Efficient Algorithm Design of Optimizing SpMV on GPU

Author:

Chu Genshen1ORCID,He Yuanjie1ORCID,Dong Lingyu1ORCID,Ding Zhezhao1ORCID,Chen Dandan1ORCID,Bai He1ORCID,Wang Xuesong2ORCID,Hu Changjun1ORCID

Affiliation:

1. University of Science and Technology Beijing, Beijing, China

2. China Institute of Atomic Energy, Beijing, China

Funder

National Key R&D Program of China

Publisher

ACM

Reference41 articles.

1. Sarah AlAhmadi , Thaha Muhammed , Rashid Mehmood , and Aiiad Albeshri . 2020. Performance Characteristics for Sparse Matrix-Vector Multiplication on GPUs . In Smart Infrastructure and Applications, Rashid Mehmood, Simon See, Iyad Katib, and Imrich Chlamtac (Eds.). Springer International Publishing , Cham, 409--426. https://doi.org/10.1007/978--3-030--13705--2_17 Series Title: EAI/Springer Innovations in Communication and Computing. 10.1007/978--3-030--13705--2_17 Sarah AlAhmadi, Thaha Muhammed, Rashid Mehmood, and Aiiad Albeshri. 2020. Performance Characteristics for Sparse Matrix-Vector Multiplication on GPUs. In Smart Infrastructure and Applications, Rashid Mehmood, Simon See, Iyad Katib, and Imrich Chlamtac (Eds.). Springer International Publishing, Cham, 409--426. https://doi.org/10.1007/978--3-030--13705--2_17 Series Title: EAI/Springer Innovations in Communication and Computing.

2. An efficient sparse matrix-vector multiplication on CUDA-enabled graphic processing units for finite element method simulations

3. Accelerating Machine Learning on Sparse Datasets with a Distributed Memory Vector Architecture

4. Arash Ashari , Naser Sedaghati , John Eisenlohr , Srinivasan Parthasarath , and P. Sadayappan . 2014 . Fast Sparse Matrix-Vector Multiplication on GPUs for Graph Applications. In SC14: International Conference for High Performance Computing, Networking, Storage and Analysis. IEEE , New Orleans, LA, USA, 781--792. https://doi.org/10.1109/SC. 2014 .69 10.1109/SC.2014.69 Arash Ashari, Naser Sedaghati, John Eisenlohr, Srinivasan Parthasarath, and P. Sadayappan. 2014. Fast Sparse Matrix-Vector Multiplication on GPUs for Graph Applications. In SC14: International Conference for High Performance Computing, Networking, Storage and Analysis. IEEE, New Orleans, LA, USA, 781--792. https://doi.org/10.1109/SC.2014.69

5. Implementing sparse matrix-vector multiplication on throughput-oriented processors

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