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Hi, I suppose this is less of issue and more of an open question.
I am trying to run several centrifuge processes over a period of time, but from only one index. So ideally I'd like to load the index and then have all the processes reference that one index during classification. I have limited memory and processing power, so I was looking at the --mm option. However I was a little unclear on how it works.
Does using the --mm flag mean that a centrifuge-class process loads the index into memory and then any subsequent classification process use that pre-loaded index once that process is finished, or do they share it in real time?
Once the classifications are finished I assume the index is removed from memory. Is there a way to leave it loaded?
Also, can someone explain how --mm works if the index doesn't fit into memory? Is the index placed into virtual memory instead?
I know that's a lot of questions, so I appreciate any help!
Thank you
Rory
The text was updated successfully, but these errors were encountered:
Hi, I suppose this is less of issue and more of an open question.
I am trying to run several centrifuge processes over a period of time, but from only one index. So ideally I'd like to load the index and then have all the processes reference that one index during classification. I have limited memory and processing power, so I was looking at the --mm option. However I was a little unclear on how it works.
Does using the --mm flag mean that a centrifuge-class process loads the index into memory and then any subsequent classification process use that pre-loaded index once that process is finished, or do they share it in real time?
Once the classifications are finished I assume the index is removed from memory. Is there a way to leave it loaded?
Also, can someone explain how --mm works if the index doesn't fit into memory? Is the index placed into virtual memory instead?
I know that's a lot of questions, so I appreciate any help!
Thank you
Rory
The text was updated successfully, but these errors were encountered: