Recommended environment

• Clang with CilkPlus and NUMA support: https://github.com/hvdieren/swan_clang
• Matching LLVM: https://github.com/hvdieren/swan_llvm
• Extended Cilkplus runtime: https://github.com/hvdieren/swan_runtime

Check out https://github.com/hvdieren/swan_tests for instructions on how to set up the build environment.

After the appropriate environment variables are set, to compile, simply run

$ make -j 16 

This is to compile and build with 16 threads in parallel. You can use the number of your choice.

The remainder of the explanation is retained from Ligra.

Example of running the code: An example unweighted graph rMatGraph_J_5_100 and weighted graph rMatGraph_WJ_5_100 are provided. Symmetric graphs should be called with the "-s" flag for better performance. For example:

$ ./BFS -s rMatGraph_J_5_100
$ ./BellmanFord -s rMatGraph_WJ_5_100

For BFS, BC and BellmanFord, one can also pass the "-r" flag followed by an integer to indicate the source vertex. rMat graphs along with other graphs can be generated with the graph generators at www.cs.cmu.edu/~pbbs. By default, the applications are run four times, with times reported for the last three runs. This can be changed by passing the flag "-rounds" followed by an integer indicating the number of timed runs.

The input format of an unweighted graphs should be in one of two formats.

1. The adjacency graph format from the Problem Based Benchmark Suite (http://www.cs.cmu.edu/~pbbs/benchmarks/graphIO.html). The adjacency graph format starts with a sequence of offsets one for each vertex, followed by a sequence of directed edges ordered by their source vertex. The offset for a vertex i refers to the location of the start of a contiguous block of out edges for vertex i in the sequence of edges. The block continues until the offset of the next vertex, or the end if i is the last vertex. All vertices and offsets are 0 based and represented in decimal. The specific format is as follows:

AdjacencyGraph
<n>
<m>
<o0>
<o1>
...
<o(n-1)>
<e0>
<e1>
...
<e(m-1)>

This file is represented as plain text.

2. In binary format. This requires three files NAME.config, NAME.adj, and NAME.idx, where NAME is chosen by the user. The .config file stores the number of vertices in the graph in text format. The .idx file stores in binary the offsets for the vertices in the CSR format (the 's above). The .adj file stores in binary the edge targets in the CSR format (the 's above).

Weighted graphs: For format (1), the weights are listed at the end of the file (after <e(m-1)>). Currently for format (2), the weights are all set to 1.

By default, format (1) is used. To run an input with format (2), pass the "-b" flag as a command line argument.

By default the offsets are stored as 32-bit integers, and to represent them as 64-bit integers, compile with the variable LONG defined. By default the vertex IDs (edge values) are stored as 32-bit integers, and to represent them as 64-bit integers, compile with the variable EDGELONG defined.

Currently, Ligra comes with 8 implementation files: BFS.C (breadth-first search), BC.C (betweenness centrality), Radii.C (graph radii estimation), Components.C (connected components), BellmanFord.C (Bellman-Ford shortest paths), PageRank.C, PageRankDelta.C and BFSCC.C (connected components based on BFS).

vertexSubset: represents a subset of vertices in the graph. Various constructors are given in ligra.h

edgeMap: takes as input 3 required arguments and 3 optional arguments: a graph G, vertexSubset V, struct F, threshold argument (optional, default threshold is m/20), an option in {DENSE, DENSE_FORWARD} (optional, default value is DENSE), and a boolean indiciating whether to remove duplicates (optional, default does not remove duplicates). It returns as output a vertexSubset Out (see section 4 of paper for how Out is computed).

The F struct contains three boolean functions: update, updateAtomic and cond. update and updateAtomic should take two integer arguments (corresponding to source and destination vertex). In addition, updateAtomic should be atomic with respect to the destination vertex. cond takes one argument corresponding to a vertex. For the cond function which always returns true, cond_true can be called.

struct F {
  inline bool update (intT s, intT d) {
  //fill in
  }
  inline bool updateAtomic (intT s, intT d){ 
  //fill in
  }
  inline bool cond (intT d) {
  //fill in 
  }
};

The threshold argument determines when edgeMap switches between edgemapSparse and edgemapDense---for a threshold value T, edgeMap calls edgemapSparse if the vertex subset size plus its number of outgoing edges is less than T, and otherwise calls edgemapDense.

DENSE and is a read-based version where all vertices not satisfying Cond loop over their incoming edges and DENSE_FORWARD is a write-based version where each frontier vertex loops over its outgoing edges. This optimization is described in Section 4 of the paper.

Note that duplicate removal can only be avoided if updateAtomic returns true at most once for each vertex in a call to edgeMap.

vertexMap: takes as input 2 arguments: a vertexSubset V and a function F which is applied to all vertices in V. It does not have a return value.

vertexFilter: takes as input a vertexSubset V and a boolean function F which is applied to all vertices in V. It returns a vertexSubset containing all vertices v in V such that F(v) returns true.

struct F {
  inline bool operator () (intT i) {
  //fill in
  }
};

To write your own Ligra code, it would be helpful to look at the code for the provided applications as reference.

Currently the results of the computation are not used, but the code can be easily modified to output the results to a file.

To develop a new implementation, simply include "ligra.h" in the implementation files. When finished, one may add it to the ALL variable in Makefile. The function that is passed to the Ligra driver is the following Compute function, which is filled in by the user. The first argument is the graph, and second argument specifies the starting vertex for algorithms that require one.

template<class vertex>
void Compute(graph<vertex> GA, intT start){ 

}

For weighted graph applications, add "#define WEIGHTED 1" before including ligra.h.

To write a parallel for loop in your code, simply use the parallel_for construct in place of "for".

Jiawen Sun, Hans Vandierendonck and Dimitrios S. Nikolopoulos [GraphGrind: Addressing Load Imbalance of Graph Partitioning]. To appear in Proceedings of the International Conference on Supercomputing (ICS), 2017.

Based on: Julian Shun and Guy Blelloch. Ligra: A Lightweight Graph Processing Framework for Shared Memory. Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), pp. 135-146, 2013.