Research Groups

Parallel high-performance computing for systems biology

Performing simulations, image analysis, and visualization in real time requires parallel high-performance computer resources. In our case, this includes accelerators like graphics cards for visualization, and computer clusters for image analysis and simulations. Combining the two, we develop a standard high-performance environment for particle methods.

To this end, we have been co-developing the Parallel Particle Mesh (PPM) software library since 2005. The PPM Library has enabled some of the world’s biggest and most efficient simulations and has reduced code-development times from years to weeks. In addition to PPM, we also developed a domain-specific programming language for parallel particle methods, PPML. Using PPM and PPML, we are able to implement a fully parallel, scalable particle method for simulation or image processing within a few hours, whereas it took years before to hand-parallelize the code. When used for image processing, PPM and PPML enable real-time image segmentation during microscopy acquisition.

In order to exploit software-development synergies, we participate in the “Dresden Software Synergy Consortium” (Myers, Tomancak, Hiller, Zerial, Sbalzarini), contributing to open-source software projects like Fiji (image processing) and ClearVolume (3D real-time microscopy), and making our methods available as Knime nodes for reusable workflows.

Collaborators:

  • Dr. Michael Bussmann (Computational Physics Group, Helmholtz Center Dresden Rossendorf)
  • Prof. Dr. Jeronimo Castrillon (Chair of Compiler Construction, TU Dresden)
  • Prof. Dr. Uwe Assmann (Chair of Software Engineering, TU Dresden)
  • Dr. Pavel Tomancak (MPI-CBG)
  • Prof. Dr. Eugene W. Myers (MPI-CBG)
The PPM Library provides a versatile middleware for parallel particle methods on a range of computer architectures from vector (GPU) processors to distributed-memory clusters. It hides the intricacies of parallel programming from the user and enables development times of under a day. Previous PPM uses (shown on top) included large-scale simulations of fluid flow, diffusion, astrophysics, and electromagnetism on thousands of processors.