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High-Performance Sparse Matrix-Multi Vector Multiplication on Multi-Core Architecture

Singh, Kunal
http://orcid.org/0000-0003-4087-3968
http://rave.ohiolink.edu/etdc/view?acc_num=osu1524089757826551

Abstract Details

2018, Master of Science, Ohio State University, Computer Science and Engineering.
SpMM is a widely used primitive in many domains like Fluid Dynamics, Data Analytics, Economic Modelling and Machine Learning. In Machine Learning and Artificial Neural Network domain SpMM is used iteratively and is the main bottleneck in many kernels. Due to its prime importance, many Machine Learning frameworks like Tensorflow, PyTorch, etc offer SpMM as a primitive. When compared to SpMV, SpMM has a higher theoretical operational intensity. However, the fraction of roofline performance achieved by SpMM is lower than SpMV suggesting possible improvements. In this paper, we systematically explore different design choices for SpMM primitive and develop a high-performance SpMM algorithm targeted at Multi-core and Many-core architectures. In addition, we also developed an analytical model to guide the tile size selection. As shown in our experimental section we achieve up to 3.4x speedup when compared to Intel MKL library.
Ponnuswamy Sadayappan (Advisor)
Atanas Rountev (Committee Member)
54 p.
Computer Science
SpMM; SpMDM; Sparse Dense Matrix Multiplication; Multi-core; Many-Core;

Recommended Citations

Citations

  • Singh, K. (2018). High-Performance Sparse Matrix-Multi Vector Multiplication on Multi-Core Architecture [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1524089757826551

    APA Style (7th edition)

  • Singh, Kunal. High-Performance Sparse Matrix-Multi Vector Multiplication on Multi-Core Architecture. 2018. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1524089757826551.

    MLA Style (8th edition)

  • Singh, Kunal. "High-Performance Sparse Matrix-Multi Vector Multiplication on Multi-Core Architecture." Master's thesis, Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1524089757826551

    Chicago Manual of Style (17th edition)

osu1524089757826551
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© 2018, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.