|
|
pln->m = p->vecsz->dims[dim1].n;
|
|
get_transpose_vec(p, dim2, &pln->vl, &vs);
|
|
pln->nbuf = nbuf;
|
|
pln->d = gcd(pln->n, pln->m);
|
|
pln->nd = pln->n / pln->d;
|
|
pln->md = pln->m / pln->d;
|
|
pln->slv = ego;
|
|
|
|
X(ops_zero)(&pln->super.super.ops); /* mkcldrn is responsible for ops */
|
|
|
|
pln->cld1 = pln->cld2 = pln->cld3 = 0;
|
|
if (!ego->adt->mkcldrn(p, plnr, pln)) {
|
|
X(plan_destroy_internal)(&(pln->super.super));
|
|
return 0;
|
|
}
|
|
|
|
return &(pln->super.super);
|
|
}
|
|
|
|
static solver *mksolver(const transpose_adt *adt)
|
|
{
|
|
static const solver_adt sadt = { PROBLEM_RDFT, mkplan, 0 };
|
|
S *slv = MKSOLVER(S, &sadt);
|
|
slv->adt = adt;
|
|
return &(slv->super);
|
|
}
|
|
|
|
void X(rdft_vrank3_transpose_register)(planner *p)
|
|
{
|
|
unsigned i;
|
|
static const transpose_adt *const adts[] = {
|
|
&adt_gcd, &adt_cut,
|
|
&adt_toms513
|
|
};
|
|
for (i = 0; i < sizeof(adts) / sizeof(adts[0]); ++i)
|
|
REGISTER_SOLVER(p, mksolver(adts[i]));
|
|
}
|