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Reinforcement learning is a powerful tool for teaching robotic agents to perform tasks in real environments. Visual information provided by a camera could be a cheap and rich source of information about an agent's surroundings, if this information were represented in a compact and generalizable form. We turn to cellular neural networks as the means of transforming visual input to a representation...
We describe a pilot project for the use of GPUs in a real-time triggering application in the early trigger stages at the CERN NA62 experiment, and the results of the first field tests together with a prototype data acquisition (DAQ) system. This pilot project within NA62 aims at integrating GPUs into the central L0 trigger processor, and also to use them as fast online processors for computing trigger...
High energy physics particle detectors are large and complex devices with very demanding requirements at the level of signal to noise ratios, processing times and data throughput. The first stages of the data acquisition are hardware based while the last ones depend rather on software. Among the solutions to the problems posed by the requirements we may find the use of multi-core processors or maybe...
The CNN (Cellular Neural Network) is a powerful image processing architecture whose hardware implementation is extremely fast. The lack of such hardware device in a development process can be substituted by using an efficient simulator implementation. Commercially available graphics cards with high computing capabilities make this simulator feasible. The aim of this work is to present a GPU based...
In this work, active wave simulation on Cellular Nonlinear Network was computed for path planning on the GPU of a NVIDIA GTX275 video card. In software part, QtOpenCL, which is a wrapper library of OpenCL, was used to make code portable for systems with different GPUs. We achieved promising results comparing to results achieved by both CPU and FPGA. We have implemented different hardware and software...
The online event reconstruction for the ALICE experiment at CERN requires processing capabilities to process central Pb-Pb collisions at a rate of more than 200 Hz, corresponding to an input data rate of about 25 GB/s. The reconstruction of particle trajectories in the Time Projection Chamber (TPC) is the most compute intensive step. The TPC online tracker implementation combines the principle of...
The aim of this paper is to discuss and compare several architectural possibilities for implementing a simulator for (ultra) sound propagation in a controlled environment (e.g. using specified obstacles and signal sources). Although initially such sound propagation simulators were designed to assist the design of robotic "ears" of autonomous agents trying to reconstruct an image of the environment,...
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