Fast optical and process proximity correction algorithms for integrated circuit manufacturing
Fast optical and process proximity correction algorithms for integrated circuit manufacturing
FPGA-Based Hardware Acceleration of Lithographic Aerial Image Simulation
ACM Transactions on Reconfigurable Technology and Systems (TRETS)
Hardware Acceleration of EDA Algorithms: Custom ICs, FPGAs and GPUs
Hardware Acceleration of EDA Algorithms: Custom ICs, FPGAs and GPUs
Efficient Parallel Graph Exploration on Multi-Core CPU and GPU
PACT '11 Proceedings of the 2011 International Conference on Parallel Architectures and Compilation Techniques
Accelerating aerial image simulation with GPU
Proceedings of the International Conference on Computer-Aided Design
Exploiting State-of-the-Art x86 Architectures in Scientific Computing
ISPDC '12 Proceedings of the 2012 11th International Symposium on Parallel and Distributed Computing
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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, GPU or FPGA has demonstrated its potential for accelerating aerial image simulation. However, the comparisons of GPU or FPGA to CPU were not done thoroughly. In particular, careful tunings for the CPU-based method were missing in the previous works, while the recent CPU architectures have significant modifications toward high performance computing capabilities. In this paper, we present and discuss several algorithms for the aerial image simulation on multi-core SIMD CPU. Our fastest method achieves up to 73X speedup over the baseline serial approach and outperforms the state-of-the-art GPU-based approach by up to 2X speedup on a single hex-core SIMD CPU. We show that the performance on the multi-core SIMD CPU is promising, and that careful CPU tunings are necessary in order to exploit its computing capabilities.