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OpenPME: Open Particle Mesh Environment for Systems Biology

OpenPME：系统生物学的开放粒子网格环境

基本信息

批准号：
350008342
负责人：
Professor Dr.-Ing. Jeronimo Castrillon
金额：
--
依托单位：
Institut für Technische Informatik
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2017
资助国家：
德国
起止时间：
2016-12-31 至 2021-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/350008342?language=en
关键词：
OpenPME Open Particle Mesh Environment

项目摘要

Parallel high-performance computing (HPC) is essential to study scientific models of complex real-world phenomena, to accurately predict their behavior and reaction to perturbations, and analyze large data sets of real-world experiments. Particularly challenging applications of this kind arise from the field of systems biology,where complex models of cells and systems of cells are simulated in order to reverse-engineer biological mechanisms. The process of modeling and simulation is driven by high-resolution 3D microscopy images, which also need to be processed in real time. Modeling, simulation, and data analysis hence critically depend on effective use of HPC platforms. Developing robust and versatile numerical methods that run efficiently on parallel HPC hardware, however, is a challenging, error-prone, and time-consuming task. Developers need to understand the problem domain at hand, the mathematical models, as well as the impact of algorithmic specifications on the underlying system architecture and performance. Rarely, all of these intricacies can be dealt with in a given project, hence defining a knowledge gap between the application and the HPC system.In this project, we narrow the gap between a high-level problem description and the final HPC code by introducing transparent layers of abstraction, consisting of: a domain-specific language, a compiler, an adaptive runtime system, and a development environment. We focus on generic particle-mesh methods as the numerical simulation framework, because they can simulate both discrete and continuous models and process images, hence covering the entire workflow of systems biology. We will create the first semantic description of particle-mesh algorithms and derive a formal domain-specific language from it. Around this language, we will design a tool-flow and integrated development environment that provides instant user feedback and support for interactive debugging.Our runtime system will be based on the OpenFPM library for particle-mesh methods being currently developed. Leveraging domain knowledge and runtime monitoring, we will develop static and dynamic optimizations at the language level, as well as at runtime. To asses our language and optimizations, three driver applications from computational biology that pose outstanding problems will be implemented and evaluated in terms of runtime performance, scalability, and developers productivity.

并行高性能计算(HPC)对于研究复杂现实世界现象的科学模型、准确预测它们的行为和对扰动的反应以及分析真实世界实验的大数据集是必不可少的。这类特别具有挑战性的应用出现在系统生物学领域，该领域模拟复杂的细胞模型和细胞系统，以便对生物机制进行反向工程。建模和仿真的过程是由高分辨率的三维显微图像驱动的，也需要实时处理。因此，建模、仿真和数据分析至关重要地依赖于高性能计算平台的有效使用。然而，开发在并行HPC硬件上高效运行的健壮和通用的数值方法是一项具有挑战性、容易出错和耗时的任务。开发人员需要了解手头的问题域、数学模型以及算法规范对底层系统架构和性能的影响。在这个项目中，我们通过引入透明的抽象层来缩小高级问题描述和最终HPC代码之间的差距，这些抽象层包括：特定于领域的语言、编译器、自适应运行时系统和开发环境。我们把一般的粒子网格方法作为数值模拟的框架，因为它们既可以模拟离散的模型，也可以模拟连续的模型和处理图像，从而覆盖了系统生物学的整个工作流程。我们将创建第一个粒子网格算法的语义描述，并从它派生出一种形式化的领域特定语言。围绕这一语言，我们将设计一个工具流和集成开发环境，提供即时用户反馈和交互调试支持。我们的运行系统将基于目前正在开发的粒子网格方法的OpenFPM库。利用领域知识和运行时监控，我们将在语言级别以及运行时开发静态和动态优化。为了评估我们的语言和优化，将实现和评估来自计算生物学的三个驱动程序应用程序，它们会带来突出的问题，并从运行时性能、可伸缩性和开发人员生产力方面进行评估。