Abstract
In this paper, we report the results obtained from the acceleration of multi-binary64-type multiple precision block and Strassen matrix multiplications with AVX2. We target double-double (DD), triple-double (TD), and quad-double (QD) precision arithmetic designed using certain types of error-free transformation (EFT) arithmetic. Furthermore, we implement SIMDized EFT functions, which simultaneously compute with four binary64 numbers on x86_64 computing environment, and by using help of them, we also develop SIMDized DD, TD, and QD additions and multiplications. In addition, AVX2 load/store functions were adopted to efficiently speed up reading and storing matrix elements from/to memory. Owing to these combined techniques, our implemented multiple precision matrix multiplications were accelerated more than three times compared with non-accelerated ones. Our accelerated matrix multiplication modifies parallelization performance with OpenMP.
Supported by JSPS KAKENHI (Grant Number JP20K11843) and Shizuoka Institute of Science and Technology.
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Kouya, T. (2021). Acceleration of Multiple Precision Matrix Multiplication Based on Multi-component Floating-Point Arithmetic Using AVX2. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12953. Springer, Cham. https://doi.org/10.1007/978-3-030-86976-2_14
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DOI: https://doi.org/10.1007/978-3-030-86976-2_14
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