Octopy looks far too simplistic for anything too large. For example, it pushes the entire python source file to the client, including all of the data. It then assigns a client data to process? I've been reading the code for a few minutes and can't imagine using it for anything substantial...
I too prefer to have local processing, but there are times where I also like to farm out jobs to a larger HPC cluster (I'm at a university with 2 large clusters). The downside to this is that I usually have to wait in a job queue.
I guess what I really want is a hybrid approach where I can run jobs locally, but if there are too many, spin up either a loadleveller / pbs job on a university cluster or spin up a few EC2 instances.
I too prefer to have local processing, but there are times where I also like to farm out jobs to a larger HPC cluster (I'm at a university with 2 large clusters). The downside to this is that I usually have to wait in a job queue.
I guess what I really want is a hybrid approach where I can run jobs locally, but if there are too many, spin up either a loadleveller / pbs job on a university cluster or spin up a few EC2 instances.