Abstract
In this paper, we develop a GPGPU acceleration methodology for the Binary-Collision-Approximation based Monte Carlo ion implantation simulation (MCII). Our proposed method avoids the branch-divergence issue which comes from the difference of material crystallinity for the structure with multiple materials. We also introduce an efficient scheme to mitigate the side effect for damage accumulation due to massive parallelization of simulation. Our demonstration of high energy implantation into CIS structure shows almost 40x speed-up compared to CPU implementation of MCII. We conclude that GPU-MCII is effective for acceleration of Monte Carlo simulations with high energy implantation e.g. deep photodiode or well isolation formation.
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