With Elastic, instead of specific use cases, a use case has to be coded by the user of the system in Elastic’s own programming language - Elastic PL. It is similar to C but with limited functionality so it can be guaranteed that Elastic code can be executed on other machines without causing any harm. You can write a program in Elastic PL and be sure that if executed correctly, no exploits, no endless loops, no data leakage.
So while Elastic is more flexible in designing tasks, it does not perform better for one particular use case over other systems. With other super computer models, If you want to do 6 different tasks you need 6 separate use cases. With Elastic you can do them all at once. As the Elastic PL is further developed, so the diversity of tasks will become more complex. Currently, only tasks which explore a search space can be performed, and not tasks which are divided into multiple packages (like rendering divides a large image into many smaller tiles).
Elastic PL will get better over time with the flexibility that Elastic PL provides. The system is built and designed this way from ground up to allow user configurable tasks. This makes Elastic the only system that currently offer this. The potential of Elastic is basically limitless.
we have been quiet lately. Not much to write, only that you can be sure #Elastic devs tend to deliver state of the art platform. #XEL $XEL
Short dev update has been given today by coralreefer (xel_miner dev) - to stay up-to-date track GitHub or join us a…
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