analysis problems, where the hydraulic simulation has to be repeated many times. Among 7 the methods used for hydraulic solvers, the most prominent nowadays is the global gradi-8 ent algorithm (GGA), based on a hybrid node-loop formulation and used by the software 9 package Epanet. Earlier, another method based just on loop flow equations was proposed, 10 which presents the advantage that it leads to a system matrix which is in most cases much 11 smaller than in the GGA method, but has also some disadvantages, mainly a less sparse 12 system matrix, and the fact that introducing some types of valves requires the redefinition 13 of the set of network loops initially defined.
14The contribution of this paper is to present solutions for overcoming the mentioned 15 disadvantages of the method based on loop flow equations. In particular, efficient procedures 16 are shown for selecting the network loops so as to achieve a highly sparse matrix, and methods 17 are presented to incorporate check valves and automatic control valves, while avoiding the 18 need to redefine the loops initially selected.
Massive convolution is the basic operation in multichannel acoustic signal processing. This field has experienced a major development in recent years. One reason for this has been the increase in the number of sound sources used in playback applications available to users. Another reason is the growing need to incorporate new effects and to improve the hearing experience. Massive convolution requires high computing capacity. GPUs offer the possibility of parallelizing these operations. This allows us to obtain the processing result in much shorter time and to free up CPU resources. One important aspect lies in the possibility of overlapping the transfer of data from CPU to GPU and vice versa with the computation, in order to carry out real-time applications. Thus, a synthesis of 3D sound scenes could be achieved with only a peer-to-peer music streaming environment using a simple GPU in your computer, while the CPU in the computer is being used for other tasks. Nowadays, these effects are obtained in theaters or funfairs at a very high cost, requiring a large quantity of resources. Thus, our work focuses on two mains points: to describe an efficient massive convolution implementation and to incorporate this task to real-time multichannel-sound applications.
ElsevierBelloch Rodríguez, JA.; Vidal Maciá, AM.; Cobos Serrano, M. (2015). On the performance of multi-GPU-based expert systems for acoustic localization involving massive microphone array. Expert Systems with Applications. 42 (13)
AbstractSound source localization is an important topic in expert systems involving microphone arrays, such as automatic camera steering systems, human-machine interaction, video gaming or audio surveillance. The Steered Response Power with Phase Transform (SRP-PHAT) algorithm is a well-known approach for sound source localization due to its robust performance in noisy and reverberant environments. This algorithm analyzes the sound power captured by an acoustic beamformer on a defined spatial grid, estimating the source location as the point that maximizes the output power. Since localization accuracy can be improved by using high-resolution spatial grids and a high number of microphones, accurate acoustic localization systems require high computational power. Graphics Processing Units (GPUs) are highly parallel programmable co-processors that provide massive computation when the needed operations are properly parallelized. Emerging GPUs offer multiple parallelism levels; however, properly managing their computational resources becomes a very challenging task. In fact, management issues become even more difficult when multiple GPUs are * Corresponding author: Phone Number +34-655436190 Email addresses: email@example.com (Jose A. Belloch), firstname.lastname@example.org (Alberto Gonzalez), email@example.com (Antonio M. Vidal), firstname.lastname@example.org (Maximo Cobos)
Preprint submitted to Journal of L A T E X TemplatesFebruary 25, 2015 involved, adding one more level of parallelism. In this paper, the performance of an acoustic source localization system using distributed microphones is analyzed over a massive multichannel processing framework in a multi-GPU system. The paper evaluates and points out the influence that the number of microphones and the available computational resources have in the overall system performance. Several acoustic environments are considered to show the impact that noise and reverberation have in the localization accuracy and how the use of massive microphone systems combined with parallelized GPU algorithms can help to mitigate substantially adverse acoustic effects. In this context, the proposed implementation is able to work in real time with high-resolution spatial grids and using up to 48 microphones. These results confirm the advantages of suitable GPU architectures in the development of real-time massive acoustic signal processing systems.
ElsevierGarcía Mollá, VM.; Liberos Mascarell, A.; Vidal Maciá, AM.; Guillem Sánchez, MS.; Millet Roig, J.; González Salvador, A.; Gonzalez, A.... (2014). Adaptive step ODE algorithms for the 3D simulation of electric heart activity with graphics processing units. Computers in Biology and Medicine. 44:15-26. doi:10.1016/j.compbiomed.2013.10.023. Adaptive step ODE algorithms for the 3D simulation of electric heart activity with graphics processing units
AbstractIn this paper we studied the implementation and performance of adaptive step methods for large systems of ordinary differential equations systems in Graphics Processing Units, focusing on the simulation of thre-dimensional electric cardiac activity. The RushLarsen method was applied in all of the implemented solvers to improve efficiency. We compared the adaptive methods with the fixed step methods, and we found that the fixed step methods can be faster while the adaptive step methods are better in terms of accuracy and robustness.
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