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Evaluating Non-square Sparse Bilinear Forms on Multiple Vector Pairs in the I/O-Model

机译:在I / O模型中评估多个向量对上的非平方稀疏双线性形式

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We consider evaluating one bilinear form defined by a sparse N_y x N_x matrix A having h entries on w pairs of vectors The model of computation is the semiring I/O-model with main memory size M and block size B. For a range of low densities (small h), we determine the I/O-complexity of this task for all meaningful choices of N_x, N_y, w, M and B, as long as M > B~2 (tall cache assumption). To this end, we present asymptotically optimal algorithms and matching lower bounds. Moreover, we show that multiplying the matrix A with w vectors has the same worst-case I/O-complexity.
机译:我们考虑评估由稀疏的N_y x N_x矩阵A定义的一种双线性形式,该矩阵A在w对向量上具有h个条目。计算模型是具有主存储器大小M和块大小B的半环I / O模型。密度(小h),只要M> B〜2(高缓存假设),我们就为N_x,N_y,w,M和B的所有有意义的选择确定此任务的I / O复杂度。为此,我们提出了渐近最优算法和匹配的下界。此外,我们表明将矩阵A与w向量相乘具有相同的最坏情况I / O复杂度。

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