用专用计算机mdgraph -3进行蛋白质x射线结构分析的281 Tflops计算

Y. Ohno, E. Nishibori, T. Narumi, T. Koishi, T. Tahirov, H. Ago, M. Miyano, R. Himeno, T. Ebisuzaki, M. Sakata, M. Taiji
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引用次数: 11

摘要

利用遗传算法-直接空间(GA-DS)方法对x射线实验数据进行蛋白质三维结构优化,实现了281 Tflops的持续计算速度。在此计算中,我们使用mdgraph -3,这是一种用于分子模拟的专用计算机,其峰值性能为752 Tflops。GA-DS方法通过遗传算法对一组选定的蛋白质晶体结构参数进行优化。我们使用可靠度因子R1作为估计模型参数的标准,它表示计算和测量的衍射数据之间的统计差异。为了评估这一因素,有必要在每次更新模型时重建模型结构的衍射图样。因此,在该方法中,用于计算衍射图样的非均衡离散傅立叶变换(DFT)占据了大部分计算时间。为了加速DFT计算,我们使用了专用计算机mdgraph -3。对氨基甲酰磷酸合成酶分子进行了研究。最终的可靠度因子比其他方法(如分子置换法)得到的典型值要小得多。我们的研究结果成功地证明了GA-DS方法在专用计算机上的高性能计算对生物分子结构的确定是有效的,并且该方法在不久的将来具有广泛应用的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A 281 Tflops calculation for X-ray protein structure analysis with special-purpose computers MDGRAPE-3
We have achieved a sustained calculation speed of 281 Tflops for the optimization of the 3-D structures of proteins from the X-ray experimental data by the Genetic Algorithm - Direct Space (GA-DS) method. In this calculation we used MDGRAPE-3, special-purpose computer for molecular simulations, with the peak performance of 752 Tflops. In the GA-DS method, a set of selected parameters which define the crystal structures of proteins is optimized by the Genetic Algorithm. As a criterion to estimate the model parameters, we used the reliability factor R1 which indicates the statistical difference between the calculated and the measured diffraction data. To evaluate this factor it is necessary to reconstruct the diffraction patterns of the model structures every time the model is updated. Therefore, in this method the nonequispaced Discrete Fourier Transformation (DFT) used to calculate the diffraction patterns dominates most of the computation time. To accelerate DFT calculations, we used the special-purpose computer, MDGRAPE-3. A molecule, Carbamoyl-Phosphate Synthetase was investigated. The final reliability factors were much smaller than the typical values obtained in other methods such as the Molecular Replacement (MR) method. Our results successfully demonstrate that high-performance computing with GA-DS method on special-purpose computers is effective for the structure determination of biological molecules and the method has a potential to be widely used in near future.
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