Increasing performance of write throughput using machine learning

A system comprising:

• a processor;
• and
• a memory comprising code stored thereon that, when executed, performs a method of processing data comprising:
• determining a first amount denoting an amount of write pending data stored in cache to be redirected through storage class memory (SCM) when destaging cached write pending data from the cache;
• performing first processing that destages write pending data from the cache, the first processing including:
• selecting, in accordance with the first amount, a first portion of write pending data that is destaged from the cache and stored in the SCM and a second portion of write pending data that is destaged directly from the cache and stored on one or more physical storage devices providing back-end non-volatile physical storage;
• and
• subsequent to storing the first portion of write pending data to the SCM, transferring the first portion of write pending data from the SCM to the one or more physical storage devices providing back-end non-volatile physical storage;
• determining, using a Markov chain state machine (MCSM) included in a predictor, a predicted probabilistic risk of transitioning from a current state to a high state of heavy write throughput;
• and
• providing the probabilistic risk from the predictor as an input to a controller, wherein the MCSM uses a matrix of state transition probabilities to determine the predicted probabilistic risk of transitioning from the current state to the high state of heavy write throughput.

A non-transitory computer readable medium comprising code stored thereon that, when executed, performs a method of processing data comprising:

• determining a first amount denoting an amount of write pending data stored in cache to be redirected through storage class memory (SCM) when destaging cached write pending data from the cache;
• performing first processing that destages write pending data from the cache, the first processing including:
• selecting, in accordance with the first amount, a first portion of write pending data that is destaged from the cache and stored in the SCM and a second portion of write pending data that is destaged directly from the cache and stored on one or more physical storage devices providing back-end non-volatile physical storage;
• and
• subsequent to storing the first portion of write pending data to the SCM, transferring the first portion of write pending data from the SCM to the one or more physical storage devices providing back-end non-volatile physical storage;
• determining, using a Markov chain state machine (MCSM) included in a predictor, a predicted probabilistic risk of transitioning from a current state to a high state of heavy write throughput;
• and
• providing the probabilistic risk from the predictor as an input to a controller, wherein the MCSM uses a matrix of state transition probabilities to determine the predicted probabilistic risk of transitioning from the current state to the high state of heavy write throughput.