In-memory computing architecture for nearest neighbor search of cosine distance and operating method thereof

An in-memory computing architecture for a nearest neighbor search of a cosine distance, wherein the in-memory computing architecture comprises two FeFET-based storage arrays, Translinear circuits and a WTA circuit, and the two storage arrays are a first storage array and a second storage array, respectively;

• each of the storage arrays comprises a plurality of storage rows, each of the plurality of storage rows is formed by connecting a plurality of storage cells in parallel, wherein each of the storage cell comprises a FeFET and a resistor which are electrically connected, and each storage row in the same storage array stores a different storage vector;
• one storage row in one of the two storage arrays corresponds to one storage row of another one of the two storage arrays, and the storage vectors stored in the two corresponding storage rows are the same;
• an input vector is inputted into the first storage array, for outputting an inner product X of the input vector being multiplied by all the storage vectors in the first storage array;
• the second storage array outputs the sum of squares Y of all vector elements in the storage vectors;
• output values of the first storage array and the second storage array are respectively inputted into the Translinear circuits through current mirrors;
• the Translinear circuits output X2/Y to the WTA circuit;
• and
• the WTA circuit is used to select a maximum X2/Y value from all X2/Y corresponding to all the storage rows, wherein a storage row corresponding to the maximum X2/Y value is a nearest neighbor of the cosine distance between the input vector and all the storage vectors.