FPGA-Based Hardware Acceleration of Lithographic Aerial Image Simulation

Author:

Cong Jason1,Zou Yi1

Affiliation:

1. University of California, Los Angeles

Abstract

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.

Funder

National Natural Science Foundation of China

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

Reference18 articles.

1. Cobb N. B. 1998. Fast optical and process proximity correction algorithms for integrated circuit manufacturing. Ph.D. thesis University of California Berkeley. Cobb N. B. 1998. Fast optical and process proximity correction algorithms for integrated circuit manufacturing. Ph.D. thesis University of California Berkeley.

2. Lithographic aerial image simulation with FPGA-based hardwareacceleration

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Architecturally truly diverse systems: A review;Future Generation Computer Systems;2020-09

2. An Approach of Hardware and Software Partitioning for the Wearables Design with Limited Reconfigurable Hardware Resources;2018 VIII Brazilian Symposium on Computing Systems Engineering (SBESC);2018-11

3. Soft Core Processor Generated Based on the Machine Code of the Application;Journal of Circuits, Systems and Computers;2016-02-02

4. Heterogeneous Hardware Accelerators with Hybrid Interconnect: An Automated Design Approach;2015 International Conference on Advanced Computing and Applications (ACOMP);2015-11

5. Accelerating aerial image simulation using improved CPU/GPU collaborative computing;Computers & Electrical Engineering;2015-08

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3