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@@ -0,0 +1,112 @@ +GPGPU-Sim Simulator version 2.1.1b (beta) + +See doc/GPGPU-Sim_Manual.html for more documentation. + +Please see the copyright notice in the file COPYRIGHT distributed with this +release in the same directory as this file. This version of GPGPU-Sim is +for non-commercial use only. + +If you use this simulator in your research please cite: + +Ali Bakhoda, George Yuan, Wilson W. L. Fung, Henry Wong, Tor M. Aamodt, +Analyzing CUDA Workloads Using a Detailed GPU Simulator, in IEEE International +Symposium on Performance Analysis of Systems and Software (ISPASS), Boston, MA, +April 19-21, 2009. + +Please sign up for the google groups page for Q&A (see gpgpu-sim.org). + +See Section 2 "INSTALLING, BUILDING and RUNNING GPGPU-Sim" below to get started. + +1. CONTRIBUTIONS and HISTORY + +GPGPU-Sim was created at the University of British Columbia by Tor M. Aamodt, +Wilson W. L. Fung, Ali Bakhoda, George Yuan along with contributions by Ivan +Sham, Henry Wong, Henry Tran, and others. + +GPGPU-Sim models the features of a modern graphics processor that are relevant +to non-graphics applications. The first version of GPGPU-Sim was used in a +MICRO'07 paper and follow-on ACM TACO paper on dynamic warp formation. That +version of GPGPU-Sim used the SimpleScalar PISA instruction set for functional +simulation, and various configuration files to provide a programming model +close to CUDA. Creating benchmarks for the original GPGPU-Sim simulator was a +very time consuming process. This motivated the development an interface for +directly running CUDA applications to leverage the growing number of +applications being developed to use CUDA. + +The interconnection network is simulated using the booksim simulator developed +by Bill Dally's research group at Stanford. + +The current version of GPGPU-Sim still uses a few portions of SimpleScalar +functional simulation code: support for memory spaces and command line option +processing (but not for any timing model purposes). SimpleScalar code has very +strict restrictions on non-academic use (these portions may be removed in a +future version of GPGPU-Sim). + +To produce output that is compatible with the output from running the same CUDA +program on the GPU, we have implemented several PTX instructions using the CUDA +Math library (part of the CUDA toolkit). Code to interface with the CUDA Math +library is contained in cuda-math.h, which also includes several structures +derived from vector_types.h (one of the CUDA header files). + +See file CHANGES for updates in this and earlier versions. + +2. INSTALLING, BUILDING and RUNNING GPGPU-Sim + +GPGPU-Sim was developed on Linux SuSe (this release was tested with SuSe +version 11.1) and has been used on several other Linux platforms. + +Step 1: Ensure you have gcc, g++, make, makedepend, zlib, bison and flex +installed on your system. For CUDA 2.x we used gcc version 4.3.2, for CUDA 1.1 +we used gcc/g++ version 4.1.3. We used bison version 2.3, and flex version 2.5.33. + +Step 2: Download and install the CUDA Toolkit and CUDA SDK code samples from +NVIDIA's website: <http://www.nvidia.com/cuda>. If you want to run OpenCL on +the simulator, download and install NVIDIA's OpenCL driver from +<http://developer.nvidia.com/object/opencl-download.html>. Update your PATH and +LD_LIBRARY_PATH as indicated by the install scripts. + +Step 3: Build libcutil.a. The install script for the CUDA SDK does not do this +step automatically. If you installed the CUDA Toolkit in a nonstandard location +you will first need to set CUDA_INSTALL_PATH to the location you installed the +CUDA toolkit (including the trailing "/cuda"). Then, change to the C/common +subdirectory of your CUDA SDK installation (or common subdirectory on older +CUDA SDK versions) and type "make". + +Step 4: Set environment variables (e.g., your .bashrc file if you use bash as +your shell). + + (a) Set GPGPUSIM_ROOT to point to the directory containing this README file. + (b) Set CUDAHOME to point to your CUDA installation directory + (c) Set NVIDIA_CUDA_SDK_LOCATION to point to the location of the CUDA SDK + (d) Add $CUDAHOME/bin and $GPGPUSIM_ROOT/bin to your PATH + (e) Add $GPGPUSIM_ROOT/lib/ to your LD_LIBRARY_PATH and remove $CUDAHOME/lib + or $CUDAHOME/lib64 from LD_LIBRARY_PATH + (f) If using OpenCL, set NVOPENCL_LIBDIR to the installation directory of + libOpenCL.so distributed with the NVIDIA OpenCL driver. + On SuSe 11.1 64-bit NVIDIA's libOpenCL.so is installed in /usr/lib64/. + +Step 5: Type "make" in this directory. This will build the simulator with +optimizations enabled so the simulator runs faster. If you want to run the +simulator in gdb to debug it, then build it using "make DEBUG=1" instead. + +Step 6: Run a CUDA built with a recent version of CUDA (or an OpenCL +application) and the device code should now run on the simulator instead of +your graphics card. To be able to run the application on your graphics card +again, remove $GPGPUSIM_ROOT/lib from your LD_LIBRARY_PATH. There is also a +"static" build setup used for some of the examples in the benchmarks directory +(more information on this is available in doc/GPGPU-Sim_Manual.html) + +By default, this version of GPGPU-Sim uses the ptx source embedded within the +binary. To use the .ptx files in the current directory, type: + + export PTX_SIM_USE_PTX_FILE=1 + +Note that for OpenCL applications the NVIDIA driver is required to convert +OpenCL ".cl" files to PTX. The resulting PTX can be saved to disk by adding +-save_embedded_ptx to your gpgpusim.config file (embedded PTX files with be +saved as _0.ptx, _1.ptx, etc...). + +3. USING THE SIMULATOR + +For guidelines on using and configuring the simulator, please see +doc/GPGPU-Sim_Manual.html |