Each task runs a genetic program. In desktop, each task takes 5 mins and consumes 250 MB ram. A user-level job consists of 10 such tasks. In desktop ( a normal Windows PC ), It takes about 50 minutes to complete one user-level job.
Can I use App Engine to run the tasks in parallel and achieve a response of ~5 mins for the user-level job ? Specifically, a single http request triggers 10 DeferredTasks. The DeferredTask need not do any datastore operation. Can taskqueue process the DeferredTasks in parallel and handle the 10 DeferredTasks simultaneously? As each DeferredTask runs, it has to notify the progress to the client using Channels API. Is it possible ? Channel being not serializable, how can I keep a channel as a member variable to a DeferredTask? Could you please share your experience in CPU and memory intensive DeferredTasks ? J.Ganesan -- You received this message because you are subscribed to the Google Groups "Google App Engine" group. To post to this group, send email to [email protected]. To unsubscribe from this group, send email to [email protected]. For more options, visit this group at http://groups.google.com/group/google-appengine?hl=en.
