#Copyright (c) 2015, Los Alamos National Security, LLC
#All rights reserved.
#
#Copyright 2015. Los Alamos National Security, LLC. This software was produced under U.S. Government contract DE-AC52-06NA25396 for Los Alamos National Laboratory (LANL), which is operated by Los Alamos National Security, LLC for the U.S. Department of Energy. The U.S. Government has rights to use, reproduce, and distribute this software. NEITHER THE GOVERNMENT NOR LOS ALAMOS NATIONAL SECURITY, LLC MAKES ANY WARRANTY, EXPRESS OR IMPLIED, OR ASSUMES ANY LIABILITY FOR THE USE OF THIS SOFTWARE. If software is modified to produce derivative works, such modified software should be clearly marked, so as not to confuse it with the version available from LANL.
#
#Additionally, redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
# Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# 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.
# Neither the name of Los Alamos National Security, LLC, Los Alamos National Laboratory, LANL, the U.S. Government, nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
#THIS SOFTWARE IS PROVIDED BY LOS ALAMOS NATIONAL SECURITY, LLC 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 LOS ALAMOS NATIONAL SECURITY, LLC OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 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.
from SimianPie.simian import Simian
import random, math
simName, startTime, endTime, minDelay, useMPI = "HELLO", 0, 1000000.1, 1, False
simianEngine = Simian(simName, startTime, endTime, minDelay, useMPI)
num_entities = 32
random.seed(0)
class HelloMessage:
def __init__(self, reply_to_id):
self.reply_to_id = reply_to_id
# def __str__(self):
# return "HelloMessage(%s %s)" %(self.source_id, self.dest_id)
class ReplyMessage:
#Additionally, redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
# Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# 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.
# Neither the name of Los Alamos National Security, LLC, Los Alamos National Laboratory, LANL, the U.S. Government, nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
#THIS SOFTWARE IS PROVIDED BY LOS ALAMOS NATIONAL SECURITY, LLC 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 LOS ALAMOS NATIONAL SECURITY, LLC OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 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.
#Author: Nandakishore Santhi
#Date: 23 November, 2014
#Copyright: Open source, must acknowledge original author
#Purpose: PDES Engine in Python, mirroring a subset of the Simian JIT-PDES
# Simple example simulation script
from SimianPie.simian import Simian
import random, math
simName, startTime, endTime, minDelay, useMPI = "PHOLD", 0, 100000, 0.0001, True
simianEngine = Simian(simName, startTime, endTime, minDelay, useMPI)
count = 4
lookahead = minDelay
def exponential(mean):
return -math.log(random.random())/mean
class Node(simianEngine.Entity):
def __init__(self, baseInfo, *args):
super(Node, self).__init__(baseInfo)
def generate(self, *args):
targetId = random.randrange(count)
offset = exponential(1) + lookahead
# Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# 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.
# Neither the name of Los Alamos National Security, LLC, Los Alamos National Laboratory, LANL, the U.S. Government, nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
#THIS SOFTWARE IS PROVIDED BY LOS ALAMOS NATIONAL SECURITY, LLC 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 LOS ALAMOS NATIONAL SECURITY, LLC OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 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.
#Author: Nandakishore Santhi
#Date: 23 November, 2014
#Copyright: Open source, must acknowledge original author
#Purpose: PDES Engine in Python, mirroring a subset of the Simian JIT-PDES
# Simple example simulation scipt
from SimianPie.simian import Simian
import random, math
#Initialize Simian
simName, startTime, endTime, minDelay, useMPI = "HELLO", 0, 100000, 0.0001, True
simianEngine = Simian(simName, startTime, endTime, minDelay, useMPI,
"/usr/lib/libmpich.so.12")
#simianEngine = Simian(simName, startTime, endTime, minDelay, useMPI)
count = 4
class Alice(simianEngine.Entity):
def __init__(self, baseInfo, *args):
super(Alice, self).__init__(baseInfo)
def generate(self, *args):
targets = [{
"entity": "Alice",
"service": "square"
}, {
"entity": "Bob",
#Additionally, redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
# Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# 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.
# Neither the name of Los Alamos National Security, LLC, Los Alamos National Laboratory, LANL, the U.S. Government, nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
#THIS SOFTWARE IS PROVIDED BY LOS ALAMOS NATIONAL SECURITY, LLC 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 LOS ALAMOS NATIONAL SECURITY, LLC OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 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.
#Author: Nandakishore Santhi
#Date: 23 November, 2014
#Copyright: Open source, must acknowledge original author
#Purpose: PDES Engine in Python, mirroring a subset of the Simian JIT-PDES
# Simple example simulation script
from SimianPie.simian import Simian
import random, math
simName, startTime, endTime, minDelay, useMPI = "PHOLD", 0, 100000, 0.0001, True
simianEngine = Simian(simName, startTime, endTime, minDelay, useMPI)
#simianEngine = Simian(simName, startTime, endTime, minDelay, useMPI, mpiLibName="/Users/nsanthi/Work/Lua/PDES/Lua/x86-64-ompi/lib/libmpi.dylib")
simianEngine = Simian(
simName,
startTime,
endTime,
minDelay,
useMPI,
mpiLibName=
"/Users/nsanthi/Work/Lua/PDES/Lua/x86-64-mpich/lib/libmpich.dylib")
count = 4
lookahead = minDelay
def exponential(mean):
# Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# 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.
# Neither the name of Los Alamos National Security, LLC, Los Alamos National Laboratory, LANL, the U.S. Government, nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
#THIS SOFTWARE IS PROVIDED BY LOS ALAMOS NATIONAL SECURITY, LLC 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 LOS ALAMOS NATIONAL SECURITY, LLC OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 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.
#Author: Nandakishore Santhi
#Date: 23 November, 2014
#Copyright: Open source, must acknowledge original author
#Purpose: PDES Engine in Python, mirroring a subset of the Simian JIT-PDES
# Simple example simulation scipt
from SimianPie.simian import Simian
import random, math
#Initialize Simian
simName, startTime, endTime, minDelay, useMPI = "HELLO", 0, 100000, 0.0001, True
simianEngine = Simian(simName, startTime, endTime, minDelay, useMPI)
count = 4
class Alice(simianEngine.Entity):
def __init__(self, baseInfo, *args):
super(Alice, self).__init__(baseInfo)
def generate(self, *args):
targets = [{"entity": "Alice", "service": "square"},
{"entity": "Bob", "service": "sqrt"}]
target = targets[int(random.randrange(len(targets)))]
targetId = int(random.randrange(count))
data = random.randrange(100)
#Additionally, redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
# Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# 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.
# Neither the name of Los Alamos National Security, LLC, Los Alamos National Laboratory, LANL, the U.S. Government, nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
#THIS SOFTWARE IS PROVIDED BY LOS ALAMOS NATIONAL SECURITY, LLC 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 LOS ALAMOS NATIONAL SECURITY, LLC OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 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.
#Author: Nandakishore Santhi
#Date: 23 November, 2014
#Copyright: Open source, must acknowledge original author
#Purpose: PDES Engine in Python, mirroring a subset of the Simian JIT-PDES
# Simple example simulation script
from SimianPie.simian import Simian
import random, math
simName, startTime, endTime, minDelay, useMPI = "PHOLD-NOOP", 0, 100000, 0.0001, True
simianEngine = Simian(simName, startTime, endTime, minDelay, useMPI)
count = 10
lookahead = minDelay
def exponential(mean):
return -math.log(random.random()) / mean
class Node(simianEngine.Entity):
def __init__(self, baseInfo, *args):
super(Node, self).__init__(baseInfo)
def generate(self, *args):
targetId = random.randrange(count)
# Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# 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.
# Neither the name of Los Alamos National Security, LLC, Los Alamos National Laboratory, LANL, the U.S. Government, nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
#THIS SOFTWARE IS PROVIDED BY LOS ALAMOS NATIONAL SECURITY, LLC 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 LOS ALAMOS NATIONAL SECURITY, LLC OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 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.
#Author: Nandakishore Santhi
#Date: 23 November, 2014
#Copyright: Open source, must acknowledge original author
#Purpose: PDES Engine in Python, mirroring a subset of the Simian JIT-PDES
# Simple example simulation script for many application processes
from SimianPie.simian import Simian
import random
#Initialize Simian
simName, startTime, endTime, minDelay, useMPI = "GREEN", 0, 50000000, 0.0001, True
simianEngine = Simian(simName, startTime, endTime, minDelay, useMPI)
count = int(1e5)
maxSleep = 100
#Example of a process on an entity
def appProcess(this): #Here arg(1) "this" is current process
entity = this.entity
entity.out.write("Process App started\n")
while True:
x = random.randrange(0, maxSleep)
entity.out.write("Time " + str(entity.engine.now) \
+ ": Process " + this.name + " is sleeping for " + str(x) + "\n")
this.sleep(x)
entity.out.write("Time " + str(entity.engine.now) \
+ ": Waking up Process " + this.name + "\n")
# Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# 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.
# Neither the name of Los Alamos National Security, LLC, Los Alamos National Laboratory, LANL, the U.S. Government, nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
#THIS SOFTWARE IS PROVIDED BY LOS ALAMOS NATIONAL SECURITY, LLC 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 LOS ALAMOS NATIONAL SECURITY, LLC OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 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.
#Author: Nandakishore Santhi
#Date: 23 November, 2014
#Copyright: Open source, must acknowledge original author
#Purpose: PDES Engine in Python, mirroring a subset of the Simian JIT-PDES
# Simple example simulation scipt to test runtime attaching of services
from SimianPie.simian import Simian
import random, math
#Initialize Simian
simName, startTime, endTime, minDelay, useMPI = "HELLO-ATTACH", 0, 100000, 0.0001, True
simianEngine = Simian(simName, startTime, endTime, minDelay, useMPI)
count = 4
class Alice(simianEngine.Entity):
def __init__(self, baseInfo, *args):
super(Alice, self).__init__(baseInfo)
def generate(self, *args):
targets = [{"entity": "Alice", "service": "square"},
{"entity": "Bob", "service": "sqrt"}]
target = targets[int(random.randrange(len(targets)))]
targetId = int(random.randrange(count))
data = random.randrange(100)
from SimianPie.simian import Simian
simName, startTime, endTime, minDelay, useMPI = "Simulation", 0, 999999999999999999999, 0.0001, True
#simEngine = Simian(simName, startTime, endTime, minDelay, useMPI, "/usr/local/lib/libmpich.so")
simEngine = Simian(simName, startTime, endTime, minDelay, False)
class BBNode(simEngine.Entity):
def __init__(self, baseInfo, *args):
super(BBNode, self).__init__(baseInfo)
self.bbID = args[0]
self.writeBw = 100
self.wakeRetval = [-99]
self.nodeToExecute = dict()
self.shareCnt = 2 #pre set to 2(2 requests)
#initialize two executor processes to process two requests from two compude nodes
for i in range(2):
nodeID = i
procName = "cpWrite_" + str(nodeID)
print("** New process: " + procName)
reqSize = 100000
self.createProcess(procName, self.cpWrite)
self.startProcess(procName, procName, 0, nodeID, reqSize)
#add to node-to-proc dictionary
procList = None
if nodeID in self.nodeToExecute:
procList = self.nodeToExecute[nodeID]
else:
procList = []
import random
import array
from load import Load, LoadPacket, LoadData, IntervalData, MPIData, MPIRecvData, MPIBcastData, MPIBarrierData # zzz
from SimianPie.simian import Simian
import clusters
import nodes
import router
import interface
import sys
from parameters import *
from genconfig import topologyGenerator
simName, startTime, endTime, minDelay, useMPI = "intconnsim", 0.0, 100.0, 0.000000001, True
simianEngine = Simian(simName, startTime, endTime, minDelay, useMPI)
print "Generating torus topology..."
topologyGenerator(interconnect_type, topology_file_name, torus_dim_size_0, torus_dim_size_1, torus_dim_size_2)
print "Finished topology generation..."
debug_parameters = { # need to work on this parameter and concise it...
"printStat": DEBUG_PRINT_INFO,
"printRoute": DEBUG_PACKET_ROUTE,
"linkStat": DEBUG_LINK_STATS,
}
router_parameters = {
"bufferSize": torus_inbuf_size,
"bwX": torus_bandwidth_0,
#Copyright (c) 2015, Los Alamos National Security, LLC
#All rights reserved.
#
#Copyright 2015. Los Alamos National Security, LLC. This software was produced under U.S. Government contract DE-AC52-06NA25396 for Los Alamos National Laboratory (LANL), which is operated by Los Alamos National Security, LLC for the U.S. Department of Energy. The U.S. Government has rights to use, reproduce, and distribute this software. NEITHER THE GOVERNMENT NOR LOS ALAMOS NATIONAL SECURITY, LLC MAKES ANY WARRANTY, EXPRESS OR IMPLIED, OR ASSUMES ANY LIABILITY FOR THE USE OF THIS SOFTWARE. If software is modified to produce derivative works, such modified software should be clearly marked, so as not to confuse it with the version available from LANL.
#
#Additionally, redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
# Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# 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.
# Neither the name of Los Alamos National Security, LLC, Los Alamos National Laboratory, LANL, the U.S. Government, nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
#THIS SOFTWARE IS PROVIDED BY LOS ALAMOS NATIONAL SECURITY, LLC 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 LOS ALAMOS NATIONAL SECURITY, LLC OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 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.
from SimianPie.simian import Simian
import random, math
simName, startTime, endTime, minDelay, useMPI = "HELLO", 0, 1000000.1, 1, False
simianEngine = Simian(simName, startTime, endTime, minDelay, useMPI)
num_entities = 32
random.seed(0)
class HelloMessage:
def __init__(self, reply_to_id):
self.reply_to_id = reply_to_id
# def __str__(self):
# return "HelloMessage(%s %s)" %(self.source_id, self.dest_id)
class ReplyMessage:
pass
