We present a cache-oblivious adaptation of matrix multiplication to be incorporated in the parallel TU decomposition for rectangular matrices over finite fields, based on the Morton-hybrid space-filling curve representation. To realise this, we introduce the concepts of alignment and containment of sub-matrices under the Morton-hybrid layout. We redesign the decompositions within the recursive matrix multiplication to force the base case to avoid all jumps in address space, at the expense of extra recursive matrix multiplication (MM) calls. We show that the resulting cache oblivious adaptation has low span, and our experiments demonstrate that its sequential evaluation order demonstrates orders of magnitude improvement in run-time, despite the recursion overhead.
We examine several matrix layouts based on space-filling curves that allow for a cache-oblivious adaptation of parallel TU decomposition for rectangular matrices over finite fields. The TU algorithm of [11] requires index conversion routines for which the cost to encode and decode the chosen curve is significant. Using a detailed analysis of the number of bit operations required for the encoding and decoding procedures, and filtering the cost of lookup tables that represent the recursive decomposition of the Hilbert curve, we show that the Morton-hybrid order incurs the least cost for index conversion routines that are required throughout the matrix decomposition as compared to the Hilbert, Peano, or Morton orders. The motivation lies in that cache efficient parallel adaptations for which the natural sequential evaluation order demonstrates lower cache miss rate result in
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