Abstract We present , a zkSNARK solution for large-scale matrix multiplication. Classical zkSNARK protocols typically underperform in data analytic contexts, hampered by the large size of datasets and the superlinear nature of matrix multiplication. excels in its scalability. The prover time of scales linearly with respect to the number of non-zero elements in the input matrices. For $$n \times n$$ n × n matrix multiplication with N non-zero elements across three input matrices, employs a structured reference string (SRS) of size O ( n ), and achieves RAM usage of $$O(N+n)$$
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