Examples with PDataPartitioner org.apache.sysml.runtime.controlprogram.ParForProgramBlock.PDataPartitioner used on opensource projects

Example 1 with PDataPartitioner

use of org.apache.sysml.runtime.controlprogram.ParForProgramBlock.PDataPartitioner in project incubator-systemml by apache.

the class OptimizerRuleBased method rewriteSetExecutionStategy.

///////
//REWRITE set execution strategy
///
protected boolean rewriteSetExecutionStategy(OptNode n, double M0, double M, double M2, double M3, boolean flagLIX) throws DMLRuntimeException {
    boolean isCPOnly = n.isCPOnly();
    boolean isCPOnlyPossible = isCPOnly || isCPOnlyPossible(n, _rm);
    String datapartitioner = n.getParam(ParamType.DATA_PARTITIONER);
    ExecType REMOTE = getRemoteExecType();
    PDataPartitioner REMOTE_DP = OptimizerUtils.isSparkExecutionMode() ? PDataPartitioner.REMOTE_SPARK : PDataPartitioner.REMOTE_MR;
    //deciding on the execution strategy
    if (//allowed remote parfor execution
    ConfigurationManager.isParallelParFor() && (//Required: all inst already in cp and fit in remote mem
    (isCPOnly && M <= _rm) || //Required: all inst already in cp and fit partitioned in remote mem
    (isCPOnly && M3 <= _rm) || //Required: all inst forced to cp fit in remote mem
    (isCPOnlyPossible && M2 <= _rm))) {
        //at this point all required conditions for REMOTE_MR given, now its an opt decision
        //estimated local exploited par  
        int cpk = (int) Math.min(_lk, Math.floor(_lm / M));
        //(the factor of 2 is to account for hyper-threading and in order prevent too eager remote parfor)
        if (//incl conditional partitioning
        2 * cpk < _lk && 2 * cpk < _N && 2 * cpk < _rk) {
            //remote parfor
            n.setExecType(REMOTE);
        } else //MR if problem is large enough and remote parallelism is larger than local   
        if (_lk < _N && _lk < _rk && M <= _rm && isLargeProblem(n, M0)) {
            //remote parfor
            n.setExecType(REMOTE);
        } else //MR if MR operations in local, but CP only in remote (less overall MR jobs)
        if (!isCPOnly && isCPOnlyPossible) {
            //remote parfor
            n.setExecType(REMOTE);
        } else //MR if necessary for LIX rewrite (LIX true iff cp only and rm valid)
        if (flagLIX) {
            //remote parfor
            n.setExecType(REMOTE);
        } else //MR if remote data partitioning, because data will be distributed on all nodes 
        if (datapartitioner != null && datapartitioner.equals(REMOTE_DP.toString()) && !InfrastructureAnalyzer.isLocalMode()) {
            //remote parfor
            n.setExecType(REMOTE);
        } else //otherwise CP
        {
            //local parfor	
            n.setExecType(ExecType.CP);
        }
    } else //mr instructions in body, or rm too small
    {
        //local parfor
        n.setExecType(ExecType.CP);
    }
    //actual programblock modification
    long id = n.getID();
    ParForProgramBlock pfpb = (ParForProgramBlock) OptTreeConverter.getAbstractPlanMapping().getMappedProg(id)[1];
    PExecMode mode = n.getExecType().toParForExecMode();
    pfpb.setExecMode(mode);
    //decide if recompilation according to remote mem budget necessary
    boolean requiresRecompile = ((mode == PExecMode.REMOTE_MR || mode == PExecMode.REMOTE_SPARK) && !isCPOnly);
    _numEvaluatedPlans++;
    LOG.debug(getOptMode() + " OPT: rewrite 'set execution strategy' - result=" + mode + " (recompile=" + requiresRecompile + ")");
    return requiresRecompile;
}

Example 2 with PDataPartitioner

use of org.apache.sysml.runtime.controlprogram.ParForProgramBlock.PDataPartitioner in project incubator-systemml by apache.

the class OptimizerRuleBased method rewriteSetDataPartitioner.

///////
//REWRITE set data partitioner
///
protected boolean rewriteSetDataPartitioner(OptNode n, LocalVariableMap vars, HashMap<String, PartitionFormat> partitionedMatrices, double thetaM) throws DMLRuntimeException {
    if (n.getNodeType() != NodeType.PARFOR)
        LOG.warn(getOptMode() + " OPT: Data partitioner can only be set for a ParFor node.");
    boolean blockwise = false;
    //preparations
    long id = n.getID();
    Object[] o = OptTreeConverter.getAbstractPlanMapping().getMappedProg(id);
    ParForStatementBlock pfsb = (ParForStatementBlock) o[0];
    ParForProgramBlock pfpb = (ParForProgramBlock) o[1];
    //search for candidates
    boolean apply = false;
    if (//only if we are allowed to recompile
    OptimizerUtils.isHybridExecutionMode() && //only if beneficial wrt problem size
    (_N >= PROB_SIZE_THRESHOLD_PARTITIONING || _Nmax >= PROB_SIZE_THRESHOLD_PARTITIONING)) {
        ArrayList<String> cand = pfsb.getReadOnlyParentVars();
        HashMap<String, PartitionFormat> cand2 = new HashMap<String, PartitionFormat>();
        for (String c : cand) {
            PartitionFormat dpf = pfsb.determineDataPartitionFormat(c);
            if (dpf != PartitionFormat.NONE && dpf._dpf != PDataPartitionFormat.BLOCK_WISE_M_N) {
                cand2.put(c, dpf);
            }
        }
        apply = rFindDataPartitioningCandidates(n, cand2, vars, thetaM);
        if (apply)
            partitionedMatrices.putAll(cand2);
    }
    PDataPartitioner REMOTE = OptimizerUtils.isSparkExecutionMode() ? PDataPartitioner.REMOTE_SPARK : PDataPartitioner.REMOTE_MR;
    PDataPartitioner pdp = (apply) ? REMOTE : PDataPartitioner.NONE;
    //NOTE: since partitioning is only applied in case of MR index access, we assume a large
    //      matrix and hence always apply REMOTE_MR (the benefit for large matrices outweigths
    //      potentially unnecessary MR jobs for smaller matrices)
    // modify rtprog 
    pfpb.setDataPartitioner(pdp);
    // modify plan
    n.addParam(ParamType.DATA_PARTITIONER, pdp.toString());
    _numEvaluatedPlans++;
    LOG.debug(getOptMode() + " OPT: rewrite 'set data partitioner' - result=" + pdp.toString() + " (" + ProgramConverter.serializeStringCollection(partitionedMatrices.keySet()) + ")");
    return blockwise;
}

Example 3 with PDataPartitioner

use of org.apache.sysml.runtime.controlprogram.ParForProgramBlock.PDataPartitioner in project incubator-systemml by apache.

the class OptimizerRuleBased method rewriteSetFusedDataPartitioningExecution.

///////
//REWRITE set fused data partitioning / execution
///
/**
	 * This dedicated execution mode can only be applied if all of the 
	 * following conditions are true:
	 * - Only cp instructions in the parfor body
	 * - Only one partitioned input 
	 * - number of iterations is equal to number of partitions (nrow/ncol)
	 * - partitioned matrix access via plain iteration variables (no composed expressions)
	 *   (this ensures that each partition is exactly read once)
	 * - no left indexing (since by default static task partitioning)
	 * 
	 * Furthermore, it should be only chosen if we already decided for remote partitioning
	 * and otherwise would create a large number of partition files.
	 * 
	 * NOTE: We already respect the reducer memory budget for plan correctness. However,
	 * we miss optimization potential if the reducer budget is larger than the mapper budget
	 * (if we were not able to select REMOTE_MR as execution strategy wrt mapper budget)
	 * TODO modify 'set exec strategy' and related rewrites for conditional data partitioning.
	 * 
	 * @param pn internal representation of a plan alternative for program blocks and instructions
	 * @param M ?
	 * @param flagLIX ?
	 * @param partitionedMatrices map of data partition formats
	 * @param vars local variable map
	 * @throws DMLRuntimeException if DMLRuntimeException occurs
	 */
protected void rewriteSetFusedDataPartitioningExecution(OptNode pn, double M, boolean flagLIX, HashMap<String, PartitionFormat> partitionedMatrices, LocalVariableMap vars) throws DMLRuntimeException {
    //assertions (warnings of corrupt optimizer decisions)
    if (pn.getNodeType() != NodeType.PARFOR)
        LOG.warn(getOptMode() + " OPT: Fused data partitioning and execution is only applicable for a ParFor node.");
    boolean apply = false;
    String partitioner = pn.getParam(ParamType.DATA_PARTITIONER);
    PDataPartitioner REMOTE_DP = OptimizerUtils.isSparkExecutionMode() ? PDataPartitioner.REMOTE_SPARK : PDataPartitioner.REMOTE_MR;
    PExecMode REMOTE_DPE = OptimizerUtils.isSparkExecutionMode() ? PExecMode.REMOTE_SPARK_DP : PExecMode.REMOTE_MR_DP;
    // try to merge MR data partitioning and MR exec 
    if ((//fits into remote memory of reducers
    pn.getExecType() == ExecType.MR && M < _rm2 || //MR/SP EXEC and CP body
    pn.getExecType() == ExecType.SPARK) && partitioner != null && //MR/SP partitioning
    partitioner.equals(REMOTE_DP.toString()) && //only one partitioned matrix
    partitionedMatrices.size() == 1) {
        ParForProgramBlock pfpb = (ParForProgramBlock) OptTreeConverter.getAbstractPlanMapping().getMappedProg(pn.getID())[1];
        //partitioned matrix
        String moVarname = partitionedMatrices.keySet().iterator().next();
        PartitionFormat moDpf = partitionedMatrices.get(moVarname);
        MatrixObject mo = (MatrixObject) vars.get(moVarname);
        //check if access via iteration variable and sizes match
        String iterVarname = pfpb.getIterablePredicateVars()[0];
        if (rIsAccessByIterationVariable(pn, moVarname, iterVarname) && ((moDpf == PartitionFormat.ROW_WISE && mo.getNumRows() == _N) || (moDpf == PartitionFormat.COLUMN_WISE && mo.getNumColumns() == _N) || (moDpf._dpf == PDataPartitionFormat.ROW_BLOCK_WISE_N && mo.getNumRows() <= _N * moDpf._N) || (moDpf._dpf == PDataPartitionFormat.COLUMN_BLOCK_WISE_N && mo.getNumColumns() <= _N * moDpf._N))) {
            int k = (int) Math.min(_N, _rk2);
            pn.addParam(ParamType.DATA_PARTITIONER, REMOTE_DPE.toString() + "(fused)");
            pn.setK(k);
            //set fused exec type	
            pfpb.setExecMode(REMOTE_DPE);
            pfpb.setDataPartitioner(PDataPartitioner.NONE);
            pfpb.enableColocatedPartitionedMatrix(moVarname);
            pfpb.setDegreeOfParallelism(k);
            apply = true;
        }
    }
    LOG.debug(getOptMode() + " OPT: rewrite 'set fused data partitioning and execution' - result=" + apply);
}