This is the code for TRUST: Triangle Counting Reloaded on GPUs.

The code of TRUST has two version: without graph partition for small graph and without graph partition for large graph. Preprocess include the code for preprocessing. Following the step to test the TRUST.

CUDA Toolkit 10.2; g++ 7.4.0; MPICH-3.3

In Preprocessing step, use

$ cd Preprocess
$ ./compile.sh 

compile the code and we will get three files: fromDirectToUndirece, preprocess and partition. This corresponds to following three step:

1. fromDirectToUndirect transform the directed graph to undirected graph, delete the duplicate edges and self loops and remove orphan vertices. It take file name as input and will generate undirected graph 1.mmio. For example:

   $ ./fromDirectToUndirect cit-Patents.txt

The format of cit-Patents.txt should be edge list.

2. preprocess will do the orientation and reordering and generate the CSR format of graph. It will take 1.mmio as input and generate two file begin.bin and adjacent.bin

3. partition use hash to partition the graph. To see detail of partition usage, you can read the Dataset/Cit-Patents/partition.sh

In folder Dataset/Cit-Patents/ we give a example of download Cit-Patents graph and preprocessing it. Run it by

$ cd Dataset/Cit-Patents/
$ ./get+preprocess.sh

For the large graph and input file only include edge list, we recommend use preprocess code in Preprocess/speedupIO.

For partition, run

$./partition.sh 2

There are one input arguments n, it represent the partition number, we will partition graph into n*n pieces

Before compile the code, you should modify the Makefile to match your architecture. The current settings, --gpu-architecture=compute_70 --gpu-code=sm_70, are tailored for the V100 environment used in the paper. For small graph, we don't partition the graph. Compile the code:

$ cd Without-graph-partition/
$ make

Run the code:

$ mpirun -n 1 ./trianglecounting.bin ../Dataset/Cit-Patents/ 1 1024 1024 1

The input arguments is

1. input graph folder
2. number of GPUs
3. number of thread per block
4. number of block
5. chuncksize

The output arguments is

1. graph folder
2. vertex count
3. edge count
4. triangle counts
5. times
6. TEPS rate

For the large graph, partition is required.

Compile the code:

$ cd With-graph-partition/
$ make

Run the code:

$ mpirun -n 8 ./trianglecounting.bin ../Dataset/Cit-Patents/ 8 1024 1024 1 2

The input arguments is

1. input graph folder
2. number of GPUs should be m
3. number of thread per block
4. number of block
5. chuncksize
6. partition number n

The output arguments is

1. graph folder
2. triangle counts
3. min times
4. max times

@article{pandey2021trust, 
  title={TRUST: Triangle Counting Reloaded on GPUs}, 
  author={Pandey, Santosh and Wang, Zhibin and Zhong, Sheng and Tian, Chen and Zheng, Bolong and Li, Xiaoye and Li, Lingda and Hoisie, Adolfy and Ding, Caiwen and Li, Dong and others}, 
  journal={IEEE Transactions on Parallel and Distributed Systems}, 
  volume={32}, 
  number={11}, 
  pages={2646--2660}, 
  year={2021}, 
  publisher={IEEE} 
}