Beispiel #1
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def cc_pull_topo_operator(graph: PropertyGraph, changed, comp_current: np.ndarray, nid):
    for ii in graph.edges(nid):
        dst = graph.get_edge_dst(ii)
        # Pull the minimum component from your neighbors
        if comp_current[nid] > comp_current[dst]:
            comp_current[nid] = comp_current[dst]
            # Indicates that update happened
            changed.update(True)
Beispiel #2
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def compute_async_kcore_operator(graph: PropertyGraph, current_degree,
                                 k_core_num, nid, ctx):
    # Decrement degree of all the neighbors of dead node
    for ii in graph.edges(nid):
        dst = graph.get_edge_dst(ii)
        old_degree = atomic_sub(current_degree, dst, 1)
        # Add new dead nodes to the worklist
        if old_degree == k_core_num:
            ctx.push(dst)
Beispiel #3
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def compute_pagerank_pull_residual_operator(graph: PropertyGraph, delta, residual, nid):
    sum = 0
    for ii in graph.edges(nid):
        dst = graph.get_edge_dst(ii)
        if delta[dst] > 0:
            sum += delta[dst]

    if sum > 0:
        residual[nid] = sum
Beispiel #4
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def cc_push_topo_operator(graph: PropertyGraph, changed, comp_current: np.ndarray, comp_old: np.ndarray, nid):
    if comp_old[nid] > comp_current[nid]:
        comp_old[nid] = comp_current[nid]
        # Indicates that update happened
        changed.update(True)
        for ii in graph.edges(nid):
            dst = graph.get_edge_dst(ii)
            new_comp = comp_current[nid]
            # Push the minimum component to your neighbors
            atomic_min(comp_current, dst, new_comp)
Beispiel #5
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def bfs_sync_operator_pg(
    graph: PropertyGraph, next_level: InsertBag[np.uint64], next_level_number: int, distance: np.ndarray, nid,
):
    num_nodes = graph.num_nodes()

    for ii in graph.edges(nid):
        dst = graph.get_edge_dst(ii)
        if distance[dst] == num_nodes:
            distance[dst] = next_level_number
            next_level.push(dst)
Beispiel #6
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def sssp_operator(g: PropertyGraph, dists: np.ndarray, edge_weights, item,
                  ctx: UserContext):
    if dists[item.src] < item.dist:
        return
    for ii in g.edges(item.src):
        dst = g.get_edge_dst(ii)
        edge_length = edge_weights[ii]
        new_distance = edge_length + dists[item.src]
        old_distance = atomic_min(dists, dst, new_distance)
        if new_distance < old_distance:
            ctx.push((dst, new_distance))
Beispiel #7
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def compute_out_deg_operator(graph: PropertyGraph, nout, nid):
    """Operator for computing outdegree of nodes in the Graph"""
    for ii in graph.edges(nid):
        dst = graph.get_edge_dst(ii)
        atomic_add(nout, dst, 1)