在動物細胞中，有許多大大小小的離子蛋白質通道，並且我們使用很重要的蛋白質通道之一，即瞬時受體電位陽離子通道（TRPV1）。在本文中，我們使用SOR 和BiCG 的演算法來測試加速速率，因此再次證實BiCG 優於SOR。在本文的最後，我們使用由泊松-能斯特-普朗克-費米模型（PFNP）模擬的TRPV1 離子通道來測試CPU 和GPU 的加速速度，然後使用BiCG 演算法找到可加速6.2 倍。

Among animal cells, there are many large and small ionic protein channels, and we have used one of the important protein channels, the Transient Receptor Potential Cation Channel (TRPV1). In this paper, we used Successive Over Relaxation (SOR) and BiConjugate Gradient (BiCG) algorithms to test the accelerating rate, and therefore once again confirmed that BiCG is better than SOR. At the end of this paper, we use the TRPV1 ion channel simulated by the Poisson-Nernst-Planck-Fermi model (PFNP) to test the acceleration rate of the CPU and GPU after using the BiCG algorithm to find the acceleration 6.2 times.

Contents
摘要------------------------------------------------------I
Abstract-------------------------------------------------II
1 Introduction--------------------------------------------1
2 Transient Receptor Potential Cation Channel TRPV1-------2
3 Successive Over Relaxation Method-----------------------3
4 BiConjugate Gradient Method-----------------------------6
5 Poisson-Nernst-Planck-Fermi Nonlinear Solver------------8
6 Results------------------------------------------------13
7 Summary------------------------------------------------16
References-----------------------------------------------17

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