RWRoute: An Open-source Timing-driven Router for Commercial FPGAs

2022 ◽  
Vol 15 (1) ◽  
pp. 1-27
Author(s):  
Yun Zhou ◽  
Pongstorn Maidee ◽  
Chris Lavin ◽  
Alireza Kaviani ◽  
Dirk Stroobandt

One of the key obstacles to pervasive deployment of FPGA accelerators in data centers is their cumbersome programming model. Open source tooling is suggested as a way to develop alternative EDA tools to remedy this issue. Open source FPGA CAD tools have traditionally targeted academic hypothetical architectures, making them impractical for commercial devices. Recently, there have been efforts to develop open source back-end tools targeting commercial devices. These tools claim to follow an alternate data-driven approach that allows them to be more adaptable to the domain requirements such as faster compile time. In this paper, we present RWRoute, the first open source timing-driven router for UltraScale+ devices. RWRoute is built on the RapidWright framework and includes the essential and pragmatic features found in commercial FPGA routers that are often missing from open source tools. Another valuable contribution of this work is an open-source lightweight timing model with high fidelity timing approximations. By leveraging a combination of architectural knowledge, repeating patterns, and extensive analysis of Vivado timing reports, we obtain a slightly pessimistic, lumped delay model within 2% average accuracy of Vivado for UltraScale+ devices. Compared to Vivado, RWRoute results in a 4.9× compile time improvement at the expense of 10% Quality of Results (QoR) loss for 665 synthetic and six real designs. A main benefit of our router is enabling fast partial routing at the back-end of a domain-specific flow. Our initial results indicate that more than 9× compile time improvement is achievable for partial routing. The results of this paper show how such a router can be beneficial for a low touch flow to reduce dependency on commercial tools.

2018 ◽  
Vol 5 (2) ◽  
pp. 60-67 ◽  
Author(s):  
Dwi Yulianto ◽  
Retno Nugroho Whidhiasih ◽  
Maimunah Maimunah

ABSTRACT   Banana fruit is a commodity that contributes a great value to both national and international fruit production achievement. The government through the National Standardization Agency establishes standards to maintain the quality of bananas. The purpose of this Project is to classify the stages of maturity of Ambon banana base on the color index using Naïve Bayes method in accordance with the regulations of SNI 7422:2009. Naive Bayes is used as a method in the classification process by comparing the probability values generated from the variable value of each model to determine the stage of Ambon banana maturity. The data used is the primary data image of 105 pieces of Ambon banana. By using 3 models which consists of different variables obtained the same greatest average accuracy by using the 2nd model which has 9 variable values (r, g, b, v, * a, * b, entropy, energy, and homogeneity) and the 3rd model has 7 variable values (r, g, b, v , * a, entropy and homogeneity) that is 90.48%.   Keywords: banana maturity, classification, image processing     ABSTRAK   Buah pisang merupakan komoditas yang memberikan kontribusi besar terhadap angka produksi buah nasional maupun internasional. Pemerintah melalui Badan Standarisasi Nasional menetapkan standar untuk buah pisang, menjaga mutu  buah pisang. Tujuan dari penelitian ini adalah klasifikasi tahapan kematangan dari buah pisang ambon berdasarkan indeks warna menggunakan metode Naïve Bayes  sesuai dengan SNI 7422:2009. Naive bayes digunakan sebagai metode dalam proses pengklasifikasian dengan cara membandingkan nilai probabilitas yang dihasilkan dari nilai variabel penduga setiap model untuk menentukan tahap kematangan pisang ambon. Data yang digunakan adalah data primer citra pisang ambon sebanyak 105. Dengan menggunakan 3 buah model yang terdiri dari variabel penduga yang berbeda didapatkan akurasi rata-rata terbesar yang sama yaitu dengan menggunakan model ke-2 yang mempunyai 9 nilai variabel (r, g, b, v, *a, *b, entropi, energi, dan homogenitas) dan model ke-3 yang mempunyai 7 nilai variabel (r, g, b, v, *a, entropi dan homogenitas) yaitu sebesar 90.48%.   Kata Kunci : kematangan pisang,  klasifikasi, pengolahan citra


SLEEP ◽  
2020 ◽  
Author(s):  
Luca Menghini ◽  
Nicola Cellini ◽  
Aimee Goldstone ◽  
Fiona C Baker ◽  
Massimiliano de Zambotti

Abstract Sleep-tracking devices, particularly within the consumer sleep technology (CST) space, are increasingly used in both research and clinical settings, providing new opportunities for large-scale data collection in highly ecological conditions. Due to the fast pace of the CST industry combined with the lack of a standardized framework to evaluate the performance of sleep trackers, their accuracy and reliability in measuring sleep remains largely unknown. Here, we provide a step-by-step analytical framework for evaluating the performance of sleep trackers (including standard actigraphy), as compared with gold-standard polysomnography (PSG) or other reference methods. The analytical guidelines are based on recent recommendations for evaluating and using CST from our group and others (de Zambotti and colleagues; Depner and colleagues), and include raw data organization as well as critical analytical procedures, including discrepancy analysis, Bland–Altman plots, and epoch-by-epoch analysis. Analytical steps are accompanied by open-source R functions (depicted at https://sri-human-sleep.github.io/sleep-trackers-performance/AnalyticalPipeline_v1.0.0.html). In addition, an empirical sample dataset is used to describe and discuss the main outcomes of the proposed pipeline. The guidelines and the accompanying functions are aimed at standardizing the testing of CSTs performance, to not only increase the replicability of validation studies, but also to provide ready-to-use tools to researchers and clinicians. All in all, this work can help to increase the efficiency, interpretation, and quality of validation studies, and to improve the informed adoption of CST in research and clinical settings.


Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1906
Author(s):  
Jia-Zheng Jian ◽  
Tzong-Rong Ger ◽  
Han-Hua Lai ◽  
Chi-Ming Ku ◽  
Chiung-An Chen ◽  
...  

Diverse computer-aided diagnosis systems based on convolutional neural networks were applied to automate the detection of myocardial infarction (MI) found in electrocardiogram (ECG) for early diagnosis and prevention. However, issues, particularly overfitting and underfitting, were not being taken into account. In other words, it is unclear whether the network structure is too simple or complex. Toward this end, the proposed models were developed by starting with the simplest structure: a multi-lead features-concatenate narrow network (N-Net) in which only two convolutional layers were included in each lead branch. Additionally, multi-scale features-concatenate networks (MSN-Net) were also implemented where larger features were being extracted through pooling the signals. The best structure was obtained via tuning both the number of filters in the convolutional layers and the number of inputting signal scales. As a result, the N-Net reached a 95.76% accuracy in the MI detection task, whereas the MSN-Net reached an accuracy of 61.82% in the MI locating task. Both networks give a higher average accuracy and a significant difference of p < 0.001 evaluated by the U test compared with the state-of-the-art. The models are also smaller in size thus are suitable to fit in wearable devices for offline monitoring. In conclusion, testing throughout the simple and complex network structure is indispensable. However, the way of dealing with the class imbalance problem and the quality of the extracted features are yet to be discussed.


Author(s):  
Huaiwei Yang ◽  
Shuang Liu ◽  
Lin Gui ◽  
Yongxin Zhao ◽  
Jun Sun ◽  
...  

2021 ◽  
Vol 11 (12) ◽  
pp. 5690
Author(s):  
Mamdouh Alenezi

The evolution of software is necessary for the success of software systems. Studying the evolution of software and understanding it is a vocal topic of study in software engineering. One of the primary concepts of software evolution is that the internal quality of a software system declines when it evolves. In this paper, the method of evolution of the internal quality of object-oriented open-source software systems has been examined by applying a software metric approach. More specifically, we analyze how software systems evolve over versions regarding size and the relationship between size and different internal quality metrics. The results and observations of this research include: (i) there is a significant difference between different systems concerning the LOC variable (ii) there is a significant correlation between all pairwise comparisons of internal quality metrics, and (iii) the effect of complexity and inheritance on the LOC was positive and significant, while the effect of Coupling and Cohesion was not significant.


2015 ◽  
Vol 19 (4) ◽  
pp. 791-813 ◽  
Author(s):  
Zilia Iskoujina ◽  
Joanne Roberts

Purpose – This paper aims to add to the understanding of knowledge sharing in online communities through an investigation of the relationship between individual participant’s motivations and management in open source software (OSS) communities. Drawing on a review of literature concerning knowledge sharing in organisations, the factors that motivate participants to share their knowledge in OSS communities, and the management of such communities, it is hypothesised that the quality of management influences the extent to which the motivations of members actually result in knowledge sharing. Design/methodology/approach – To test the hypothesis, quantitative data were collected through an online questionnaire survey of OSS web developers with the aim of gathering respondents’ opinions concerning knowledge sharing, motivations to share knowledge and satisfaction with the management of OSS projects. Factor analysis, descriptive analysis, correlation analysis and regression analysis were used to explore the survey data. Findings – The analysis of the data reveals that the individual participant’s satisfaction with the management of an OSS project is an important factor influencing the extent of their personal contribution to a community. Originality/value – Little attention has been devoted to understanding the impact of management in OSS communities. Focused on OSS developers specialising in web development, the findings of this paper offer an important original contribution to understanding the connections between individual members’ satisfaction with management and their motivations to contribute to an OSS project. The findings reveal that motivations to share knowledge in online communities are influenced by the quality of management. Consequently, the findings suggest that appropriate management can enhance knowledge sharing in OSS projects and online communities, and organisations more generally.


2021 ◽  
Author(s):  
Jason Hunter ◽  
Mark Thyer ◽  
Dmitri Kavetski ◽  
David McInerney

&lt;p&gt;Probabilistic predictions provide crucial information regarding the uncertainty of hydrological predictions, which are a key input for risk-based decision-making. However, they are often excluded from hydrological modelling applications because suitable probabilistic error models can be both challenging to construct and interpret, and the quality of results are often reliant on the objective function used to calibrate the hydrological model.&lt;/p&gt;&lt;p&gt;We present an open-source R-package and an online web application that achieves the following two aims. Firstly, these resources are easy-to-use and accessible, so that users need not have specialised knowledge in probabilistic modelling to apply them. Secondly, the probabilistic error model that we describe provides high-quality probabilistic predictions for a wide range of commonly-used hydrological objective functions, which it is only able to do by including a new innovation that resolves a long-standing issue relating to model assumptions that previously prevented this broad application. &amp;#160;&lt;/p&gt;&lt;p&gt;We demonstrate our methods by comparing our new probabilistic error model with an existing reference error model in an empirical case study that uses 54 perennial Australian catchments, the hydrological model GR4J, 8 common objective functions and 4 performance metrics (reliability, precision, volumetric bias and errors in the flow duration curve). The existing reference error model introduces additional flow dependencies into the residual error structure when it is used with most of the study objective functions, which in turn leads to poor-quality probabilistic predictions. In contrast, the new probabilistic error model achieves high-quality probabilistic predictions for all objective functions used in this case study.&lt;/p&gt;&lt;p&gt;The new probabilistic error model and the open-source software and web application aims to facilitate the adoption of probabilistic predictions in the hydrological modelling community, and to improve the quality of predictions and decisions that are made using those predictions. In particular, our methods can be used to achieve high-quality probabilistic predictions from hydrological models that are calibrated with a wide range of common objective functions.&lt;/p&gt;


2021 ◽  
Vol 4 (2) ◽  
pp. 192-203
Author(s):  
Ida Bagus Ary Indra Iswara ◽  
I Putu Pedro Kastika Yasa

The use of video conferencing technology is increasing due to the COVID-19 pandemic. Bigbluebutton and jitsi are examples of open source video conferencing platforms that can be installed on their own servers. The server is created using a cloud-based virtual machine. Analysis of quality of service which includes delay, packet loss, throughput, and jitter is needed to determine the quality of service and the comparison of the two platforms. Observations were also made on the use of CPU, memory / RAM, and disk usage for each server. There are 3 test scenarios carried out. Each scenario is carried out on each existing VM specification. From this test, it is known that in the delay parameter, the highest bigbluebutton is obtained, which is 35,35 ms. And then the highest jitsi delay is 17,66 ms. In packet loss parameters, jitsi obtained the highest yield, namely 0,29%, while for bigbluebutton only 0,16% of packet loss was the highest. Throughput, bigbluebutton and jitsi all got very bad results. However, bigbluebutton obtained better results, namely, the highest throughput was 5.6%. While Jitsi obtained the highest throughput, namely 2,8%. Whereas for the jitter parameter, jitsi obtained 0,00 ms results on all tests in each VM. Meanwhile, bigbluebutton, get 0,1 ms on test 3 on VM 1


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