#!/usr/bin/python
#
# File: aerialvision.py
# 
# Copyright (C) 2009 by Aaron Ariel, Tor M. Aamodt, Andrew Turner 
# and the University of British Columbia, Vancouver, 
# BC V6T 1Z4, All Rights Reserved.
# 
# THIS IS A LEGAL DOCUMENT BY DOWNLOADING GPGPU-SIM, YOU ARE AGREEING TO THESE
# TERMS AND CONDITIONS.
# 
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNERS OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
# 
# NOTE: The files libcuda/cuda_runtime_api.c and src/cuda-sim/cuda-math.h
# are derived from the CUDA Toolset available from http://www.nvidia.com/cuda
# (property of NVIDIA).  The files benchmarks/BlackScholes/ and 
# benchmarks/template/ are derived from the CUDA SDK available from 
# http://www.nvidia.com/cuda (also property of NVIDIA).  The files from 
# src/intersim/ are derived from Booksim (a simulator provided with the 
# textbook "Principles and Practices of Interconnection Networks" available 
# from http://cva.stanford.edu/books/ppin/). As such, those files are bound by 
# the corresponding legal terms and conditions set forth separately (original 
# copyright notices are left in files from these sources and where we have 
# modified a file our copyright notice appears before the original copyright 
# notice).  
# 
# Using this version of GPGPU-Sim requires a complete installation of CUDA 
# which is distributed seperately by NVIDIA under separate terms and 
# conditions.  To use this version of GPGPU-Sim with OpenCL requires a
# recent version of NVIDIA's drivers which support OpenCL.
# 
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# 
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
# 
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
# 
# 3. Neither the name of the University of British Columbia nor the names of
# its contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
# 
# 4. This version of GPGPU-SIM is distributed freely for non-commercial use only.  
#  
# 5. No nonprofit user may place any restrictions on the use of this software,
# including as modified by the user, by any other authorized user.
# 
# 6. GPGPU-SIM was developed primarily by Tor M. Aamodt, Wilson W. L. Fung, 
# Ali Bakhoda, George L. Yuan, at the University of British Columbia, 
# Vancouver, BC V6T 1Z4
 
import sys
import os

if not os.environ['HOME']:
	print('please set your HOME environment variable to your home directory')
	sys.exit
if not os.environ['GPGPUSIM_ROOT']:
	print('please set your GPGPUSIM_ROOT environment variable to your home directory')
	sys.exit

sys.path.append( os.environ['GPGPUSIM_ROOT'] + '/aerialvision/' ) 

import tkinter as Tk
import Pmw
import startup
import time

from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2Tk
from matplotlib.figure import Figure

startup.fileInput(sys.argv[1:])