Skew-polynomial-sparse matrix multiplication

Skew-polynomial-sparse matrix multiplication
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斜多项式稀疏矩阵乘法

DOI:
10.1016/j.jsc.2023.102240
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发表时间:
2023
期刊:
J. Symb. Comput.
影响因子:
--
通讯作者:
Xiao
Xiao
中科院分区:
--
文献类型:
--
作者:
Qiao;Ke Ye;Xiao

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基于Q(p− 1)×(p− 1)同构于商斜多项式环的观察,提出了Q上(p− 1)×(p− 1)矩阵乘法的一个新的确定性算法,其中p为素数.该算法的复杂度为O(T ω− 2 p 2),其中T≤ p− 1是由输入矩阵的斜多项式稀疏性决定的参数,ω是矩阵乘法的渐近指数。这里矩阵是斜多项式稀疏的,如果它对应的斜多项式是稀疏的。此外,通过引入随机性,我们还提出了一个复杂度为O <$(t ω− 2 p 2+ p 2 log <$1 ν)的概率算法,其中t≤ p− 1是乘积的斜多项式稀疏性,ν是概率参数。该算法的主要特点是当输入矩阵或其乘积为斜多项式稀疏矩阵时,可加速矩阵乘法运算。
Based on the observation that Q (p− 1)×(p− 1) is isomorphic to a quotient skew polynomial ring, we propose a new deterministic algorithm for (p− 1)×(p− 1) matrix multiplication over Q, where p is a prime number. The algorithm has complexity O (T ω− 2 p 2), where T≤ p− 1 is a parameter determined by the skew-polynomial-sparsity of input matrices and ω is the asymptotic exponent of matrix multiplication. Here a matrix is skew-polynomial-sparse if its corresponding skew polynomial is sparse. Moreover, by introducing randomness, we also propose a probabilistic algorithm with complexity O∼(t ω− 2 p 2+ p 2 log⁡ 1 ν), where t≤ p− 1 is the skew-polynomial-sparsity of the product and ν is the probability parameter. The main feature of the algorithms is the acceleration for matrix multiplication if the input matrices or their products are skew-polynomial-sparse.
DOI: 10.1109/micro50266.2020.00068
发表时间: 2020-10
期刊: 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)
影响因子: --
作者:
Nitish Srivastava;Hanchen Jin;Jie Liu-;D. Albonesi;Zhiru Zhang
通讯作者: Nitish Srivastava;Hanchen Jin;Jie Liu-;D. Albonesi;Zhiru Zhang