File	Date	Author	Commit
corunner	2013-10-25	zwsun	[9ca02c] show status in place
README	2013-10-03	zwsun	[4b84ec] Impose an END signal for a normal termination

Read Me

Description:
	This is a framework to execute programs in multiple nodes concurrently.
	It consists of two modules: controller and executor. The controller controls the whole process, it first dispatches the executor 
and user-defined program files to all the nodes specified by the user. Then it starts the executor remotely and waits for all the executors 
to end. The executor run the program specified by the user and reports to the controller peroidly. When it finishes, it notifys the 
controller and then exits. After all the executors have reported their status or a speicified timeout is reached, the controller exits. 
The user can then send another request to pull the results. 
	To monitor every executor's status, the executor reports to the controller peroidly. When one executor fails to report in a 
predefined timeout, the controller will mark it as dead. And if the controller receives the report later, it changes the status to be alive 
again. The controller never waits for a dead node.

Features:
	Heart beat monitor
	Complete parallel execution
	Easy tool for cloning files
	Agile and simple: 
		unlike program in other languages, this is simple and the executor is only one single file.
	Minimal resource exhaustion: 
		the execution is distributed in all nodes, and the controller exausted little resource(mainly for monitor heartbeat)

Environment:
	This is just tested on python2.7 and python2.6 in linux environment.
	And it based on ssh and scp for net communication, before your exection, you should authenticated your controller with all executors.

Commands:
	corunner-run:	to run program in multiple nodes concurrently.
	corunner-cp:	to dispatch files from or to multiple nodes concurrently.

Example:
	1. Execute the myscript in all machines from 192.168.101 to 192.168.200 conrrently with heartbeat switched off:
	   Run in controller: corunner-run -n 192.168.100.101..200 -f myscript -r "/tmp/corunner" -i 1 python /tmp/corunner/myscript
	2. Collect all output files from above to the controller and put in seperated directory:
	   Run in controller: corunner-cp -n 192.168.100.101..200 -i -s /tmp/corunner/ouput -d /temp/corunner/all --divide

Other:
	If you have any problem or suggestion, welcome to contact me, my email is zwsun<sun33170161@gmail.com>. I'm pleasant if it can help 
you and improve your efficiency when working with many machines.