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NVIDIA Compute Visual Profiler 
Linux Release Notes
Version 3.2
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PLEASE REFER EULA.txt FOR THE LICENSE AGREEMENT FOR USING NVIDIA SOFTWARE.

Please refer Changelog.txt for changes with respect to the previous version.

FILES IN THE RELEASE:
--------------------
* computeprof/bin/computeprof    : Compute Visual Profiler Executable

* computeprof/bin/libQt*.so.4    : Qt shared libraries

* computeprof/projects           : Directory containing sample profiler projects

* computeprof/doc                : Directory containing files for user documentation.


SUPPORTED LINUX DISTRIBUTIONS
-----------------------------
Compute Visual Profiler platform support is same as  that for the CUDA Toolkit. 
Please refer the CUDA Toolkit Linux release notes.


SYSTEM REQUIREMENTS
-------------------
. CUDA-enabled GPU
  See http://www.nvidia.com/object/cuda_learn_products.html
. NVIDIA Driver
. NVIDIA CUDA Toolkit


INSTALLATION AND SETUP
---------------------
The installation is part of the CUDA toolkit installation. The files are
installed under "<CudaToolkitDir>/computeprof" where <CudaToolkitDir> is the 
directory under which the CUDA Toolkit is installed.

Setup LD_LIBRARY PATH to include the ComputeVisualProfiler bin directory:
 > export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:<CudaToolkitDir>/computeprof/bin


RUNNING Compute Visual Profiler
----------------------------
 > <CudaToolkitDir>/computeprof/bin/computeprof &

Refer the Compute Visual Profiler User Guide "Compute_Visual_Profiler_User_Guide.pdf" for more information.


KNOWN ISSUES
------------
1) Following are some issues related to profiler counters:
   . "warp serialize" counter for GPUs with compute capability 1.x is known to 
     give incorrect and high values for some cases.

   . "divergent branch" counter for GPUs with compute capability 2.0 is known to
      give an incorrect value zero for some cases.

   . For GPUs with compute capability 2.0 the "instructions issued" and
     "instructions executed" counter values are incorrect for some cases.
  
2) If some OpenCL resources (contexts, events, etc.) are not released in the program, 
   the profiler output may be incomplete or empty and Visual profiler will report 
   the message ‘Error in reading profiler output'. The program needs to be
   modified to properly free up all OpenCL resources before termination.

3) You need to use the command line argument "--noprompt" for running most
   of the CUDA/OpenCL SDK samples. You can enable the "Run in separate window"
   checkbox in the Session settings dialog to open a separate window.
   Only with this option you can give some keyboard input for console-based
   CUDA/OpenCL programs.

4) The total memory size shown on the GPU device properties dialog is incorrect for
   devices having more than 4 GB of device memory.