Optimized neural network data organization

A data storage device, comprising:

• a memory configured to store data;
• and
• a controller coupled to the memory, the controller configured to:
• organize various types of data for a neural network into two or more hierarchies, such that data in different hierarchies is stored in different portions of the memory comprising a plurality of dies;
• and
• selectively store weight data comprising a first and second subset of weights for the neural network, wherein:
• the first subset of weights for the neural network is stored in a first portion of the memory, the neural network comprising a plurality of nodes and a plurality of connections between the plurality of nodes, wherein:
• the first subset of weights comprises weights used by the neural network;
• and
• a first error correction code is used for the first portion of the memory;
• and
• the second subset of weights for the neural network is stored in a second portion of the memory, wherein:
• the second subset of weights comprises prunable weights that, once removed, reduce an amount of data used to store weights for the neural network;
• a second error correction code is used for the second portion of the memory;
• and
• the second error correction code is weaker than the first error correction code;
• wherein copies of the weight data are duplicated across the plurality of dies.

A non-transitory machine-readable medium having executable instructions to cause one or more processing devices to perform operations comprising:

• organizing various types of data for a neural network into two or more hierarchies, such that data in different hierarchies is stored in different portions of memory, the memory comprising a plurality of dies;
• storing weight data comprising a first and second subset of weights for the neural network;
• the first subset of weights for the neural network is stored in a first portion of the memory, the neural network comprising a plurality of nodes and a plurality of connections between the plurality of nodes, wherein:
• the first subset of weights comprises weights used by the neural network;
• and
• a first error correction code is used for the first portion of the memory;
• and
• the second subset of weights for the neural network is stored in a second portion of the memory, wherein:
• more overprovisioning is utilized in the second portion of the memory than in the first portion of the memory;
• the second subset of weights comprises weights that are prunable;
• a second error correction code is used for the second portion of the memory;
• and
• the second error correction code is weaker than the first error correction code,
• wherein copies of the weight data are duplicated across the plurality of dies.