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首页> 外文期刊>Procedia Computer Science >GPGPU Application to the Computation of Hamiltonian Matrix Elements between Non-orthogonal Slater Determinants in the Monte Carlo Shell Model
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GPGPU Application to the Computation of Hamiltonian Matrix Elements between Non-orthogonal Slater Determinants in the Monte Carlo Shell Model

机译:GPGPU在蒙特卡洛壳模型中非正交Slater行列式之间的哈密顿矩阵元素计算中的应用

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We apply the computation with a GPU accelerator to calculate Hamiltonian matrix elements between non-orthogonal Slater determinants utilized in the Monte Carlo shell model. The bottleneck of this calculation is the two-body part in the computation of Hamiltonian matrix elements. We explain an efficient computational method to overcome this bottleneck. For General-Purpose computing on the GPU (GPGPU) of this method, we propose a computational procedure to avoid the unnecessary costs of data transfer into a GPU device and aim for efficient computation with the cuBLAS interface and the OpenACC directive. As a result, we achieve about 40 times better performance in FLOPS as compared with a single-threaded process of CPU for the two-body part in the computation of Hamiltonian matrix elements.
机译:我们使用GPU加速器进行计算,以计算在蒙特卡洛壳模型中使用的非正交Slater行列式之间的哈密顿矩阵元素。该计算的瓶颈是哈密顿矩阵元素的计算中的两体部分。我们解释了一种有效的计算方法来克服这一瓶颈。对于此方法在GPU上进行的通用计算(GPGPU),我们提出了一种计算程序,以避免不必要的数据传输到GPU设备的费用,并旨在通过cuBLAS接口和OpenACC指令进行有效的计算。结果,在汉密尔顿矩阵元素的计算中,与两主体部分的单线程CPU处理相比,我们在FLOPS中实现了约40倍的性能提高。

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