def sl_mst_lifetime_gpu(dest, weight, fe, od, disconnect_weight = None,
MAX_TPB = 256, stream = None):
"""
Input are device arrays.
Inputs:
dest, weight, fe : device arrays
disconnect_weight : weight between unconnected vertices
mst : list of edges in MST
MAX_TPB : number of threads per block
stream : CUDA stream to use
TODO:
- argmax is from cuBlas and only works with 32/64 floats. Make this work
with any type.
-
"""
if disconnect_weight is None:
disconnect_weight = weight.max()
if stream is None:
myStream = cuda.stream()
else:
myStream = stream
mst, n_edges = boruvka_minho_gpu(dest, weight, fe, od,
MAX_TPB=MAX_TPB, stream=myStream,
returnDevAry=True)
# Allocate array for the mst weights.
h_n_edges = int(n_edges.getitem(0, stream=myStream)) # edges to keep in MST
mst_weights = cuda.device_array(h_n_edges, dtype=weight.dtype)
# Get array with only the considered weights in the MST
# and remove those edges in the MST edge list
mstGrid = compute_cuda_grid_dim(h_n_edges, MAX_TPB)
d_weight = cuda.to_device(weight, stream = myStream)
getWeightsOfEdges_gpu[mstGrid, MAX_TPB, myStream](mst, n_edges, d_weight,
mst_weights)
# Sort the MST weights. There are no repeated edges at this
# point since the output MST is like a directed graph.
sorter = RadixSort(maxcount = mst_weights.size, dtype = mst_weights.dtype,
stream = myStream)
sortedWeightArgs = sorter.argsort(mst_weights)
# Allocate array for the lifetimes.
lifetimes = cuda.device_array(mst_weights.size - 1, dtype=mst_weights.dtype)
compute_lifetimes_CUDA[mstGrid, MAX_TPB, myStream](mst_weights, lifetimes)
maxer = Blas(stream)
arg_max_lt = maxer.amax(lifetimes)
max_lt = lifetimes.getitem(arg_max_lt)
# this is the lifetime between edges with no connection and the weakest link
#lt_threshold = disconnect_weight - max_lt
lt_threshold = disconnect_weight - mst_weights.getitem(mst_weights.size - 1)
# if the maximum lifetime is higher or equal than the lifetime threshold
# cut the tree
if max_lt >= lt_threshold:
# from arg_max_lt onward all edges are discarded
n_discarded = lifetimes.size - arg_max_lt + 1
# remove edges
removeGrid = compute_cuda_grid_dim(n_discarded, MAX_TPB)
removeEdges[removeGrid, MAX_TPB](edgeList, sortedArgs, n_discarded)
# compute new amount of edges and update it
new_n_edges = h_n_edges - n_discarded
cuda.to_device(np.array([new_n_edges], dtype = n_edges.dtype),
to = n_edges,
stream = myStream)
ngraph = getGraphFromEdges_gpu(dest, weight, fe, od, edges = mst,
n_edges = n_edges, MAX_TPB = MAX_TPB,
stream = myStream)
ndest, nweight, nfe, nod = ngraph
labels = connected_comps_gpu(ndest, nweight, nfe, nod,
MAX_TPB = 512, stream = myStream)
del ndest, nweight, nfe, nod, lifetimes
return labels
