992 resultados para Graphical processing unit
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The objective of the present study was to evaluate the efficiency of the process of biodigestion of the protein concentrate resulting from the ultrafiltration of the effluent from a slaughterhouse freezer of Nile tilapia. Bench digesters were used with excrements and water (control) in comparison with a mixture of cattle manure and effluent from the stages of filleting and bleeding of tilapias. The effluent obtained in the continuous process (bleeding + filleting) was the one with highest accumulated population from the 37th day, as well as greatest daily production. Gases composition did not differ between the protein concentrates, but the gas obtained with the use of the effluent from the filleting stage presented highest methane gas average (78.05%) in comparison with those obtained in the bleeding stage (69.95%) and in the continuous process (70.02%) or by the control method (68.59%).
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Microprocessori basati su singolo processore (CPU), hanno visto una rapida crescita di performances ed un abbattimento dei costi per circa venti anni. Questi microprocessori hanno portato una potenza di calcolo nell’ordine del GFLOPS (Giga Floating Point Operation per Second) sui PC Desktop e centinaia di GFLOPS su clusters di server. Questa ascesa ha portato nuove funzionalità nei programmi, migliori interfacce utente e tanti altri vantaggi. Tuttavia questa crescita ha subito un brusco rallentamento nel 2003 a causa di consumi energetici sempre più elevati e problemi di dissipazione termica, che hanno impedito incrementi di frequenza di clock. I limiti fisici del silicio erano sempre più vicini. Per ovviare al problema i produttori di CPU (Central Processing Unit) hanno iniziato a progettare microprocessori multicore, scelta che ha avuto un impatto notevole sulla comunità degli sviluppatori, abituati a considerare il software come una serie di comandi sequenziali. Quindi i programmi che avevano sempre giovato di miglioramenti di prestazioni ad ogni nuova generazione di CPU, non hanno avuto incrementi di performance, in quanto essendo eseguiti su un solo core, non beneficiavano dell’intera potenza della CPU. Per sfruttare appieno la potenza delle nuove CPU la programmazione concorrente, precedentemente utilizzata solo su sistemi costosi o supercomputers, è diventata una pratica sempre più utilizzata dagli sviluppatori. Allo stesso tempo, l’industria videoludica ha conquistato una fetta di mercato notevole: solo nel 2013 verranno spesi quasi 100 miliardi di dollari fra hardware e software dedicati al gaming. Le software houses impegnate nello sviluppo di videogames, per rendere i loro titoli più accattivanti, puntano su motori grafici sempre più potenti e spesso scarsamente ottimizzati, rendendoli estremamente esosi in termini di performance. Per questo motivo i produttori di GPU (Graphic Processing Unit), specialmente nell’ultimo decennio, hanno dato vita ad una vera e propria rincorsa alle performances che li ha portati ad ottenere dei prodotti con capacità di calcolo vertiginose. Ma al contrario delle CPU che agli inizi del 2000 intrapresero la strada del multicore per continuare a favorire programmi sequenziali, le GPU sono diventate manycore, ovvero con centinaia e centinaia di piccoli cores che eseguono calcoli in parallelo. Questa immensa capacità di calcolo può essere utilizzata in altri campi applicativi? La risposta è si e l’obiettivo di questa tesi è proprio quello di constatare allo stato attuale, in che modo e con quale efficienza pùo un software generico, avvalersi dell’utilizzo della GPU invece della CPU.
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Graphics Processing Units have become a booster for the microelectronics industry. However, due to intellectual property issues, there is a serious lack of information on implementation details of the hardware architecture that is behind GPUs. For instance, the way texture is handled and decompressed in a GPU to reduce bandwidth usage has never been dealt with in depth from a hardware point of view. This work addresses a comparative study on the hardware implementation of different texture decompression algorithms for both conventional (PCs and video game consoles) and mobile platforms. Circuit synthesis is performed targeting both a reconfigurable hardware platform and a 90nm standard cell library. Area-delay trade-offs have been extensively analyzed, which allows us to compare the complexity of decompressors and thus determine suitability of algorithms for systems with limited hardware resources.
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This paper analyzes the behavior of a neural processing unit based on the optical bistable properties of semiconductor laser amplifiers. A similar unit to the reported here was previously employed in the simulation of the mammalian retina. The main advantages of the present cell are its larger fan-out and the possibility of different responses according to the light wavelength impinging onto the cell. These properties allow to work with larger structures as well as to obtain different behaviors according to the light characteristics. This new approach gives a possible modeling closer to the real biological configurations. Moreover, a more detailed analysis of the basic cell internal behavior is reported
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Photocopy of typescript.
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Bibliography: p. 74.
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"May 1958."
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Includes index.
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In Fourier domain optical coherence tomography (FD-OCT), a large amount of interference data needs to be resampled from the wavelength domain to the wavenumber domain prior to Fourier transformation. We present an approach to optimize this data processing, using a graphics processing unit (GPU) and parallel processing algorithms. We demonstrate an increased processing and rendering rate over that previously reported by using GPU paged memory to render data in the GPU rather than copying back to the CPU. This avoids unnecessary and slow data transfer, enabling a processing and display rate of well over 524,000 A-scan/s for a single frame. To the best of our knowledge this is the fastest processing demonstrated to date and the first time that FD-OCT processing and rendering has been demonstrated entirely on a GPU.
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The objective of the present study was to evaluate the efficiency of the process of biodigestion of the protein concentrate resulting from the ultrafiltration of the effluent from a slaughterhouse freezer of Nile tilapia. Bench digesters were used with excrements and water (control) in comparison with a mixture of cattle manure and effluent from the stages of filleting and bleeding of tilapias. The effluent obtained in the continuous process (bleeding + filleting) was the one with highest accumulated population from the 37th day, as well as greatest daily production. Gases composition did not differ between the protein concentrates, but the gas obtained with the use of the effluent from the filleting stage presented highest methane gas average (78.05%) in comparison with those obtained in the bleeding stage (69.95%) and in the continuous process (70.02%) or by the control method (68.59%).
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A graphical processing unit (GPU) is a hardware device normally used to manipulate computer memory for the display of images. GPU computing is the practice of using a GPU device for scientific or general purpose computations that are not necessarily related to the display of images. Many problems in econometrics have a structure that allows for successful use of GPU computing. We explore two examples. The first is simple: repeated evaluation of a likelihood function at different parameter values. The second is a more complicated estimator that involves simulation and nonparametric fitting. We find speedups from 1.5 up to 55.4 times, compared to computations done on a single CPU core. These speedups can be obtained with very little expense, energy consumption, and time dedicated to system maintenance, compared to equivalent performance solutions using CPUs. Code for the examples is provided.
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The Computational Biophysics Group at the Universitat Pompeu Fabra (GRIB-UPF) hosts two unique computational resources dedicated to the execution of large scale molecular dynamics (MD) simulations: (a) the ACMD molecular-dynamics software, used on standard personal computers with graphical processing units (GPUs); and (b) the GPUGRID. net computing network, supported by users distributed worldwide that volunteer GPUs for biomedical research. We leveraged these resources and developed studies, protocols and open-source software to elucidate energetics and pathways of a number of biomolecular systems, with a special focus on flexible proteins with many degrees of freedom. First, we characterized ion permeation through the bactericidal model protein Gramicidin A conducting one of the largest studies to date with the steered MD biasing methodology. Next, we addressed an open problem in structural biology, the determination of drug-protein association kinetics; we reconstructed the binding free energy, association, and dissaciociation rates of a drug like model system through a spatial decomposition and a Makov-chain analysis. The work was published in the Proceedings of the National Academy of Sciences and become one of the few landmark papers elucidating a ligand-binding pathway. Furthermore, we investigated the unstructured Kinase Inducible Domain (KID), a 28-peptide central to signalling and transcriptional response; the kinetics of this challenging system was modelled with a Markovian approach in collaboration with Frank Noe’s group at the Freie University of Berlin. The impact of the funding includes three peer-reviewed publication on high-impact journals; three more papers under review; four MD analysis components, released as open-source software; MD protocols; didactic material, and code for the hosting group.
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Communities are present on physical, chemical and biological systems and their identification is fundamental for the comprehension of the behavior of these systems. Recently, available data related to complex networks have grown exponentially, demanding more computational power. The Graphical Processing Unit (GPU) is a cost effective alternative suitable for this purpose. We investigate the convenience of this for network science by proposing a GPU based implementation of Newman community detection algorithm. We showed that the processing time of matrix multiplications of GPUs grow slower than CPUs in relation to the matrix size. It was proven, thus, that GPU processing power is a viable solution for community dentification simulation that demand high computational power. Our implementation was tested on an integrated biological network for the bacterium Escherichia coli
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A dificuldade de controlo de um motor de indução, bem como o armazenamento de energia CC e posterior utilização como energia alternada promoveram o desenvolvimento de variadores de frequência e inversores. Assim, como projeto de tese de mestrado em Automação e Sistemas surge o desenvolvimento de um variador de frequência. Para elaboração do variador de frequência efetuou-se um estudo sobre as técnicas de modulação utilizadas nos inversores. A técnica escolhida e utilizada é a Sinusoidal Pulse Width Modulation (SPWM). Esta técnica baseia-se na modelação por largura de impulso (PWM), o qual é formado por comparação de um sinal de referência com um sinal de portadora de elevada frequência. Por sua vez, a topologia escolhida para o inversor corresponde a um Voltage Source Inverter (VSI) de ponte trifásica completa a três terminais. O desenvolvimento da técnica de modulação SPWM levou ao desenvolvimento de um modelo de simulação em SIMULINK, o qual permitiu retirar conclusões sobre os resultados obtidos. Na fase de implementação, foram desenvolvidas placas para o funcionamento do variador de frequência. Assim, numa fase inicial foi desenvolvida a placa de controlo, a qual contém a unidade de processamento e que é responsável pela atuação de Insulated Gate Bipolar Transistors (IGBTs). Para além disso, foi desenvolvida uma placa para proteção dos IGBTs (evitando condução simultânea no mesmo terminal) e uma placa de fontes isoladas para alimentação dos circuitos e para atuação dos IGBTs. Ainda, foi desenvolvida a técnica de SPWM em software para a unidade de controlo e finalmente foi desenvolvida uma interface gráfica para interação com o utilizador. A validação do projeto foi conseguida através da variação da velocidade do motor de indução trifásico. Para isso, este foi colocado a funcionar a diversas frequências de funcionamento e a diferentes amplitudes. Para além disso, o seu funcionamento foi também validado utilizando uma carga trifásica equilibrada de 3 lâmpadas de forma a ser visualizada a variação de frequência e variação de amplitude.
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Shading reduces the power output of a photovoltaic (PV) system. The design engineering of PV systems requires modeling and evaluating shading losses. Some PV systems are affected by complex shading scenes whose resulting PV energy losses are very difficult to evaluate with current modeling tools. Several specialized PV design and simulation software include the possibility to evaluate shading losses. They generally possess a Graphical User Interface (GUI) through which the user can draw a 3D shading scene, and then evaluate its corresponding PV energy losses. The complexity of the objects that these tools can handle is relatively limited. We have created a software solution, 3DPV, which allows evaluating the energy losses induced by complex 3D scenes on PV generators. The 3D objects can be imported from specialized 3D modeling software or from a 3D object library. The shadows cast by this 3D scene on the PV generator are then directly evaluated from the Graphics Processing Unit (GPU). Thanks to the recent development of GPUs for the video game industry, the shadows can be evaluated with a very high spatial resolution that reaches well beyond the PV cell level, in very short calculation times. A PV simulation model then translates the geometrical shading into PV energy output losses. 3DPV has been implemented using WebGL, which allows it to run directly from a Web browser, without requiring any local installation from the user. This also allows taken full benefits from the information already available from Internet, such as the 3D object libraries. This contribution describes, step by step, the method that allows 3DPV to evaluate the PV energy losses caused by complex shading. We then illustrate the results of this methodology to several application cases that are encountered in the world of PV systems design. Keywords: 3D, modeling, simulation, GPU, shading, losses, shadow mapping, solar, photovoltaic, PV, WebGL