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相关概念视频

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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在基于混合CPU-GPU架构上的大规模并行张量网络状态算法.

Andor Menczer1,2, Örs Legeza1,3

  • 1Strongly Correlated Systems "Lendület" Research Group, Wigner Research Centre for Physics, H-1525 Budapest, Hungary.

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概括
此摘要是机器生成的。

这项研究增强了用于高性能计算 (HPC) 的张量网络状态 (TNS) 算法,从而实现更大的量子模拟. 新的方法推动了对强烈相关的分子的计算界限.

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科学领域:

  • 计算物理 计算物理
  • 量子化学 是一个量子化学.
  • 高性能计算 高性能计算

背景情况:

  • 张量网络状态 (TNS) 对于模拟量子系统至关重要.
  • 弥合量子和经典模拟需要先进的算法.
  • 高性能计算 (HPC) 对于解决大型量子问题至关重要.

研究的目的:

  • 为TNS算法开发新的算法解决方案.
  • 在HPC基础设施上扩展TNS算法的功能.
  • 利用最先进的硬件和软件进行量子模拟.

主要方法:

  • 大规模并行 TNS 算法.
  • 实施新的算法解决方案.
  • 大规模密度矩阵重规范化组 (DMRG) 模拟.
  • 使用多GPU的NVIDIA A100系统.使用多GPU的NVIDIA A100系统.

主要成果:

  • 在HPC上证明了TNS算法限制的扩展.
  • 实现了对强烈相关的分子系统的基准结果.
  • 成功地解决了直至4.17 × 10^35.35的希尔伯特空间维度.
  • 在先进的硬件上验证了性能.

结论:

  • 新型算法显著提升了HPC上的TNS能力.
  • 开发的方法可以进行前所未有的规模的模拟.
  • 这项工作为未来复杂分子系统的量子模拟提供了途径.