Systolic similarity estimation with two-dimensional sliding window

A systolic array implemented in circuitry of an integrated circuit, comprising:

• a plurality of processing elements, wherein each of the plurality of processing elements receives a first data stream comprising a row of a first dataset having samples Am,n and a second data stream comprising a row of a second dataset having samples Bk,l over a plurality of computing cycles that output a plurality of values to construct a two-dimensional sliding window, wherein each of the plurality of processing elements comprises:
• a first circuitry to compute an absolute value of an intrapair between the first data stream and the second data stream;
• a second circuitry to compute a difference between row indices m and k of the samples Am,n and the samples Bk,l, wherein the difference provides an indication of a correspondence between the intrapair and the two-dimensional sliding window;
• and
• an accumulator array to accumulate computed results from the first circuitry based on the indication.

A method to determine similarity between two datasets, comprising:

• loading samples Am,n of a first dataset via a first data loading scheme, one row at a time, to a processing element of a systolic array comprising an array of processing elements, one processing element at a time;
• loading samples Bk,l of a second dataset via a second data loading scheme, in conjunction with loading the samples Am,n to the processing element, one row at a time and one processing element at a time, wherein the second data loading scheme comprises:
• loading a first row of the samples Bk,l, wherein the first row of the samples Bk,l have a row index and a column index equal to a first corresponding row index and a first corresponding column index of the samples Am,n;
• and
• replacing the first row of the samples Bk,l with a second row of the samples Bk,l, wherein the second row of the samples Bk,l have a row index and a column index equal to a second corresponding row index and a second corresponding column index of the samples Am,n;
• and
• computing a sum of absolute difference (SAD) value at each processing element.