Despite the increasing interest in neural architecture search (NAS), the significant computational cost of NAS is a hindrance to researchers. Hence, we propose to reduce the cost of NAS using proxy data, i.e., a repre...
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An open problem in industrial automation is to reliably perform tasks requiring in-contact movements with complex workpieces, as current solutions lack the ability to seamlessly adapt to the workpiece geometry. In thi...
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Gaussian processes (GPs) are commonly used for geospatial analysis, but they suffer from high computational complexity when dealing with massive data. For instance, the log-likelihood function required in estimating t...
Gaussian processes (GPs) are commonly used for geospatial analysis, but they suffer from high computational complexity when dealing with massive data. For instance, the log-likelihood function required in estimating the statistical model parameters for geospatial data is a computationally intensive procedure that involves computing the inverse of a covariance matrix with size $n$ × n, where $n$ represents the number of geographical locations in the simplest case. As a result, in the literature, studies have shifted towards approximation methods to handle larger values of $n$ effectively while maintaining high accuracy. These methods encompass a range of techniques, including low-rank and sparse approximations. Among these techniques, Vecchia approximation is one of the most promising methods to speed up evaluating the log-likelihood function. This study presents a parallel implementation of the Vecchia approximation technique, utilizing batched matrix computations on contemporary GPUs. The proposed implementation relies on batched linear algebra routines to efficiently execute individual conditional distributions in the Vecchia algorithm. We rely on the KBLAS linear algebra library to perform batched linear algebra operations, reducing the time to solution compared to the state-of-the-art parallel implementation of the likelihood estimation operation in the ExaGeoStat software by up to 700X, 833X, 1380X on 32GB GV100, 80GB A100, and 80GB H100 GPUs, respectively, with the largest matrix dimension that can fully fit into the GPU memory in the dense Maximum Likelihood Estimation (MLE) case. We also successfully manage larger problem sizes on a single NVIDIA GPU, accommodating up to 1 million locations with 80GB A100 and H100 GPUs while maintaining the necessary application accuracy. We further assess the accuracy performance of the implemented algorithm, identifying the optimal settings for the Vecchia approximation algorithm to preserve accuracy on two real geos
We present topological insulators for surface acoustic waves on piezoelectric materials. Our structures are based on honeycomb lattices of different types of acoustic domains and derive their nontrivial topology by br...
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We present topological insulators for surface acoustic waves on piezoelectric materials. Our structures are based on honeycomb lattices of different types of acoustic domains and derive their nontrivial topology by breaking the symmetry of the lattice hexagonal unit cells. Our results can have applications in compact signal processing integrated devices at microwave frequencies based on surface acoustic waves.
This paper proposes an alternative detection frame-work for multiple sclerosis (MS) and idiopathic acute transverse myelitis (ATM) within the 6G-enabled Internet of Medical Things (IoMT) environment. The developed fra...
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ISBN:
(数字)9798350351408
ISBN:
(纸本)9798350351415
This paper proposes an alternative detection frame-work for multiple sclerosis (MS) and idiopathic acute transverse myelitis (ATM) within the 6G-enabled Internet of Medical Things (IoMT) environment. The developed framework relies on the implementation of a deep learning technique known as Dense Convolutional Networks (DenseNets) in the 6G-enabled IoMT to enhance prediction performance. To validate the performance of DenseNets, we compared it with other deep learning techniques, including Convolutional Neural Networks (CNN) and MobileNet, using real-world datasets. The experimental results show the high performance of DenseNets in predicting MS and ATM compared to other methods, achieving an accuracy of nearly 90 %.
With the increase in demand for higher-quality and more capable IT services, IT organizations in order to obtain competitive advantage require extensive knowledge that needs to be shared and reused among different ent...
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With the increase in demand for higher-quality and more capable IT services, IT organizations in order to obtain competitive advantage require extensive knowledge that needs to be shared and reused among different entities within the organization. The existing IT Service Management (ITSM) mechanisms mention the importance of organizational learning (OL) and knowledge management (KM) for IT organizations. However, they do not explicitly address how OL capabilities of an IT organization can be assessed. This paper, by using an OL assessment model developed for software organizations, namely AiOLoS, shows that with the proper adjustment, the application of the model to IT organizations is feasible. We report the results of applying the model in four functional teams in an IT organization from private sector.
In this paper, we carry out an exact outage analysis for a secondary (unlicensed) system operating under a strict primary (licensed) system outage constraint. We focus on single-user single-input multiple-output (SIMO...
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In this paper, we carry out an exact outage analysis for a secondary (unlicensed) system operating under a strict primary (licensed) system outage constraint. We focus on single-user single-input multiple-output (SIMO) secondary communications where the direct link is being assisted by a cluster of single-antenna decode-and-forward (DF) relay nodes acting in a half-duplex selective-and-incremental relaying mode. Firstly, we derive a transmit power model for the secondary system where the source and relays adapt their transmit power based on: 1) a perfect acquisition of the underlying interference channel state information (I-CSI), and 2) an interference constraint that is either fixed or proportional to the primary system outage probability. Secondly, the cumulative distribution functions (CDF)s of the received signal-to-noise ratio (SNR) at the secondary receiving nodes are devised in a recursive and tractable closed-form expressions. These statistics are used to derive the exact end-to-end secondary system outage probability. The analytical and simulation results are then compared and interestingly shown to perfectly match, while revealing that with a moderate number of primary and secondary receive antennas, the secondary system spectral efficiency is amply enhanced as opposed to being severely degraded in the single receive antenna case.
Effective exploitation of the application-specific parallel patterns and computation operations through their direct implementation in hardware is the base for construction of high-quality application-specific (re-)co...
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Effective exploitation of the application-specific parallel patterns and computation operations through their direct implementation in hardware is the base for construction of high-quality application-specific (re-)configurable application specific instruction set processors (ASIPs) and hardware accelerators for modern highly-demanding applications. Although it receives a lot of attention from the researchers and practitioners, a very important problem of hardware reuse in ASIP and accelerator synthesis is clearly underestimated and does not get enough attention in the published research. This paper is an effect of an industry and academic collaborative research. It analyses the problem of hardware sharing, shows its high practical relevance, as well as a big influence of hardware sharing on the major circuit and system parameters, and its importance for the multi-objective optimization and tradeoff exploitation. It also demonstrates that the state-of-the-art synthesis tools do not sufficiently address this problem and gives several guidelines related to enhancement of the hardware reuse.
Modern social intelligence includes the ability to watch videos and answer questions about social and theory-of-mind-related content, e.g., for a scene in Harry Potter, "Is the father really upset about the boys ...
In this paper, the influence of different Phase-Locked Loops (PLLs) on the fault response of a grid-following (GFL) Inverter-Based Resource (IBR) is evaluated. The analyzed IBR represents a wind power plant with rated...
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ISBN:
(数字)9798331507152
ISBN:
(纸本)9798331507169
In this paper, the influence of different Phase-Locked Loops (PLLs) on the fault response of a grid-following (GFL) Inverter-Based Resource (IBR) is evaluated. The analyzed IBR represents a wind power plant with rated power equal to 100 MVA, being composed of 50 turbines with 2 MVA each, whose controls follow the Brazilian grid code. Two PLL models are taken into account to conduct the proposed studies, which include the analysis of voltage and frequency estimated by each PLL, and currents injected into the IBR interconnection transmission line. The Synchronous Reference Frame (SRF) PLL and the Quadrature Signal Generator-based Second-Order Generalized Integrator (QSG-SOGI) PLL are considered, assessing their influence under different transmission line fault scenarios. The obtained results indicate that the PLL can present severe instabilities during faults, which can be more or less critical depending on the fault type and on the PLL type. Indeed, the results reveal that different PLLs can result in distinct behaviors of currents injected into the interconnection line, raising the importance of knowing the PLL structures when studies on IBR fault responses are of interest.
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