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Graspan-G

Welcome to the home repository of Graspan-G.

Graspan-G is a scalable GPU-based out-of-core graph system for interprocedural static analysis.

This Readme (under revision) provides a how-to-use guide for Graspan-G.

Getting Started

Required Libraries

Ensure that you have a recent version(10.2 in our project) of the CUDA Toolkit and the Boost library installed in your system.

Compiling Graspan-G

First, download the entire Graspan-G source code into your machine. Next, edit the src/makefile to set the paths to the CUDA include files and lib files in your machine. Finally, run the makefile in the src folder using make. Graspan-G should now be compiled and ready to run.

Running Graspan-G

Graspan-G needs two input files:

  1. A program graph on which Graspan-G can perform computations;
  2. A grammar file which describes how the computations are to be performed.

A sample input is inside the src/inputFiles folder.

After getting the graph and grammar file, run Graspan-G by entering the following command and monitor the progress of the computation on the screen:

../bin/comp <graph_file>  <grammar_file>  <filter_flag> 

Note that the filter flag is a switch to optimize the performance of dataflow analysis rules only. 0 means off optimization, 1 means on optimization. In other analysis, the flag should be set to 0.

Project Contributors

  • Zhiqiang Zuo - Assistant Professor, Nanjing University
  • Yiyu Zhang - PhD Student, Nanjing University
  • Shenming Lu - Master Student, Nanjing University

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Graspan-G is a GPU-based version of Graspan.

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