Maciej Cytowski

The Copernicus Complexio: a high-resolution view of the small-scale Universe

We introduce Copernicus Complexio (COCO), a high-resolution cosmological N-body simulation of structure formation in the ΛCDM model. COCO follows an approximately spherical region of radius ∼17.4 h−1 Mpc embedded in a much larger periodic cube that is followed at lower resolution. The high-resolution volume has a particle mass of 1.135 × 105 h−1 M⊙ (60 times higher than the Millennium-II simulation). COCO gives the dark matter halo mass function over eight orders of magnitude in halo mass; it forms ∼60 haloes of galactic size, each resolved with about 10 million particles. We confirm the power-law character of the subhalo mass function, , down to a reduced subhalo mass Msub/M200 ≡ μ = 10−6, with a best-fitting power-law index, s = 0.94, for hosts of mass 〈M200〉 = 1012 h−1 M⊙. The concentration–mass relation of COCO haloes deviates from a single power law for masses M200 < afew × 108 h−1 M⊙, where it flattens, in agreement with results by Sanchez-Conde et al. The host mass invariance of the reduced maximum circular velocity function of subhaloes, ν ≡ Vmax/V200, hinted at in previous simulations, is clearly demonstrated over five orders of magnitude in host mass. Similarly, we find that the average, normalized radial distribution of subhaloes is approximately universal (i.e. independent of subhalo mass), as previously suggested by the Aquarius simulations of individual haloes. Finally, we find that at fixed physical subhalo size, subhaloes in lower mass hosts typically have lower central densities than those in higher mass hosts.

Large-Scale Parallel Simulations of 3D Cell Colony Dynamics: The Cellular Environment

The authors present a large-scale, hybrid 3D model for simulating dynamics of cell colonies growing in and interacting with a variable environment. For this purpose, they extended an earlier mathematical and computational formulation of a cell colony model to incorporate the cellular environment modeled in a continuous manner. A mathematical description based on partial differential equations is formulated for selected important components of the environment. Such extension is necessary to deal with complex biological processes such as cancer growth, where a number of scales need to be considered (subcellular, cellular, and tissue). The authors show how a continuous model can be efficiently solved on a massively parallel processing system. They also present computational methods that couple discrete and continuous descriptions while maintaining high scalability of the resulting application.

Implementation of an Agent-Based Parallel Tissue Modelling Framework for the Intel MIC Architecture

Timothy is a novel large scale modelling framework that allows simulating of biological processes involving different cellular colonies growing and interacting with variable environment. Timothy was designed for execution on massively parallel High Performance Computing (HPC) systems. The high parallel scalability of the implementation allows for simulations of up to 109 individual cells (i.e., simulations at tissue spatial scales of up to 1źcm3 in size). With the recent advancements of the Timothy model, it has become critical to ensure appropriate performance level on emerging HPC architectures. For instance, the introduction of blood vessels supplying nutrients to the tissue is a very important step towards realistic simulations of complex biological processes, but it greatly increased the computational complexity of the model. In this paper, we describe the process of modernization of the application in order to achieve high computational performance on HPC hybrid systems based on modern Intel® MIC architecture. Experimental results on the Intel Xeon Phiź coprocessor x100 and the Intel Xeon Phi processor x200 are presented.

Computational Modelling of Cancer Development and Growth: Modelling at Multiple Scales and Multiscale Modelling

In this paper, we present two mathematical models related to different aspects and scales of cancer growth. The first model is a stochastic spatiotemporal model of both a synthetic gene regulatory network (the example of a three-gene repressilator is given) and an actual gene regulatory network, the NF-

Analysis of gravitational wave signals on heterogeneous architectures

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Large-Scale Parallel Simulations of 3D Cell Colony Dynamics

κB pathway. The second model is a force-based individual-based model of the development of a solid avascular tumour with specific application to tumour cords, i.e. a mass of cancer cells growing around a central blood vessel. In each case, we compare our computational simulation results with experimental data. In the final discussion section, we outline how to take the work forward through the development of a multiscale model focussed at the cell level. This would incorporate key intracellular signalling pathways associated with cancer within each cell (e.g. p53–Mdm2, NF-

Enabling Large Scale Individual-Based Modelling through High Performance Computing

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