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The recent successes and wide spread application of compute intensive machine learning and data analytics methods have been boosting the usage of the Python programming language on HPC systems. While Python provides many advantages for the users, it has not been designed with a focus on multiuser environments or parallel programming - making it quite challenging to maintain stable and secure Python workflows on a HPC system. In this paper, we analyze the key problems induced by the usage of Python on HPC clusters and sketch appropriate workarounds for efficiently maintaining multi-user Python software environments, securing and restricting resources of Python jobs and containing Python processes, while focusing on Deep Learning applications running on GPU clusters.
Due to the rapidly increasing storage consumption worldwide, as well as the expectation of continuous availability of information, the complexity of administration in today’s data centers is growing permanently. Integrated techniques for monitoring hard disks can increase the reliability of storage systems. However, these techniques often lack intelligent data analysis to perform predictive maintenance. To solve this problem, machine learning algorithms can be used to detect potential failures in advance and prevent them. In this paper, an unsupervised model for predicting hard disk failures based on Isolation Forest is proposed. Consequently, a method is presented that can deal with the highly imbalanced datasets, as the experiment on the Backblaze benchmark dataset demonstrates.
The authors present an abiotically catalyzed glucose fuel cell and demonstrate its application as energy harvesting power source for a cardiac pacemaker. This is enabled by an optimized DC-DC converter operating at 40 % conversion efficiency, which surpasses commercial low-power DC-DC converters. The required fuel cell surface area can thus be reduced from about 125 cm2 to 18 cm2, which would allow for its direct integration onto the pacemaker casing.
In this paper we present the implementation of a model-predictive controller (MPC) for real-time control of a cable-robot-based motion simulator. The controller computes control inputs such that a desired acceleration and angular velocity at a defined point in simulator’s cabin are tracked while satisfying constraints imposed by working space and allowed cable forces of the robot. In order to fully use the simulator capabilities, we propose an approach that includes the motion platform actuation in the MPC model. The tracking performance and computation time of the algorithm are investigated in computer simulations. Furthermore, for motion simulation scenarios where the reference trajectories are not known beforehand, we derive an estimate on how much motion simulation fidelity can maximally be improved by any reference prediction scheme compared to the case when no prediction scheme is applied.
The monitoring of industrial environments ensures that highly automated processes run without interruption. However, even if the industrial machines themselves are monitored, the communication lines are currently not continuously monitored in todays installations. They are checked usually only during maintenance intervals or in case of error. In addition, the cables or connected machines usually have to be removed from the system for the duration of the test. To overcome these drawbacks, we have developed and implemented a cost-efficient and continuous signal monitoring of Ethernet-based industrial bus systems. Several methods have been developed to assess the quality of the cable. These methods can be classified to either passive or active. Active methods are not suitable if interruption of the communication is undesired. Passive methods, on the other hand, require oversampling, which calls for expensive hardware. In this paper, a novel passive method combined with undersampling targeting cost-efficient hardware is proposed.
Live streaming of events over an IP network as a catalyst in media technology education and training
(2020)
The paper describes how students are involved in applied research when setting up the technology and running a live event. Real-time IP transmission in broadcast environments via fiber optics will become increasingly important in the future. Therefore, it is necessary to create a platform in this area where students can learn how to handle IP infrastructure and fiber optics. With this in mind, we have built a fully functional TV control room that is completely IP-based. The authors present the steps in the development of the project and show the advantages of the proposed digital solutions. The IP network proves to be a synergy between the involved teams: participants of the robot competition and the members of the media team. These results are presented in the paper. Our activities aim to awaken enthusiasm for research and technology in young people. Broadcasts of live events are a good opportunity for "hands on" activities.
Temperature regulation is an important component for modern high performance single -core and multi-core processors. Especially high operating frequencies and architectures with an increasing number of monolithically integrated transistors result in a high power dissipation and - since processor chips convert the consumed electrical energy into thermal energy - in high operating temperatures. High operating temperatures of processors can have drastic consequences regarding chip reliability, processor performance, and leakage currents. External components like fans or heat spreaders can help to reduce the processor temperature - with the disadvantage of additional costs and reduced reliability. Therefore, software based algorithms for dynamic temperature management are an attractive alternative and well known as Dynamic Thermal Management (DTM). However, the existing approaches for DTM are not taking into account the requirements of real-time embedded computing, which is the objective in the given project. The first steps are the profiling and the thermal modeling of the system, which is reported in this paper for a Freescale i. MX6Q quad-core microprocessor. An analytical model is developed and verified by an extensive set of measurement runs.