Performance Analysis of Selection Combining Over Correlated Nakagami-m Fading Channels with Constant Correlation Model for Desired Signal and Cochannel Interference

A very efficient technique that reduces fading and channel interference influence is selection diversity based on the signal to interference ratio (SIR). In this pa¬per, system performances of selection combiner (SC) over correlated Nakagami-m channels with constant correlation model are analyzed. Closed-form expressions are obtained for the output SIR probability density function (PDF) and cumulative distribution function (CDF) which is main contribution of this paper. Outage probability and the average error probability for coherent, noncoherent modulation are derived. Numerical results presented in this paper point out the effects of fading severity and cor¬relation on the system performances. The main contribu¬tion of this analysis for multibranch signal combiner is that it has been done for general case of correlated co-channel interference (CCI)

Validation of the Anxiety Scale for Pregnancy in a Sample of Iranian Women

We investigated propagation of electromagnetic waves through composite structures with negative refractive index, the popular ”left-handed metamaterials”, for the case when there is a gradient of refractive index. We obtained the exact analytical solutions to the Helmholtz equation valid for arbitrary steepness of the graded interface between the positive and the negative index part. We analyzed the special case of matched impedances of the two constituent materials within the metamaterial composite. We derived analytical expressions for the field intensity, transmission and reflection coefficients and compared them with the results obtained by the numerical simulations using the Finite Element Method. The model allows for arbitrary spectral dispersion and lossy media.QC 20120126</p

Considerations in using OpenCL on GPUs and FPGAs for throughput-oriented genomics workloads

The recent upsurge in the available amount of health data and the advances in next-generation sequencing are setting the ground for the long-awaited precision medicine. To process this deluge of data, bioinformatics workloads are becoming more complex and more computationally demanding. For this reasons they have been extended to support different computing architectures, such as GPUs and FPGAs, to leverage the form of parallelism typical of each of such architectures. The paper describes how a genomic workload such as k-mer frequency counting that takes advantage of a GPU can be offloaded to one or even more FPGAs. Moreover, it performs a comprehensive analysis of the FPGA acceleration comparing its performance to a non-accelerated configuration and when using a GPU. Lastly, the paper focuses on how, when using accelerators with a throughput-oriented workload, one should also take into consideration both kernel execution time and how well each accelerator board overlaps kernels and PCIe transferred. Results show that acceleration with two FPGAs can improve both time- and energy-to-solution for the entire accelerated part by a factor of 1.32x. Per contra, acceleration with one GPU delivers an improvement of 1.77x in time-to-solution but of a lower 1.49x in energy-to-solution due to persistently higher power consumption. The paper also evaluates how future FPGA boards with components (i.e., off-chip memory and PCIe) on par with those of the GPU board could provide an energy-efficient alternative to GPUs.Peer ReviewedPostprint (published version

A highly parameterizable framework for Conditional Restricted Boltzmann Machine based workloads accelerated with FPGAs and OpenCL

© 2020 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Conditional Restricted Boltzmann Machine (CRBM) is a promising candidate for a multidimensional system modeling that can learn a probability distribution over a set of data. It is a specific type of an artificial neural network with one input (visible) and one output (hidden) layer. Recently published works demonstrate that CRBM is a suitable mechanism for modeling multidimensional time series such as human motion, workload characterization, city traffic analysis. The process of learning and inference of these systems relies on linear algebra functions like matrix–matrix multiplication, and for higher data sets, they are very compute-intensive. In this paper, we present a configurable framework for CRBM based workloads for arbitrary large models. We show how to accelerate the learning process of CRBM with FPGAs and OpenCL, and we conduct an extensive scalability study for different model sizes and system configurations. We show significant improvement in performance/Watt for large models and batch sizes (from 1.51x up to 5.71x depending on the host configuration) when we use FPGA and OpenCL for the acceleration, and limited benefits for small models comparing to the state-of-the-art CPU solution.This work was supported by the European Research Council(ERC) under the European Union’s Horizon 2020 research andinnovation programme (grant agreements No 639595); the Min-istry of Economy of Spain under contract TIN2015-65316-P andGeneralitat de Catalunya, Spain under contract 2014SGR1051;the ICREA, Spain Academia program; the BSC-CNS Severo Ochoaprogram, Spain (SEV-2015-0493) and Intel Corporation, UnitedStatesPeer ReviewedPostprint (published version

The impact of different methods of drying and preparation method ration method on the basic chemical composition of hay

The paper presents the results of three different ways of storing the dried mass of hay: bulk, small bales and large roll bales, as well as the impact of three drying methods: natural in the field, artificial drying with cold air and drying with dehumidification (warm air). In the tested meadow in the first swath, the results of chemical analyses showed differences in the method of drying hay. Regarding the tested drying method, the content of dry matter (DM) had significant differences between the storage methods as well as all variants with pre-heated air drying, where the average value of DM was in the interval of 86.18-93.01%. The content of mineral substances for certain methods of preparation and drying ranged from 5.77% to 7.72% on average. The highest content of crude proteins was in all variants of artificial drying and it ranged from 98.6 to 165.7 g/kg DM and had a statistically significant difference. Both methods of artificial post-drying had a significant impact on the cellulose content (33.76% to 28.86%) compared to drying in the traditional way because postponing the mowing time increases the cellulose content. The drying method had a statistically high significant difference on the content of neutral detergent fibres (NDF) and acidic detergent fibres (ADF), while the method of storage had no major impact. Knowledge of changes in the quality of hay during the growing season is of particular importance form the aspect of ruminant nutrition and balanced rations. The amount and quality of obtained hay is significantly affected by the time of mowing, height of mowing, swath, fertilization, floristic composition and weather conditions during drying of the green mass

Digital bank-to-turn control and guidance

SIGLEAvailable from British Library Document Supply Centre- DSC:DX96927 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Comparison of SRAM cells for 10-nm SOI FinFETs under process and environmental variations

We explore the 6T and 8T SRAM design spaces through read static noise margin (RSNM), word-line write margin, and leakage for future 10-nm FinFETs. Process variations are based on the ITRS and modeled at device (TCAD) level. We propose a method to incorporate them into a BSIM-CMG model card for time-efficient simulation. We analyze cells with different fin numbers, supply voltages, and temperatures. Results show a 1.8× improvement of RSNM for 8T SRAM cells, the need for stronger pull-downs to secure read stability in 6Ts, and high leakage sensitivity to temperature (10× between 40°C and 100°C). As a specific example, we show how the RSNM of a 6T SRAM cell can be improved by using back-gate biasing techniques for independent-gate FinFETs. We show how WLMN is increased by reducing the strength of pull-up transistors when reverse back-gate biasing is applied on it and how the RSNM can be increased by reducing the strength of access transistor by reverse back-gate biasing of pass-gate transistors. When combining these two techniques, RSNM can be improved up to 25% without compromising cell write ability for any sample. In general, when compared to previous technologies, read stability is untouched, writeability is reduced, and leakage keeps stable.Peer ReviewedPostprint (published version

Enhancing 3T DRAMs for SRAM replacement under 10nm tri-gate SOI FinFETs

In this paper, we pr esent the dynamic 3T memory cell for future 10nm tri-gate FinFETs as a potential replacement for classical 6T SRAM cell for implementation in high speed cache memories. We investigate read access time, retention time, and static power consumption of the cell when it is exposed to the effects of process and environmental variations. Process variations are extracted from the ITRS predictions and they are modeled at device level. For simulation, we use 10nm SOI tri-gate FinFET BSIM-CMG model card developed by the University of Glasgow, Device Modeling Group. When compared to the classical 6T SRAM, 3T cell has 40% smaller area, leakage is reduced up to 14 times while access time is approximately the same. In order to achieve higher retention times, we propose several cell extensions which, at the same time, enable post- fabrication/run-time adaptability.Peer ReviewedPostprint (published version

DRAM-based coherent caches and how to take advantage of the coherence protocol to reduce the refresh energy

Recent technology trends has turned DRAMs into an interesting candidate to substitute traditional SRAM-based on-chip memory structures (i.e. register file, cache memories). Nevertheless, a major problem to introduce these cells is that they lose their state (i.e. value) over time, and they have to be refreshed. This paper proposes the implementation of coherent caches with DRAM cells. Furthermore, we propose to use the coherence state to tune the refresh overhead. According to our analysis, an average of up to 57% of refresh energy can be saved. Also, comparing to the caches implemented in SRAMs total energy savings are on average up to 39% depending of the refresh policy with a performance loss below 8%.Peer Reviewe