Fast nanopore sequencing data analysis with SLOW5

Nanopore sequencing depends on the FAST5 file format, which does not allow efficient parallel analysis. Here we introduce SLOW5, an alternative format engineered for efficient parallelization and acceleration of nanopore data analysis. Using the example of DNA methylation profiling of a human genome, analysis runtime is reduced from more than two weeks to approximately 10.5 h on a typical high-performance computer. SLOW5 is approximately 25% smaller than FAST5 and delivers consistent improvements on different computer architectures.

The investigation of the features optical vortices focusing by ring gratings with the variable height using high-performance computer systems

The diffraction of vortex laser beams with circular polarization by ring gratings with the variable height was investigated in this paper. Modelling of near zone diffraction is numerically investigated by the finite difference time domain (FDTD) method. The changes in the length size of the light needle and focal spot size are shown depending on the type of the ring grating.

Improving computational efficiency of GLUE method for hydrological model uncertainty and parameter estimation using CPU-GPU hybrid high performance computer cluster

The Generalized Likelihood Uncertainty Estimation (GLUE) method has been thrived for decades, huge number of applications in the field of hydrological model have proved its effectiveness in uncertainty and parameter estimation. However, for many years, the poor computational efficiency of GLUE hampers its further applications. A feasible way to solve this problem is the integration of modern CPU-GPU hybrid high performance computer cluster technology to accelerate the traditional GLUE method. In this study, we developed a CPU-GPU hybrid computer cluster-based highly parallel large-scale GLUE method to improve its computational efficiency. The Intel Xeon multi-core CPU and NVIDIA Tesla many-core GPU were adopted in this study. The source code was developed by using the MPICH2, C++ with OpenMP 2.0, and CUDA 6.5. The parallel GLUE method was tested by a widely-used hydrological model (the Xinanjiang model) to conduct performance and scalability investigation. Comparison results indicated that the parallel GLUE method outperformed the traditional serial method and have good application prospect on super computer clusters such as the ORNL Summit and Sierra of the TOP500 super computers around the world.

What do we need to trust in models?

Scientists working with numerical models may notice that their presentations of numerical results to non-specialists sometimes unfold substantial persuasive power. It seems obvious that someone has worked intensively on a topic, bundled information and solved complicated equations on a high-performance computer. The final result is a number, a curve or a three-dimensional representation. The computer has made no mistake, so the result can certainly be trusted. But can it? Those who do the modelling often know the weak points of their models and invest time in increasing the reliability of the model calculation. Trust in model calculations is usually based on rigorous quality assurance of data, programs, simulation calculations and result analyses. It requires appropriate handling of uncertainties. In view of the simplifications and idealizations of models it is also necessary to assess which model results are actually meaningful. Additionally, in most cases simplified or idealised models have been used and it is necessary to assess which model results are actually meaningful. We want to discuss what it takes to generate simulation results that can be considered reliable and how scientists can appropriately convey their confidence in their own models in discussions with the public. The framework of the discussion is provided by an introduction from Martin Navarro und Ingo Kock (BASE) and we are happy to have brief input from Thomas Nagel (TUBAF), Klaus-Jürgen Röhlig (TUC) and Wolfram Rühaak (BGE).

FDS simulation of smoke backlayering in emergency lay-by of a road tunnel with longitudinal ventilation

This paper investigates smoke movement and its stratification in a lay-by of a 900 m long road tunnel by computer simulation using Fire Dynamics Simulator. The lay-by is located upstream of the fire in its vicinity. The influence of lay-by geometry on smoke spread is evaluated by comparison with a fictional tunnel without lay-by. Several fire scenarios with various tunnel slopes and heat release rates of fire in the tunnels without and with the lay-by are considered. The most significant breaking of smoke stratification and decrease of visibility in the area of the lay-by can be observed in the case of zero slope tunnel for more intensive fires with significant length of backlayering. Several other features of smoke spread in the lay-by are analysed as well. The parallel calculations were performed on a high-performance computer cluster.