Register Caching for Stencil Computations on GPUs

Author(s):  
Thomas L. Falch ◽  
Anne C. Elster
Keyword(s):  
2016 ◽  
Vol 51 (6) ◽  
pp. 711-726 ◽  
Author(s):  
Shoaib Kamil ◽  
Alvin Cheung ◽  
Shachar Itzhaky ◽  
Armando Solar-Lezama
Keyword(s):  

SIAM Review ◽  
2009 ◽  
Vol 51 (1) ◽  
pp. 129-159 ◽  
Author(s):  
Kaushik Datta ◽  
Shoaib Kamil ◽  
Samuel Williams ◽  
Leonid Oliker ◽  
John Shalf ◽  
...  

2015 ◽  
Vol 2 (1) ◽  
pp. 1-33 ◽  
Author(s):  
Adam Hammouda ◽  
Andrew R. Siegel ◽  
Stephen F. Siegel

Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1275
Author(s):  
Changdao Du ◽  
Yoshiki Yamaguchi

Due to performance and energy requirements, FPGA-based accelerators have become a promising solution for high-performance computations. Meanwhile, with the help of high-level synthesis (HLS) compilers, FPGA can be programmed using common programming languages such as C, C++, or OpenCL, thereby improving design efficiency and portability. Stencil computations are significant kernels in various scientific applications. In this paper, we introduce an architecture design for implementing stencil kernels on state-of-the-art FPGA with high bandwidth memory (HBM). Traditional FPGAs are usually equipped with external memory, e.g., DDR3 or DDR4, which limits the design space exploration in the spatial domain of stencil kernels. Therefore, many previous studies mainly relied on exploiting parallelism in the temporal domain to eliminate the bandwidth limitations. In our approach, we scale-up the design performance by considering both the spatial and temporal parallelism of the stencil kernel equally. We also discuss the design portability among different HLS compilers. We use typical stencil kernels to evaluate our design on a Xilinx U280 FPGA board and compare the results with other existing studies. By adopting our method, developers can take broad parallelization strategies based on specific FPGA resources to improve performance.


Author(s):  
Hikmet Dursun ◽  
Ken-ichi Nomura ◽  
Liu Peng ◽  
Richard Seymour ◽  
Weiqiang Wang ◽  
...  

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