/* PageRank
* Find PageRank for a graph with a given transition probabilities, a bookmark vector of dangling vertices, and the damping factor.
* This is equivalent to an eigenvalue problem where we want the eigenvector corresponding to the maximum eigenvalue.
* By construction, the maximum eigenvalue is 1.
* The eigenvalue problem is solved with the power method.
*
* Initially :
* V = 6
* E = 10
*
* Edges W
* 0 -> 1 0.50
* 0 -> 2 0.50
* 2 -> 0 0.33
* 2 -> 1 0.33
* 2 -> 4 0.33
* 3 -> 4 0.50
* 3 -> 5 0.50
* 4 -> 3 0.50
* 4 -> 5 0.50
* 5 -> 3 1.00
*
* bookmark (0.0, 1.0, 0.0, 0.0, 0.0, 0.0)^T note: 1.0 if i is a dangling node, 0.0 otherwise
*
* Source oriented representation (CSC):
* destination_offsets {0, 1, 3, 4, 6, 8, 10}
* source_indices {2, 0, 2, 0, 4, 5, 2, 3, 3, 4}
* W0 = {0.33, 0.50, 0.33, 0.50, 0.50, 1.00, 0.33, 0.50, 0.50, 1.00}
*
* ----------------------------------
*
* Operation : Pagerank with various damping factor
* ----------------------------------
*
* Expected output for alpha= 0.9 (result stored in pr_2) : (0.037210, 0.053960, 0.041510, 0.37510, 0.206000, 0.28620)^T
* From "Google's PageRank and Beyond: The Science of Search Engine Rankings" Amy N. Langville & Carl D. Meyer
*/
static void Main(string[] args)
{
SizeT n = 6, nnz = 10, vertex_numsets = 3, edge_numsets = 1;
float[] alpha1 = new float[] { 0.85f }, alpha2 = new float[] { 0.90f };
int i;
int[] destination_offsets_h, source_indices_h;
float[] weights_h, bookmark_h, pr_1, pr_2;
//void** vertex_dim;
// nvgraph variables
GraphContext handle;
GraphDescriptor graph;
nvgraphCSCTopology32I CSC_input;
cudaDataType[] edge_dimT = new cudaDataType[] { cudaDataType.CUDA_R_32F };
cudaDataType[] vertex_dimT;
// use command-line specified CUDA device, otherwise use device with highest Gflops/s
int cuda_device = 0;
CudaDeviceProperties deviceProp = CudaContext.GetDeviceInfo(cuda_device);
Console.WriteLine("> Detected Compute SM {0}.{1} hardware with {2} multi-processors",
deviceProp.ComputeCapability.Major, deviceProp.ComputeCapability.Minor, deviceProp.MultiProcessorCount);
if (deviceProp.ComputeCapability.Major < 3)
{
Console.WriteLine("> nvGraph requires device SM 3.0+");
Console.WriteLine("> Waiving.");
return;
}
// Allocate host data
destination_offsets_h = new int[n + 1];
source_indices_h = new int[nnz];
weights_h = new float[nnz];
bookmark_h = new float[n];
pr_1 = new float[n];
pr_2 = new float[n];
//vertex_dim = (void**)malloc(vertex_numsets * sizeof(void*));
vertex_dimT = new cudaDataType[vertex_numsets];
CSC_input = new nvgraphCSCTopology32I();
// Initialize host data
//vertex_dim[0] = (void*)bookmark_h; vertex_dim[1]= (void*)pr_1, vertex_dim[2]= (void*)pr_2;
vertex_dimT[0] = cudaDataType.CUDA_R_32F; vertex_dimT[1] = cudaDataType.CUDA_R_32F; vertex_dimT[2] = cudaDataType.CUDA_R_32F;
weights_h[0] = 0.333333f;
weights_h[1] = 0.500000f;
weights_h[2] = 0.333333f;
weights_h[3] = 0.500000f;
weights_h[4] = 0.500000f;
weights_h[5] = 1.000000f;
weights_h[6] = 0.333333f;
weights_h[7] = 0.500000f;
weights_h[8] = 0.500000f;
weights_h[9] = 0.500000f;
destination_offsets_h[0] = 0;
destination_offsets_h[1] = 1;
destination_offsets_h[2] = 3;
destination_offsets_h[3] = 4;
destination_offsets_h[4] = 6;
destination_offsets_h[5] = 8;
destination_offsets_h[6] = 10;
source_indices_h[0] = 2;
source_indices_h[1] = 0;
source_indices_h[2] = 2;
source_indices_h[3] = 0;
source_indices_h[4] = 4;
source_indices_h[5] = 5;
source_indices_h[6] = 2;
source_indices_h[7] = 3;
source_indices_h[8] = 3;
source_indices_h[9] = 4;
bookmark_h[0] = 0.0f;
bookmark_h[1] = 1.0f;
bookmark_h[2] = 0.0f;
bookmark_h[3] = 0.0f;
bookmark_h[4] = 0.0f;
bookmark_h[5] = 0.0f;
// Starting nvgraph
handle = new GraphContext();
graph = handle.CreateGraphDecriptor();
GCHandle destination_offsets_handle = GCHandle.Alloc(destination_offsets_h, GCHandleType.Pinned);
GCHandle source_indices_handle = GCHandle.Alloc(source_indices_h, GCHandleType.Pinned);
CSC_input.nvertices = n;
CSC_input.nedges = nnz;
CSC_input.destination_offsets = destination_offsets_handle.AddrOfPinnedObject();
CSC_input.source_indices = source_indices_handle.AddrOfPinnedObject();
// Set graph connectivity and properties (tranfers)
graph.SetGraphStructure(CSC_input);
graph.AllocateVertexData(vertex_dimT);
graph.AllocateEdgeData(edge_dimT);
graph.SetVertexData(bookmark_h, 0);
graph.SetVertexData(pr_1, 1);
graph.SetVertexData(pr_2, 2);
graph.SetEdgeData(weights_h, 0);
// First run with default values
graph.Pagerank(0, alpha1, 0, 0, 1, 0.0f, 0);
// Get and print result
graph.GetVertexData(pr_1, 1);
Console.WriteLine("pr_1, alpha = 0.85");
for (i = 0; i < n; i++)
{
Console.WriteLine(pr_1[i]);
}
Console.WriteLine();
// Second run with different damping factor and an initial guess
for (i = 0; i < n; i++)
{
pr_2[i] = pr_1[i];
}
graph.SetVertexData(pr_2, 2);
graph.Pagerank(0, alpha2, 0, 1, 2, 0.0f, 0);
// Get and print result
graph.GetVertexData(pr_2, 2);
Console.WriteLine("pr_2, alpha = 0.90");
for (i = 0; i < n; i++)
{
Console.WriteLine(pr_2[i]);
}
Console.WriteLine();
//Clean
graph.Dispose();
handle.Dispose();
Console.WriteLine("\nDone!");
}
