Examples with MemoTableEntry org.apache.sysml.hops.codegen.template.CPlanMemoTable.MemoTableEntry used on opensource projects

Example 6 with MemoTableEntry

use of org.apache.sysml.hops.codegen.template.CPlanMemoTable.MemoTableEntry in project incubator-systemml by apache.

the class PlanSelectionFuseCostBased method selectPlans.

private void selectPlans(CPlanMemoTable memo, HashSet<Long> partition, HashSet<Long> R, ArrayList<Long> M) {
    // prune row aggregates with pure cellwise operations
    for (Long hopID : R) {
        MemoTableEntry me = memo.getBest(hopID, TemplateType.ROW);
        if (me.type == TemplateType.ROW && memo.contains(hopID, TemplateType.CELL) && isRowTemplateWithoutAgg(memo, memo.getHopRefs().get(hopID), new HashSet<Long>())) {
            List<MemoTableEntry> blacklist = memo.get(hopID, TemplateType.ROW);
            memo.remove(memo.getHopRefs().get(hopID), new HashSet<>(blacklist));
            if (LOG.isTraceEnabled()) {
                LOG.trace("Removed row memo table entries w/o aggregation: " + Arrays.toString(blacklist.toArray(new MemoTableEntry[0])));
            }
        }
    }
    // we'd prune sum(X*(U%*%t(V))*Z), Z=U2%*%t(V2) because this would unnecessarily destroy a fusion pattern.
    for (Long hopID : partition) {
        if (memo.countEntries(hopID, TemplateType.OUTER) == 2) {
            List<MemoTableEntry> entries = memo.get(hopID, TemplateType.OUTER);
            MemoTableEntry me1 = entries.get(0);
            MemoTableEntry me2 = entries.get(1);
            MemoTableEntry rmEntry = TemplateOuterProduct.dropAlternativePlan(memo, me1, me2);
            if (rmEntry != null) {
                memo.remove(memo.getHopRefs().get(hopID), Collections.singleton(rmEntry));
                memo.getPlansBlacklisted().remove(rmEntry.input(rmEntry.getPlanRefIndex()));
                if (LOG.isTraceEnabled())
                    LOG.trace("Removed dominated outer product memo table entry: " + rmEntry);
            }
        }
    }
    // if no materialization points, use basic fuse-all w/ partition awareness
    if (M == null || M.isEmpty()) {
        for (Long hopID : R) rSelectPlansFuseAll(memo, memo.getHopRefs().get(hopID), null, partition);
    } else {
        // TODO branch and bound pruning, right now we use exhaustive enum for early experiments
        // via skip ahead in below enumeration algorithm
        // obtain hop compute costs per cell once
        HashMap<Long, Double> computeCosts = new HashMap<>();
        for (Long hopID : R) rGetComputeCosts(memo.getHopRefs().get(hopID), partition, computeCosts);
        // scan linearized search space, w/ skips for branch and bound pruning
        int len = (int) Math.pow(2, M.size());
        boolean[] bestPlan = null;
        double bestC = Double.MAX_VALUE;
        for (int i = 0; i < len; i++) {
            // construct assignment
            boolean[] plan = createAssignment(M.size(), i);
            // cost assignment on hops
            double C = getPlanCost(memo, partition, R, M, plan, computeCosts);
            if (LOG.isTraceEnabled())
                LOG.trace("Enum: " + Arrays.toString(plan) + " -> " + C);
            // cost comparisons
            if (bestPlan == null || C < bestC) {
                bestC = C;
                bestPlan = plan;
                if (LOG.isTraceEnabled())
                    LOG.trace("Enum: Found new best plan.");
            }
        }
        if (DMLScript.STATISTICS) {
            Statistics.incrementCodegenEnumAllP(len);
            Statistics.incrementCodegenEnumEval(len);
        }
        // prune memo table wrt best plan and select plans
        HashSet<Long> visited = new HashSet<>();
        for (Long hopID : R) rPruneSuboptimalPlans(memo, memo.getHopRefs().get(hopID), visited, partition, M, bestPlan);
        HashSet<Long> visited2 = new HashSet<>();
        for (Long hopID : R) rPruneInvalidPlans(memo, memo.getHopRefs().get(hopID), visited2, partition, M, bestPlan);
        for (Long hopID : R) rSelectPlansFuseAll(memo, memo.getHopRefs().get(hopID), null, partition);
    }
}

Example 7 with MemoTableEntry

use of org.apache.sysml.hops.codegen.template.CPlanMemoTable.MemoTableEntry in project incubator-systemml by apache.

the class PlanSelectionFuseCostBased method isRowTemplateWithoutAgg.

private static boolean isRowTemplateWithoutAgg(CPlanMemoTable memo, Hop current, HashSet<Long> visited) {
    // consider all aggregations other than root operation
    MemoTableEntry me = memo.getBest(current.getHopID(), TemplateType.ROW);
    boolean ret = true;
    for (int i = 0; i < 3; i++) if (me.isPlanRef(i))
        ret &= rIsRowTemplateWithoutAgg(memo, current.getInput().get(i), visited);
    return ret;
}

Example 8 with MemoTableEntry

use of org.apache.sysml.hops.codegen.template.CPlanMemoTable.MemoTableEntry in project incubator-systemml by apache.

the class PlanSelectionFuseCostBased method rIsRowTemplateWithoutAgg.

private static boolean rIsRowTemplateWithoutAgg(CPlanMemoTable memo, Hop current, HashSet<Long> visited) {
    if (visited.contains(current.getHopID()))
        return true;
    boolean ret = true;
    MemoTableEntry me = memo.getBest(current.getHopID(), TemplateType.ROW);
    for (int i = 0; i < 3; i++) if (me.isPlanRef(i))
        ret &= rIsRowTemplateWithoutAgg(memo, current.getInput().get(i), visited);
    ret &= !(current instanceof AggUnaryOp || current instanceof AggBinaryOp);
    visited.add(current.getHopID());
    return ret;
}

Example 9 with MemoTableEntry

use of org.apache.sysml.hops.codegen.template.CPlanMemoTable.MemoTableEntry in project incubator-systemml by apache.

the class PlanSelectionFuseCostBased method rGetPlanCosts.

private static double rGetPlanCosts(CPlanMemoTable memo, Hop current, HashSet<Pair<Long, Long>> visited, HashSet<Long> partition, ArrayList<Long> M, boolean[] plan, HashMap<Long, Double> computeCosts, CostVector costsCurrent, TemplateType currentType) {
    // memoization per hop id and cost vector to account for redundant
    // computation without double counting materialized results or compute
    // costs of complex operation DAGs within a single fused operator
    Pair<Long, Long> tag = Pair.of(current.getHopID(), (costsCurrent == null) ? 0 : costsCurrent.ID);
    if (visited.contains(tag))
        return 0;
    visited.add(tag);
    // open template if necessary, including memoization
    // under awareness of current plan choice
    MemoTableEntry best = null;
    boolean opened = false;
    if (memo.contains(current.getHopID())) {
        if (currentType == null) {
            best = memo.get(current.getHopID()).stream().filter(p -> p.isValid()).filter(p -> hasNoRefToMaterialization(p, M, plan)).min(new BasicPlanComparator()).orElse(null);
            opened = true;
        } else {
            best = memo.get(current.getHopID()).stream().filter(p -> p.type == currentType || p.type == TemplateType.CELL).filter(p -> hasNoRefToMaterialization(p, M, plan)).min(Comparator.comparing(p -> 7 - ((p.type == currentType) ? 4 : 0) - p.countPlanRefs())).orElse(null);
        }
    }
    // create new cost vector if opened, initialized with write costs
    CostVector costVect = !opened ? costsCurrent : new CostVector(Math.max(current.getDim1(), 1) * Math.max(current.getDim2(), 1));
    // add compute costs of current operator to costs vector
    if (partition.contains(current.getHopID()))
        costVect.computeCosts += computeCosts.get(current.getHopID());
    // process children recursively
    double costs = 0;
    for (int i = 0; i < current.getInput().size(); i++) {
        Hop c = current.getInput().get(i);
        if (best != null && best.isPlanRef(i))
            costs += rGetPlanCosts(memo, c, visited, partition, M, plan, computeCosts, costVect, best.type);
        else if (best != null && isImplicitlyFused(current, i, best.type))
            costVect.addInputSize(c.getInput().get(0).getHopID(), Math.max(c.getDim1(), 1) * Math.max(c.getDim2(), 1));
        else {
            // include children and I/O costs
            costs += rGetPlanCosts(memo, c, visited, partition, M, plan, computeCosts, null, null);
            if (costVect != null && c.getDataType().isMatrix())
                costVect.addInputSize(c.getHopID(), Math.max(c.getDim1(), 1) * Math.max(c.getDim2(), 1));
        }
    }
    // add costs for opened fused operator
    if (partition.contains(current.getHopID())) {
        if (opened) {
            if (LOG.isTraceEnabled())
                LOG.trace("Cost vector for fused operator (hop " + current.getHopID() + "): " + costVect);
            // time for output write
            costs += costVect.outSize * 8 / WRITE_BANDWIDTH;
            costs += Math.max(costVect.computeCosts * costVect.getMaxInputSize() / COMPUTE_BANDWIDTH, costVect.getSumInputSizes() * 8 / READ_BANDWIDTH);
        } else // add costs for non-partition read in the middle of fused operator
        if (hasNonPartitionConsumer(current, partition)) {
            costs += rGetPlanCosts(memo, current, visited, partition, M, plan, computeCosts, null, null);
        }
    }
    // sanity check non-negative costs
    if (costs < 0 || Double.isNaN(costs) || Double.isInfinite(costs))
        throw new RuntimeException("Wrong cost estimate: " + costs);
    return costs;
}

Example 10 with MemoTableEntry

use of org.apache.sysml.hops.codegen.template.CPlanMemoTable.MemoTableEntry in project incubator-systemml by apache.

the class PlanSelectionFuseCostBasedV2 method createAndAddMultiAggPlans.

// across-partition multi-agg templates with shared reads
private void createAndAddMultiAggPlans(CPlanMemoTable memo, ArrayList<Hop> roots) {
    // collect full aggregations as initial set of candidates
    HashSet<Long> fullAggs = new HashSet<>();
    Hop.resetVisitStatus(roots);
    for (Hop hop : roots) rCollectFullAggregates(hop, fullAggs);
    Hop.resetVisitStatus(roots);
    // remove operators with assigned multi-agg plans
    fullAggs.removeIf(p -> memo.contains(p, TemplateType.MAGG));
    // check applicability for further analysis
    if (fullAggs.size() <= 1)
        return;
    if (LOG.isTraceEnabled()) {
        LOG.trace("Found across-partition ua(RC) aggregations: " + Arrays.toString(fullAggs.toArray(new Long[0])));
    }
    // collect information for all candidates
    // (subsumed aggregations, and inputs to fused operators)
    List<AggregateInfo> aggInfos = new ArrayList<>();
    for (Long hopID : fullAggs) {
        Hop aggHop = memo.getHopRefs().get(hopID);
        AggregateInfo tmp = new AggregateInfo(aggHop);
        for (int i = 0; i < aggHop.getInput().size(); i++) {
            Hop c = HopRewriteUtils.isMatrixMultiply(aggHop) && i == 0 ? aggHop.getInput().get(0).getInput().get(0) : aggHop.getInput().get(i);
            rExtractAggregateInfo(memo, c, tmp, TemplateType.CELL);
        }
        if (tmp._fusedInputs.isEmpty()) {
            if (HopRewriteUtils.isMatrixMultiply(aggHop)) {
                tmp.addFusedInput(aggHop.getInput().get(0).getInput().get(0).getHopID());
                tmp.addFusedInput(aggHop.getInput().get(1).getHopID());
            } else
                tmp.addFusedInput(aggHop.getInput().get(0).getHopID());
        }
        aggInfos.add(tmp);
    }
    if (LOG.isTraceEnabled()) {
        LOG.trace("Extracted across-partition ua(RC) aggregation info: ");
        for (AggregateInfo info : aggInfos) LOG.trace(info);
    }
    // sort aggregations by num dependencies to simplify merging
    // clusters of aggregations with parallel dependencies
    aggInfos = aggInfos.stream().sorted(Comparator.comparing(a -> a._inputAggs.size())).collect(Collectors.toList());
    // greedy grouping of multi-agg candidates
    boolean converged = false;
    while (!converged) {
        AggregateInfo merged = null;
        for (int i = 0; i < aggInfos.size(); i++) {
            AggregateInfo current = aggInfos.get(i);
            for (int j = i + 1; j < aggInfos.size(); j++) {
                AggregateInfo that = aggInfos.get(j);
                if (current.isMergable(that)) {
                    merged = current.merge(that);
                    aggInfos.remove(j);
                    j--;
                }
            }
        }
        converged = (merged == null);
    }
    if (LOG.isTraceEnabled()) {
        LOG.trace("Merged across-partition ua(RC) aggregation info: ");
        for (AggregateInfo info : aggInfos) LOG.trace(info);
    }
    // construct and add multiagg template plans (w/ max 3 aggregations)
    for (AggregateInfo info : aggInfos) {
        if (info._aggregates.size() <= 1)
            continue;
        Long[] aggs = info._aggregates.keySet().toArray(new Long[0]);
        MemoTableEntry me = new MemoTableEntry(TemplateType.MAGG, aggs[0], aggs[1], (aggs.length > 2) ? aggs[2] : -1, aggs.length);
        for (int i = 0; i < aggs.length; i++) {
            memo.add(memo.getHopRefs().get(aggs[i]), me);
            addBestPlan(aggs[i], me);
            if (LOG.isTraceEnabled())
                LOG.trace("Added multiagg* plan: " + aggs[i] + " " + me);
        }
    }
}