pastix_subtask_blend.c

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/**
 *
 * @file pastix_subtask_blend.c
 *
 * PaStiX analyse blend subtask function
 *
 * @copyright 2004-2021 Bordeaux INP, CNRS (LaBRI UMR 5800), Inria,
 *                      Univ. Bordeaux. All rights reserved.
 *
 * @version 6.2.1
 * @author Pascal Henon
 * @author Xavier Lacoste
 * @author Pierre Ramet
 * @author Mathieu Faverge
 * @author Gregoire Pichon
 * @author Tony Delarue
 * @date 2021-07-01
 *
 **/
#include "common.h"
#include <spm.h>
#include "graph/graph.h"
#include "order/order_internal.h"
#include "blend/perf.h"
#include "blend/elimintree.h"
#include "blend/cost.h"
#include "blend/cand.h"
#include "blend/extendVector.h"
#include "blendctrl.h"
#include "blend/solver.h"
#include "blend/simu.h"
#include "blend/blend.h"
 
/**
 *******************************************************************************
 *
 * @ingroup pastix_analyze
 *
 * @brief Compute the proportional mapping and the final solver structure.
 *
 * This function computes the structural information required to factorize
 * and solve the problem. It requires an ordering structure, as well as the
 * symbolic factorization structure. It computes a solver structure that contains
 * all informations, architecture and problem dependent, to efficiently solve the
 * system.
 * On exit, the symbol structure is destroyed and only local uncompressed
 * information is stored in the solver structure.
 *
 * This routine is affected by, or returns, the following parameters:
 *   IPARM_CUDA_NBR, IPARM_TASKS2D_LEVEL, IPARM_TASKS2D_WIDTH,
 *   IPARM_COMPRESS_WHEN, IPARM_COMPRESS_MIN_WIDTH, IPARM_DOF_NBR,
 *   IPARM_FACTORIZATION, IPARM_FLOAT, IPARM_GPU_CRITERIUM,
 *   IPARM_GPU_MEMORY_PERCENTAGE, IPARM_GPU_NBR, IPARM_INCOMPLETE,
 *   IPARM_MAX_BLOCKSIZE, IPARM_MIN_BLOCKSIZE, IPARM_NNZEROS,
 *   IPARM_NNZEROS_BLOCK_LOCAL, IPARM_STARPU, IPARM_THREAD_NBR, IPARM_VERBOSE
 *
 *   DPARM_BLEND_TIME, DPARM_FACT_FLOPS, DPARM_FACT_RLFLOPS,
 *   DPARM_FACT_THFLOPS, DPARM_FILL_IN, DPARM_PRED_FACT_TIME, DPARM_SOLV_FLOPS
 *
 * This function is constructed as a sequence of steps that are described below.
 *
 * #### Construct an elimination tree
 *   A elimination tree structure is constructed out of the symbol matrix to be
 *   able to traverse the tree in a top-down fashion for the proportionnal
 *   mapping step.
 *
 * #### Construct the cost matrix
 *   For each column-block, and block of the symbolic structure, the cost of
 *   each operation is computed to evaluate the cost of each branch of the
 *   elimination tree. Costs of the blocks are the cost of the update generated
 *   out of this block when used as the B matrix in the GEMM update. Costs of
 *   the column block is the total cost associated to it: factorization, solve,
 *   and update in a right-looking algorithm. This means that the update cost is
 *   the one generated by this column block, and not the one received by the
 *   column-block.
 *
 * #### Construct the candidate array
 *   Dispatch properties such as low-rank compression, 2D tasks from the top to
 *   the bottom of the tree. Candidate array, and elimination tree are computed,
 *   and updated, simultaneously with the costs computed previously.
 *   This step is impacted by IPARM_TASKS2D_LEVEL and IPARM_TASKS2D_WIDTH that
 *   defines the minimal width of nodes which can forward 2D tasks property to
 *   their sons.
 *   Similarly, IPARM_COMPRESS_WHEN and IPARM_COMPRESS_MIN_WIDTH defines the
 *   minimal width of nodes which can forward low-rank property to their sons.
 *
 * #### Proportionnal Mapping
 *   This step performs the actual proportional mapping algorithm to define the
 *   subset of candidates to compute each supernode.
 *
 * #### Split symbol matrix
 *   Once the proportionnal mapping is performed on the original set of
 *   supernodes, the symbol matrix is split in smaller supernodes/blocks to
 *   allow for more parallelism.
 *
 * #### Simulation
 *   The simulation step defines the actual mapping per core of each supernode
 *   based on a simulation of the numerical factorization where each task is
 *   attributed to the first resource available to compute it.
 *
 * #### Solver structure generation
 *   Out of the previous step, the solver generator builds the local structure
 *   that is required for the numerical factorization and solve steps. It is
 *   mainly represented by a CSC like structure of the local blocks, linked to a
 *   CSR for the solve step and the structure that will holds the coefficients
 *   of the factorized matrix.
 *
 *******************************************************************************
 *
 * @param[inout] pastix_data
 *          The pastix_data structure that describes the solver instance.
 *
 *******************************************************************************
 *
 * @retval PASTIX_SUCCESS on successful exit
 * @retval PASTIX_ERR_BADPARAMETER if one parameter is incorrect.
 * @retval PASTIX_ERR_OUTOFMEMORY if one allocation failed.
 *
 *******************************************************************************/
int
pastix_subtask_blend( pastix_data_t *pastix_data )
{
    BlendCtrl        ctrl;
    pastix_int_t     procnum, verbose;
    pastix_int_t    *iparm;
    double          *dparm;
    pastix_order_t  *ordeptr;
    symbol_matrix_t *symbmtx;
    SolverMatrix    *solvmtx_loc;
    SolverMatrix    *solvmtx_glob;
    SimuCtrl        *simuctrl;
    double           timer_all     = 0.;
    double           timer_current = 0.;
 
    /*
     * Check parameters
     */
    if (pastix_data == NULL) {
        pastix_print_error( "pastix_subtask_blend: wrong pastix_data parameter" );
        return PASTIX_ERR_BADPARAMETER;
    }
    if ( !(pastix_data->steps & STEP_SYMBFACT) ) {
        pastix_print_error( "pastix_subtask_blend: pastix_subtask_symbfact() has to be called before calling this function" );
        return PASTIX_ERR_BADPARAMETER;
    }
 
    iparm   = pastix_data->iparm;
    dparm   = pastix_data->dparm;
    procnum = pastix_data->inter_node_procnum;
    ordeptr = pastix_data->ordemesh;
    symbmtx = pastix_data->symbmtx;
    verbose = iparm[IPARM_VERBOSE];
 
    if (ordeptr == NULL) {
        pastix_print_error( "pastix_subtask_blend: the pastix_data->ordemesh field has not been initialized, pastix_task_order should be called first" );
        return PASTIX_ERR_BADPARAMETER;
    }
    if (symbmtx == NULL) {
        pastix_print_error( "pastix_subtask_blend: the pastix_data->symbmtx has not been initialized, pastix_task_symbfact should be called first" );
        return PASTIX_ERR_BADPARAMETER;
    }
    if (symbmtx->dof < 1) {
        pastix_print_error( "pastix_subtask_blend: Dof number has not been correctly initialized" );
        return PASTIX_ERR_BADPARAMETER;
    }
 
    /* Free graph structure, we don't need it anymore */
    if ( pastix_data->graph != NULL ) {
        graphExit( pastix_data->graph );
        memFree_null( pastix_data->graph );
    }
 
    /* Cleanup the solver structure if we already computed it */
    if ( pastix_data->solvmatr != NULL ) {
        solverExit( pastix_data->solvmatr );
        memFree_null( pastix_data->solvmatr );
    }
    if ( pastix_data->solvglob != NULL ) {
        solverExit( pastix_data->solvglob );
        memFree_null( pastix_data->solvglob );
    }
 
    solvmtx_loc  = (SolverMatrix*)malloc(sizeof(SolverMatrix));
    solvmtx_glob = (SolverMatrix*)malloc(sizeof(SolverMatrix));
    pastix_data->solvloc  = solvmtx_loc;
    pastix_data->solvglob = solvmtx_glob;
 
    /* The problem is more likely to be solved by the local problem, may change later */
    pastix_data->solvmatr = pastix_data->solvloc;
 
    /* Start the analyze step */
    clockStart(timer_all);
    if ( verbose > PastixVerboseNot ) {
        pastix_print( procnum, 0, OUT_STEP_BLEND );
    }
 
    /* Create the control structure that parameterize the analyze step */
    blendCtrlInit( pastix_data, &ctrl );
 
    if( verbose > PastixVerboseNo) {
        pastix_print( procnum, 0, OUT_BLEND_CONF,
                      (long)ctrl.clustnbr, (long)ctrl.local_nbcores, (long)ctrl.local_nbthrds);
    }
 
    /* Prepare the directories for the output files if needed */
    if ( verbose > PastixVerboseYes ) {
        pastix_gendirectories( pastix_data );
    }
 
    /* Verify the coherence of the initial symbol matrix */
    if(ctrl.debug)
    {
        if( verbose > PastixVerboseYes ) {
            pastix_print( procnum, 0, OUT_BLEND_CHKSMBMTX );
        }
        pastixSymbolCheck(symbmtx);
    }
 
#if defined(PASTIX_ORDER_DRAW_LASTSEP)
    /*
     * Draw last separator before split
     */
    if ( iparm[IPARM_SPLITTING_STRATEGY] == PastixSplitKwayProjections ) {
        pastixSymbolDrawMap( pastix_data, "bsplit", ordeptr->sndenbr-1 );
    }
#endif
 
#if !defined(PASTIX_BLEND_PROPMAP_2STEPS)
    /*
     * Split the existing symbol matrix according to the number of candidates
     * and cblk types.
     * It takes the original symbol and candtab, and returns the new symbol and
     * candtab. If the symbmtx is modified, the costmtx is updated, as well as
     * the tree.
     */
    {
        if( verbose > PastixVerboseYes ) {
            pastix_print( procnum, 0, OUT_BLEND_SPLITSYMB );
        }
        clockStart(timer_current);
 
        splitSymbol(&ctrl, symbmtx);
 
        clockStop(timer_current);
        if( verbose > PastixVerboseNo ) {
            pastix_print( procnum, 0, OUT_BLEND_SPLITSYMB_TIME,
                          clockVal(timer_current) );
        }
    }
#if defined(PASTIX_ORDER_DRAW_LASTSEP)
    /*
     * Draw last separator after split
     */
    pastixSymbolDrawMap( pastix_data, "asplit", ordeptr->sndenbr-1 );
#endif
#endif
 
    /* Build the elimination tree from the symbolic partition */
    {
        if( verbose > PastixVerboseYes) {
            pastix_print( procnum, 0, OUT_BLEND_ELIMTREE );
        }
        clockStart(timer_current);
 
        ctrl.etree = eTreeBuild(symbmtx);
 
        clockStop(timer_current);
        if( verbose > PastixVerboseNo ) {
            pastix_print( procnum, 0, OUT_BLEND_ELIMTREE_TIME,
                          clockVal(timer_current) );
        }
    }
 
    /* Build the cost matrix from the symbolic partition */
    {
        if( verbose > PastixVerboseYes ) {
            pastix_print( procnum, 0, OUT_BLEND_COSTMATRIX );
        }
        clockStart(timer_current);
 
        ctrl.costmtx = costMatrixBuild( symbmtx,
                                        iparm[IPARM_FLOAT],
                                        iparm[IPARM_FACTORIZATION] );
 
        clockStop(timer_current);
        if( verbose > PastixVerboseNo ) {
            pastix_print( procnum, 0, OUT_BLEND_COSTMATRIX_TIME,
                          clockVal(timer_current) );
        }
    }
 
    /* Build the candtab array to store candidate information on each cblk */
    {
        ctrl.candtab = candInit( symbmtx->cblknbr );
 
        /* Initialize costs in elimination tree and candtab array for proportionnal mapping */
        candBuild( ctrl.level_tasks2d, ctrl.width_tasks2d,
                   iparm[IPARM_COMPRESS_WHEN], iparm[IPARM_COMPRESS_MIN_WIDTH],
                   ctrl.candtab,
                   ctrl.etree,
                   symbmtx,
                   ctrl.costmtx );
 
        if( verbose > PastixVerboseNo ) {
            pastix_print( procnum, 0, OUT_BLEND_ELIMTREE_TOTAL_COST,
                          ctrl.etree->nodetab[ eTreeRoot(ctrl.etree) ].subcost,
                          ctrl.etree->nodetab[ eTreeRoot(ctrl.etree) ].subpath );
        }
    }
 
    /* Proportional mapping step that distributes the candidates over the tree */
    {
        if( verbose > PastixVerboseYes ) {
            pastix_print( procnum, 0, OUT_BLEND_PROPMAP );
        }
        clockStart(timer_current);
 
        propMappTree( ctrl.candtab,
                      ctrl.etree,
                      ctrl.total_nbcores,
                      ctrl.nocrossproc,
                      ctrl.allcand );
 
        /* Set the cluster candidates according to the processor candidates */
        candSetClusterCand( ctrl.candtab, symbmtx->cblknbr,
                            ctrl.core2clust, ctrl.total_nbcores );
 
        clockStop(timer_current);
 
        if( verbose > PastixVerboseNo ) {
            pastix_print( procnum, 0, OUT_BLEND_PROPMAP_TIME,
                          clockVal(timer_current) );
        }
 
        /* Let's check the result if ask */
        if ( ctrl.debug ) {
            assert( candCheck( ctrl.candtab, symbmtx ) );
        }
    }
 
#if defined(PASTIX_BLEND_PROPMAP_2STEPS)
    /* Dump the dot of the eTree before split */
    if (( verbose > PastixVerboseYes ) &&
        ( pastix_data->procnum == 0 ) )
    {
        FILE *stream = NULL;
        stream = pastix_fopenw( pastix_data->dir_global, "etree.dot", "w" );
        if ( stream ) {
            candGenDotLevel( ctrl.etree, ctrl.candtab, stream, 5);
            fclose(stream);
        }
 
        stream = pastix_fopenw( pastix_data->dir_global, "ctree.dot", "w" );
        if ( stream ) {
            candGenCompressedDot( ctrl.etree, ctrl.candtab, stream );
            fclose(stream);
        }
    }
 
    /*
     * Split the existing symbol matrix according to the number of candidates
     * and cblk types.
     * It takes the original symbol and candtab, and returns the new symbol and
     * candtab. If the symbmtx is modified, the costmtx is updated, as well as
     * the tree.
     */
    {
        if( verbose > PastixVerboseYes ) {
            pastix_print( procnum, 0, OUT_BLEND_SPLITSYMB );
        }
        clockStart(timer_current);
 
        ctrl.up_after_split = 1;
        splitSymbol(&ctrl, symbmtx);
        ctrl.up_after_split = 0;
 
        clockStop(timer_current);
        if( verbose > PastixVerboseNo ) {
            pastix_print( procnum, 0, OUT_BLEND_SPLITSYMB_TIME,
                          clockVal(timer_current) );
        }
    }
 
    /* Dump the dot of the eTree after split */
    if (( verbose > PastixVerboseYes ) &&
        ( pastix_data->procnum == 0 ) )
    {
        FILE *stream = NULL;
        stream = pastix_fopenw( pastix_data->dir_global, "etree_split.dot", "w" );
        if ( stream ) {
            candGenDot( ctrl.etree, ctrl.candtab, stream );
            fclose(stream);
        }
 
        stream = pastix_fopenw( pastix_data->dir_global, "ctree_split.dot", "w" );
        if ( stream ) {
            candGenCompressedDot( ctrl.etree, ctrl.candtab, stream );
            fclose(stream);
        }
    }
#endif
 
    if(ctrl.count_ops && (ctrl.leader == procnum)) {
        pastixSymbolGetFlops( symbmtx,
                              iparm[IPARM_FLOAT],
                              iparm[IPARM_FACTORIZATION],
                              &(dparm[DPARM_FACT_THFLOPS]),
                              &(dparm[DPARM_FACT_RLFLOPS]) );
    }
 
#if defined(PASTIX_SYMBOL_DUMP_SYMBMTX)
    {
        FILE *stream = NULL;
        pastix_gendirectories( pastix_data );
        stream = pastix_fopenw( pastix_data->dir_global, "symbol_after_split.eps", "w" );
        if ( stream ) {
            pastixSymbolDraw( symbmtx, stream );
            fclose( stream );
        }
    }
#endif
 
    if (0)
    {
        FILE *file = NULL;
        pastix_gendirectories( pastix_data );
        file = pastix_fopenw( pastix_data->dir_global, "symbol_after_split", "w" );
        if ( file ) {
            pastixSymbolSave( symbmtx, file );
            fclose( file );
        }
    }
 
    /* Simulation step to perform the data distribution over the nodes and compute the priorities of each task */
    {
        if( verbose > PastixVerboseYes ) {
            pastix_print( procnum, 0, OUT_BLEND_BUILDSIMU );
        }
        clockStart(timer_current);
 
        /* Initialize simulation structure */
        MALLOC_INTERN(simuctrl, 1, SimuCtrl);
        simuInit( simuctrl, symbmtx, ctrl.candtab,
                  ctrl.clustnbr,
                  ctrl.total_nbcores );
 
        /* Create task array */
        simuTaskBuild( simuctrl, symbmtx );
        clockStop(timer_current);
 
        if( verbose > PastixVerboseNo ) {
            pastix_print( procnum, 0, OUT_BLEND_BUILDSIMU_TIME,
                          clockVal(timer_current),
                          (long)simuctrl->tasknbr );
        }
 
        if( verbose > PastixVerboseYes ) {
            pastix_print( procnum, 0, OUT_BLEND_SIMU );
        }
        clockStart(timer_current);
 
        simuRun( simuctrl, &ctrl, symbmtx );
 
        clockStop(timer_current);
        if( verbose > PastixVerboseNo ) {
            pastix_print( procnum, 0, OUT_BLEND_SIMU_TIME,
                          clockVal(timer_current) );
        }
    }
 
#ifdef PASTIX_DYNSCHED
    /**
     * If dynamic scheduling is asked, let's perform a second proportionnal
     * mapping step:
     *    - this is made only on local data
     *    - no crossing is allowed between branches
     */
    {
        clockStart(timer_current);
 
        splitPartLocal( &ctrl, simuctrl, symbmtx );
 
        clockStop(timer_current);
        if( verbose>PastixVerboseNo)
            pastix_print( procnum, 0, "  -- Split build at time: %g --\n", clockVal(timer_current));
    }
#endif
 
    /* CostMatrix and Elimination Tree are no further used */
    costMatrixExit( ctrl.costmtx );
    memFree_null( ctrl.costmtx );
    eTreeExit( ctrl.etree );
 
    /**
     * Generate the final solver structure that collects data from the different
     * simulation structures and convert to local numbering
     */
    {
        if( verbose > PastixVerboseYes ) {
            pastix_print( procnum, 0, OUT_BLEND_SOLVER );
        }
        clockStart(timer_current);
 
        solverMatrixGenSeq( solvmtx_glob, symbmtx,
                            pastix_data->ordemesh, simuctrl, &ctrl,
                            pastix_data->inter_node_comm, pastix_data->isched, 0 );
 
        solverMatrixGen( solvmtx_loc, symbmtx,
                         pastix_data->ordemesh, simuctrl, &ctrl,
                         pastix_data->inter_node_comm, pastix_data->isched );
 
        clockStop(timer_current);
        if( verbose > PastixVerboseNo ) {
            pastix_print( procnum, 0, OUT_BLEND_SOLVER_TIME,
                          clockVal(timer_current) );
            if( verbose > PastixVerboseYes ) {
                solverPrintStats( solvmtx_loc );
            }
        }
    }
 
    /* Free allocated memory */
    simuExit(simuctrl, ctrl.clustnbr, ctrl.total_nbcores, ctrl.local_nbctxts);
 
    /* Realloc solver memory in a contiguous way  */
    {
        solverRealloc(solvmtx_loc);
        solverRealloc(solvmtx_glob);
#if defined(PASTIX_DEBUG_BLEND)
        if (!ctrl.ricar) {
            if( verbose > PastixVerboseYes ) {
                pastix_print( procnum, 0, OUT_BLEND_CHKSOLVER );
            }
            solverCheck(solvmtx_loc);
            solverCheck(solvmtx_glob);
        }
#endif
    }
 
    blendCtrlExit(&ctrl);
 
    /* End timing */
    clockStop(timer_all);
    pastix_data->dparm[DPARM_BLEND_TIME] = clockVal(timer_all);
 
    if (verbose > PastixVerboseYes) {
        pastixSymbolPrintStats( pastix_data->symbmtx );
    }
 
    /* Symbol is not used anymore */
    pastixSymbolExit(pastix_data->symbmtx);
    memFree_null(pastix_data->symbmtx);
 
    /* Computes and print statistics */
    {
        if (iparm[IPARM_FACTORIZATION] == PastixFactLU)
        {
            iparm[IPARM_NNZEROS]        *= 2;
            dparm[DPARM_PRED_FACT_TIME] *= 2.;
        }
        dparm[DPARM_SOLV_FLOPS] = (double)iparm[IPARM_NNZEROS]; /* number of operations for solve */
 
        iparm[IPARM_NNZEROS_BLOCK_LOCAL] = solvmtx_loc->coefnbr;
 
        /* Affichage */
        dparm[DPARM_FILL_IN] = (double)(iparm[IPARM_NNZEROS]) / (double)(pastix_data->csc->gnnzexp);
 
        if (verbose > PastixVerboseNot) {
            pastix_print( procnum, 0, OUT_BLEND_SUMMARY,
                          (long)iparm[IPARM_NNZEROS],
                          (double)dparm[DPARM_FILL_IN],
                          pastixFactotypeStr( iparm[IPARM_FACTORIZATION] ),
                          pastix_print_value( dparm[DPARM_FACT_THFLOPS] ),
                          pastix_print_unit( dparm[DPARM_FACT_THFLOPS] ),
                          PERF_MODEL, dparm[DPARM_PRED_FACT_TIME],
                          dparm[DPARM_BLEND_TIME] );
 
            if (0) /* TODO: consider that when moving to distributed */
            {
                if ((verbose > PastixVerboseNo))
                {
                    fprintf(stdout, NNZERO_WITH_FILLIN, (int)procnum, (long)iparm[IPARM_NNZEROS_BLOCK_LOCAL]);
                }
                if (verbose > PastixVerboseYes)
                {
                    PASTIX_Comm  pastix_comm = pastix_data->inter_node_comm;
                    pastix_int_t sizeL = solvmtx_loc->coefnbr;
                    pastix_int_t sizeG = 0;
 
                    MPI_Reduce(&sizeL, &sizeG, 1, PASTIX_MPI_INT, MPI_MAX, 0, pastix_comm);
 
                    if (procnum == 0)
                    {
                        sizeG *= sizeof(pastix_complex64_t);
                        if (iparm[IPARM_FACTORIZATION] == PastixFactLU) {
                            sizeG *= 2;
                        }
 
                        fprintf( stdout, OUT_COEFSIZE,
                                 pastix_print_value(sizeG),
                                 pastix_print_unit(sizeG) );
                    }
                }
            }
        }
    }
 
    /* Backup the solver for debug */
    if (0)
    {
        FILE *file = NULL;
        pastix_gendirectories( pastix_data );
        file = pastix_fopenw( pastix_data->dir_global, "solvergen", "w" );
        if ( file ) {
            solverSave( solvmtx_loc, file );
            fclose(file);
        }
    }
 
    /* Invalidate following steps, and add analyze step to the ones performed */
    pastix_data->steps &= ~( STEP_CSC2BCSC  |
                             STEP_BCSC2CTAB |
                             STEP_NUMFACT   |
                             STEP_SOLVE     |
                             STEP_REFINE    );
    pastix_data->steps |= STEP_ANALYSE;
 
    return PASTIX_SUCCESS;
}