Hardware Execution and Acceleration of Artificial Intelligence-Based Base Caller

A computer-implemented method for analysis of base call sensor output, comprising:

• storing tile data in memory including arrays of sensor data for tiles from sensing cycles of a base calling operation;
• and
• executing a neural network over the tile data using a plurality of execution clusters, including:
• providing input units of tile data to available execution clusters in the plurality of execution clusters, the input units including a number N of spatially aligned patches of arrays of tile data from respective sensing cycles, including a subject sensing cycle, and causing the execution clusters to apply the N spatially aligned patches to the neural network to produce output patches of classification data for the spatially aligned patch of the subject sensing cycle, where N is greater than 1.

A computer-implemented method for analysis of base call sensor output, comprising:

• storing tile data in memory including sensor data for a tile from sensing cycles of a base calling operation;
• executing runs of a neural network using trained parameters to produce classification data for sensing cycles, a run of the neural network operating on a sequence of N arrays of tile data from respective sensing cycles of N sensing cycles, including a subject cycle, to produce the classification data for the subject cycle;
• and
• moving tile data and the trained parameters from memory to the neural network for runs of the neural network using input units including data for spatially aligned patches of the N arrays from respective sensing cycles of N sensing cycles.