| 1. |
- Kanai, M, et al.
(författare)
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- 2023
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swepub:Mat__t
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| 2. |
- Colucci, A., et al.
(författare)
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MLComp : A Methodology for Machine Learning-based Performance Estimation and Adaptive Selection of Pareto-Optimal Compiler Optimization Sequences
- 2021
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Ingår i: Proceedings -Design, Automation and Test in Europe, DATE. - : Institute of Electrical and Electronics Engineers Inc.. - 9783981926354 ; , s. 108-113
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Konferensbidrag (refereegranskat)abstract
- Embedded systems have proliferated in various consumer and industrial applications with the evolution of Cyber-Physical Systems and the Internet of Things. These systems are subjected to stringent constraints so that embedded software must be optimized for multiple objectives simultaneously, namely reduced energy consumption, execution time, and code size. Compilers offer optimization phases to improve these metrics. However, proper selection and ordering of them depends on multiple factors and typically requires expert knowledge. State-of-the-art optimizers facilitate different platforms and applications case by case, and they are limited by optimizing one metric at a time, as well as requiring a time-consuming adaptation for different targets through dynamic profiling. To address these problems, we propose the novel MLComp methodology, in which optimization phases are sequenced by a Reinforcement Learning-based policy. Training of the policy is supported by Machine Learning-based analytical models for quick performance estimation, thereby drastically reducing the time spent for dynamic profiling. In our framework, different Machine Learning models are automatically tested to choose the best-fitting one. The trained Performance Estimator model is leveraged to efficiently devise Reinforcement Learning-based multi-objective policies for creating quasi-optimal phase sequences. Compared to state-of-the-art estimation models, our Performance Estimator model achieves lower relative error (< 2%) with up to 50 × faster training time over multiple platforms and application domains. Our Phase Selection Policy improves execution time and energy consumption of a given code by up to 12% and 6%, respectively. The Performance Estimator and the Phase Selection Policy can be trained efficiently for any target platform and application domain. © 2021 EDAA.
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| 3. |
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| 4. |
- Jamali, Imran Ali, et al.
(författare)
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A spatial multi-criteria analysis approach for locating suitable sites for construction of subsurface dams in northern Pakistan
- 2014
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Ingår i: Water resources management. - : Springer Science and Business Media LLC. - 0920-4741 .- 1573-1650. ; 28:14, s. 5157-5174
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Tidskriftsartikel (refereegranskat)abstract
- Pakistan is an agricultural country with an increasing interest for hydropower. Water management problems such as sedimentation and evaporation have been of high concern for surface water reservoirs for many years. Therefore, groundwater storage through subsurface dams could be promising, especially considering the monsoon rainfall and seasonal river flows in Pakistan. The paper aims to develop and test a methodology to locate suitable sites for construction of subsurface dams using spatial multi-criteria analysis (SMCA) in the northern parts of Pakistan. For the study, spatial data on geology, slope, land cover, soil depth and topographic wetness index (TWI) was used. Two weighting techniques, i.e. the analytic hierarchy process (AHP) and the factor interaction method (FIM), were employed and compared. The sensitivity of the two methods as well as of the model parameters was analysed. The suitability map derived from AHP yielded about 3 % (16 km(2)) of the total area as most suitable, about 4 % (22 km(2)) as moderately suitable and about 0.8 % (5 km(2)) as least suitable. The suitability map derived from FIM identified about 2.7 % (14 km(2)) of the total area as most suitable, about 4 % (22 km(2)) as moderately suitable and about 1 % (7 km(2)) as least suitable. The sensitivity analyses suggested that AHP was a more robust weighting technique than FIM and that land cover was the most sensitive factor. The methodology presented here shows promising results and could be used in early planning to locate suitable sites for construction of subsurface dams.
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| 5. |
- Naveed, H. B., et al.
(författare)
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Model microcavity laser with CdSe/CdS quantum dots as lasing media
- 2016
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Ingår i: Laser physics. - : Institute of Physics Publishing (IOPP). - 1054-660X .- 1555-6611. ; 26:2
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Tidskriftsartikel (refereegranskat)abstract
- A model is established for a microcavity laser with cadmium selenium/cadmium sulfide (CdSe/CdS) core/shell quantum dots (QDs) as a lasing medium, The research was organised to develop and solve the rate equations for the above mentioned microcavity laser to calculate the output parameters during lasing. Using time-resolved fluorescence spectroscopy, the radiative life time of the lasing medium was measured along with its fluorescence and absorption spectra. A model is also established on the basis of the segment contact method (SCM) to demonstrate the threshold gain profile using the absorption spectrum of CdSe/CdS core/shell type II QDs residing in the cavity. A laser cavity of size 1 mu m was pumped with an optical source (532 nm) to achieve an optimised laser peak at 470nm,
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| 6. |
- Svahnberg, Mikael, et al.
(författare)
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A systematic review on strategic release planning models
- 2010
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Ingår i: Information and Software Technology. - : Elsevier. - 0950-5849 .- 1873-6025. ; 52:3, s. 237-248
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Forskningsöversikt (refereegranskat)abstract
- Strategic release planning (sometimes referred to as road-mapping) is an important phase of the requirements engineering process performed at product level. It is concerned with selection and assignment of requirements in sequences of releases such that important technical and resource constraints are fulfilled. Objectives: In this study we investigate which strategic release planning models have been proposed, their degree of empirical validation, their factors for requirements selection, and whether they are intended for a bespoke or market-driven requirements engineering context. Methods: In this systematic review a number of article sources are used, including Compendex, Inspec, IEEE Xplore, ACM Digital Library, and Springer Link. Studies are selected after reading titles and abstracts to decide whether the articles are peer reviewed, and relevant to the subject. Results: Twenty four strategic release planning models are found and mapped in relation to each other, and a taxonomy of requirements selection factors is constructed. Conclusions: We conclude that many models are related to each other and use similar techniques to address the release planning problem. We also conclude that several requirement selection factors are covered in the different models, but that many methods fail to address factors such as stakeholder value or internal value. Moreover, we conclude that there is a need for further empirical validation of the models in full scale industry trials. © 2009 Elsevier B.V. All rights reserved.
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