Measure CSP.LMC performance, investigate causes of performance degradation: Further work after SPIKE

This is a clone of SP636 which was converted into a short timeboxed Spike for some initial investigation in PI5.

Serious performance issues have been detected when a realistic number of CSP sub-arrays and other TANGO Servers and Devices are instantiated. The cause has not been identified, it may be inherent to pyTango implementation, caused by sub-optimal container configuration, blocking due to extensive use of forwarded attributes, use of synchronous (as opposed of asynchronous commands) commands. 

These are some of the options that will be explored: 

• Where appropriate replace synchronous with asynchronous commands (in particular when command completion depends on large number of other devices or involves parsing of large JSON  objects). 
• Experiment using CSP.LMC and Mid.CBF images that instantiate large number of TANGO Servers/Devices.
• Experiment with different container configurations.