ML assisted dynamic decoding gear selection

A controller, comprising:

• a first decoder that operates at a first level;
• a second decoder that operates at a second level below the first level;
• and
• a decoder manager coupled to the first decoder and the second decoder, wherein the decoder manager is configured to:
• training a machine learning (ML) classifier, wherein the training comprises:
• directing encoded data to a first decoder simulation to decode the encoded data;
• decoding, using the first decoder simulation, the encoded data directed to the first decoder simulation;
• during the decoding of the encoded data, calculating a point in the decoding where the encoded data is sufficiently decoded to be able to be decoded by a second decoder simulation, wherein the point is not calculated prior to the decoding of the encoded data;
• determining whether the point has been reached by the first decoder simulation;
• directing the sufficiently decoded data to the second decoder simulation;
• and
• determining whether the second decoder simulation successfully decoded the sufficiently decoded data;
• after determining the second decoder simulation failed to successfully decode the sufficiently decoded data, direct the sufficiently decoded data to the second decoder;
• trigger a recovery flow based on the determination that the second decoder simulation did not successfully decode the sufficiently decoded data;
• and
• if the recovery flow is triggered, bias a conservative working point, wherein the conservative working point is more conservative than the point.

A controller, comprising:

• first means to decode data at a first power efficiency level;
• second means to decode data at a second power efficiency level above the first power efficiency level;
• and
• a decoding manager coupled to the first means to decode data and the second means to decode data, wherein the decoding manager is configured to:
• obtain first decoding information from simulating a decoding of encoded data in the first means to decode data, wherein the obtaining comprises calculating a point during simulating the decoding of the encoded data in the first means to decode data, wherein the point indicates where the encoded data is sufficiently decoded to be able to be decoded by the second means to decode data;
• simulating the decoding of the encoded data in the first means to decode data to the point;
• directing the encoded data decoded to the point to the second means to decode data;
• determining whether the second means to decode data successfully decoded the encoded data decoded to the point;
• and
• create classifier weight and bias based upon a consistency of the first decoding information and the determination whether the second means to decode data successfully decoded the encoded data decoded to the point.