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Accelerating aerial image simulation using improved CPU/GPU collaborative computing
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DOI：10.1016/j.compeleceng.2015.05.018.png)
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Abstract
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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.
Keywords:
Lithography simulation
Collaborative computing
Dynamic task scheduling
Advanced vector extensions
CPU parallel
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