%0 Journal Article
%T Multiplication of medium-density matrices using TensorFlow on multicore CPUs
%A Chongstitvatana
%A Jaruloj
%A Theeracheep
%A Siraphob
%J -
%D 2019
%R 10.31803/tg-20191104183930
%X Sa£żetak Matrix multiplication is an essential part of many applications, such as linear algebra, image processing and machine learning. One platform used in such applications is TensorFlow, which is a machine learning library whose structure is based on dataflow programming paradigm. In this work, a method for multiplication of medium-density matrices on multicore CPUs using TensorFlow platform is proposed. This method, called tbt_matmul, utilizes TensorFlow built-in methods tf.matmul and tf.sparse_matmul. By partitioning each input matrix into four smaller sub-matrices, called tiles, and applying an appropriate multiplication method to each pair depending on their density, the proposed method outperforms the built-in methods for matrices of medium density and matrices of significantly uneven distribution of non-zeros
%K Sparse matrix
%K Matrix multiplication
%K TensorFlow
%U https://hrcak.srce.hr/index.php?show=clanak&id_clanak_jezik=333670