GKLEE

GKLEE is a symbolic analyser and test generator tailored for CUDA C++ programs, it supports many CUDA intrinsic functions in kernel code and CUDA runtimes in host code. For more details, please visit GKLEE's homepage: www.cs.utah.edu/fv/GKLEE

Please refer to the tutorial on this wiki, located here: https://github.com/Geof23/Gklee/wiki/flows_tutorial

This is a fork of the original Github version of GKLEE, https://github.com/PengPengHub/Gklee

Note that GKLEE has been tested on an Ubuntu 20 system, so your mileage may vary with other 'nix distros

Prerequisites for GKLEE

• a unix type system
• a modern c++ compiler (at least c++-11 complete)
• CMake, version 3.3+
• boost developer libraries
• bison
• flex
• python (at least 2.7, < 3)
• perl

Many package managers have suitable versions of the prerequisits for your distro. (see below for a quick config example)

Building GKLEE

1. clone GKLEE
2. make an out-of-source directory to build in
3. cd chosen build directory
4. run cmake [path to GKLEE root]
5. build the system

Here's a quick example of config and GNU Makefile based build (on Ubuntu):

sudo apt-get install g++ cmake libboost-all-dev bison flex python-2.7 perl
git clone [email protected]:Geof23/Gklee.git
mkdir Gklee/build
cd Gklee/build
cmake ..
make -j

Running GKLEE

Required environment variables

Another quick example, in a bash shell:

	export KLEE_HOME_DIR=/Path/To/Gklee
	export PATH=$KLEE_HOME_DIR/bin:$PATH

After building GKLEE and setting environment variables properly, you could run GKLEE.

1. Compile your CUDA programs into LLVM bytecode with the command:

   gklee-nvcc xxx.cu [-o executable] [other options used in nvcc ...]

NOTE: if you do not specify a executable name, gklee-nvcc will use the prefix of the CUDA program as the default name

2. Run your program with GKLEE command (normal mode -- no symbolic execution)

   gklee executable

... or with symbolic execution:

   gklee --symbolic-config executable

3. The test cases will be generated in the same dir where you execute gklee, and appear as 'klee-out-[number]' and 'klee-last'.

TaintAnalysis: Gklee 'SESA'

taint analyser consists of three clang compiler passes, which perform a combination of use-def chain analysis and alias analysis to enable taint analysis on CUDA kernels.

To run the analyser:

	sesa < [input_llvm_bytecode] > [output_llvm_bytecode]

1. The taint analyser outputs informative messages on which variables shall be symbolized in a file named "summary.txt"

2. The taint analyser annotates the input llvm bytecode with LLVM metadata and generates the new llvm bytecode containing LLVM annotations that are used to prune redundant flows in the symbolic execution stage.

3. To run this annotated bytecode in Gklee:

	gklee --symbolic-config --race-prune [path to annotated bytecode]