pypto-case-matvec

Matrix-vector multiplication when K exceeds 65535 is handled by substituting matmul with elementwise multiplication followed by a sum reduction, producing C shaped (M, 1) from A shaped (M, K) and B shaped (K, 1).

Handling very large K dimensions in a matrix-vector product is achieved by reshaping B into a row vector to enable broadcasting, then applying elementwise multiplication and reduction instead of standard matmul to avoid failures.

Broadcasting for large-K matrix-vector operations works by transforming B into a row vector, allowing the (M, K) matrix A to be multiplied elementwise with B and then summed to output the (M, 1) result.

Yes, a pypto-based kernel can be used for large-K matvec workloads by utilizing a create_matvec_sum_kernel factory that implements elementwise operations and reduction for validation in testing environments.

Validating a large-K matvec workaround involves running the case with A shaped (256, 131072) and B shaped (131072, 1) through a minimal ModelNew forward path to confirm the elementwise multiplication and sum output.