Accelerating aerial image simulation using improved CPU/GPU collaborative computing

被引:4
|
作者
Zhang, Fan [1 ]
Hu, Chen [1 ]
Wu, Pei-Ci [2 ]
Zhang, Hongbo [3 ]
Wong, Martin D. F. [2 ]
机构
[1] Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing 100029, Peoples R China
[2] Univ Illinois, Dept Elect & Comp Engn, Urbana, IL USA
[3] Synopsys Inc, Mountain View, CA USA
基金
美国国家科学基金会;
关键词
Lithography simulation; Collaborative computing; Dynamic task scheduling; Advanced vector extensions; CPU parallel;
D O I
10.1016/j.compeleceng.2015.05.018
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Aerial image simulation is a fundamental problem in advanced lithography for chip fabrication. Since it requires a huge number of mathematical computations, an efficient yet accurate implementation becomes a necessity. In the literature, graphic processing unit (GPU) or multi-core single instruction multiple data (SIMD) CPU has demonstrated its potential for accelerating simulation. However, the combination of GPU and multi-core SIMD CPU was not exploited thoroughly. In this paper, we present and discuss collaborative computing algorithms for the aerial image simulation on multi-core SIMD CPU and CPU. Our improved method achieves up to 160x speedup over the baseline serial approach and outperforms the state-of-the-art GPU-based approach by up to 4x speedup with a hex-core SIMD CPU and Tesla 1(10 GPU. We show that the performance on the collaborative computing is promising, and the medium-grained task scheduling is suitable for improving the collaborative efficiency. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:176 / 189
页数:14
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