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- Cache aware factorization. Experiments shows that ic,jc factorization based on m,n gives better results compared to mu,nu on a generic data set in SUP path. Also slight adjustments in the factorizations w.r.t matrix data loads can help in improving perf further. - Moving native path inputs to SUP path. Experiments shows that in multi-threaded scenarios if the per thread data falls under SUP thresholds, taking SUP path instead of native path results in improved performance. This is the case even if the original matrix dimensions falls in native path. This is not applicable if A matrix transpose is required. - Enabling B matrix packing in SUP path. Performance improvement is observed when B matrix is packed in cases where gemm takes SUP path instead of native path based on per thread matrix dimensions. AMD-Internal: [CPUPL-659] Change-Id: I3b8fc238a0ece1ababe5d64aebab63092f7c6914