FPGA-Based Hardware Acceleration of Lithographic Aerial Image Simulation

被引:21
|
作者
Cong, Jason [1 ]
Zou, Yi [1 ]
机构
[1] Univ Calif Los Angeles, Dept Comp Sci, Los Angeles, CA 90095 USA
关键词
Algorithms; Performance; Design; Lithography simulation; coprocessor acceleration; FPGA; DESIGN;
D O I
10.1145/1575774.1575776
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Lithography simulation, an essential step in design for manufacturability (DFM), is still far from computationally efficient. Most leading companies use large clusters of server computers to achieve acceptable turn-around time. Thus coprocessor acceleration is very attractive for obtaining increased computational performance with a reduced power consumption. This article describes the implementation of a customized accelerator on FPGA using a polygon-based simulation model. An application-specific memory partitioning scheme is designed to meet the bandwidth requirements for a large number of processing elements. Deep loop pipelining and ping-pong buffer based function block pipelining are also implemented in our design. Initial results show a 15X speedup versus the software implementation running on a microprocessor, and more speedup is expected via further performance tuning. The implementation also leverages state-of-art C-to-RTL synthesis tools. At the same time, we also identify the need for manual architecture-level exploration for parallel implementations. Moreover, we implement the algorithm on NVIDIA GPUs using the CUDA programming environment, and provide some useful comparisons for different kinds of accelerators.
引用
收藏
页数:29
相关论文
共 50 条
  • [41] An FPGA-Based Hardware Architecture of Gaussian-Adaptive Bilateral Filter for Real-Time Image Denoising
    Xie, Ailin
    Zhang, Ao
    Mei, Guohui
    IEEE ACCESS, 2024, 12 : 115277 - 115285
  • [42] A hardware-efficient computing engine for FPGA-based deep convolutional neural network accelerator
    Li, Xueming
    Huang, Hongmin
    Chen, Taosheng
    Gao, Huaien
    Hu, Xianghong
    Xiong, Xiaoming
    MICROELECTRONICS JOURNAL, 2022, 128
  • [43] Active redundant hardware architecture for increased reliability in FPGA-based nuclear reactors critical systems
    Farias, Marcos Santana
    Nedjah, Nadia
    de Carvalho, Paulo Victor R.
    MICROPROCESSORS AND MICROSYSTEMS, 2022, 90
  • [44] FPGA-Based Parallel Hardware Architecture For SIFT Algorithm
    Peng, J. Q.
    Liu, Y. H.
    Lyu, C. Y.
    Li, Y. H.
    Zhou, W. G.
    Fan, K.
    2016 IEEE INTERNATIONAL CONFERENCE ON REAL-TIME COMPUTING AND ROBOTICS (IEEE RCAR), 2016, : 277 - 282
  • [45] Hardware Decompression Techniques for FPGA-Based Embedded Systems
    Koch, Dirk
    Beckhoff, Christian
    Teich, Juergen
    ACM TRANSACTIONS ON RECONFIGURABLE TECHNOLOGY AND SYSTEMS, 2009, 2 (02)
  • [46] Reconfigurable FPGA-based hardware accelerator for embedded DSP
    Rubin, G.
    Omieljanowicz, M.
    Petrovsky, A.
    MIXDES 2007: Proceedings of the 14th International Conference on Mixed Design of Integrated Circuits and Systems:, 2007, : 147 - 151
  • [47] An FPGA-Based Hardware Implementation of Visual based Fall Detection
    Ong, Peng Shen
    Ooi, Chee Pun
    Chang, Yoong Choon
    Karuppiah, Ettikan K.
    Tahir, Shahirina Mohd
    2014 IEEE REGION 10 SYMPOSIUM, 2014, : 397 - 402
  • [48] FPGA-based Implementation of Hardware Technology on Generic Algorithms
    Zhong Wei-sheng
    Wang Yu-Ti
    Zeng Xiao-Shu
    2008 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-11, 2008, : 1333 - +
  • [49] Hardware/software partitioning for FPGA-based security design
    Xu, Cheng
    Wang, Mengzhen
    Qin, Yunchuan
    Yin, Su
    Journal of Computational Information Systems, 2014, 10 (17): : 7407 - 7416
  • [50] FPGA-Based Research on The Hardware Design of CAVLC Encoder
    Xu, Jin
    Mao, Jianhua
    PROCEEDINGS OF THE 2013 INTERNATIONAL CONFERENCE ON INFORMATION, BUSINESS AND EDUCATION TECHNOLOGY (ICIBET 2013), 2013, 26 : 128 - 131