Improving blocked matrix-matrix multiplication routine by utilizing AVX-512 instructions on intel knights landing and xeon scalable processors

Author:

Park Yoosang,Kim Raehyun,Nguyen Thi My Tuyen,Choi JaeyoungORCID

Funder

Ministry of Education, Science and Technology

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Software

Reference40 articles.

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2. Geist, A., Reed, D.A.: A survey of high-performance computing scaling challenges. Int. J. High Perform. Comput. Appl. 31, 104–113 (2017)

3. Thoman, P., Dichev, K., Heller, T., Iakymchuk, R., Aguilar, X., Hasanov, K., Gschwandtner, P., Lemarinier, P., Markidis, S., Jordan, H., Fahringer, T., Katrinis, K., Laure, E., Nikolopoulos, D.S.: A taxonomy of task-based parallel programming technologies for high-performance computing. J. SuperComput. 74, 1422–1434 (2018)

4. Basic Linear Algebra Subprograms (BLAS). http://www.netlib.org/blas. Accessed 22 Nov 2020.

5. Parallel Basic Linear Algebra Subprograms (PBLAS). http://www.netlib.org/scalapack/pblas_qref.html. Accessed 22 Nov 2020.

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1. Analyzing Data Reordering of a combined MPI and AVX execution of a Jacobi Method;2023 31st Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP);2023-03

2. Optimization of Matrix-Matrix Multiplication Algorithm for Matrix-Panel Multiplication on Intel KNL;2022 IEEE/ACS 19th International Conference on Computer Systems and Applications (AICCSA);2022-12

3. Seamless optimization of the GEMM kernel for task-based programming models;Proceedings of the 36th ACM International Conference on Supercomputing;2022-06-28

4. A simple and efficient storage format for SIMD-accelerated SpMV;Cluster Computing;2021-06-20

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