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Optimization of multilateral well trajectories using pattern search and genetic algorithms
, Article Results in Engineering ; Volume 16 , 2022 ; 25901230 (ISSN) ; Biglarian, H ; Beyrami, H ; Salimi, M ; Sharif University of Technology
Elsevier B.V
2022
Abstract
Multilateral well is a promising technology in developing oil reservoirs. Because this technology may increase the production rate per well and reduce the costs of field development, it is rapidly replacing the old methods. This study uses a three-dimensional line-source model with direct search methods, including pattern search and genetic algorithms to optimize the well trajectories. This method was applied to several cases, with different forms of wells and reservoirs. In all cases, significant improvement was observed in the production rate. Furthermore, the production enhancement using the optimized well trajectories which have curved-paths is compared to the case with linear well...
NURA: A framework for supporting non-uniform resource accesses in gpus
, Article Proceedings of the ACM on Measurement and Analysis of Computing Systems ; Volume 6, Issue 1 , 2022 ; 24761249 (ISSN) ; Mahani, N ; Baxishi, H ; Yousefzadeh Asl Miandoab, E ; Sadrosadati, M ; Sarbazi Azad, H ; Sharif University of Technology
Association for Computing Machinery
2022
Abstract
Multi-application execution in Graphics Processing Units (GPUs), a promising way to utilize GPU resources, is still challenging. Some pieces of prior work (e.g., spatial multitasking) have limited opportunity to improve resource utilization, while other works, e.g., simultaneous multi-kernel, provide fine-grained resource sharing at the price of unfair execution. This paper proposes a new multi-application paradigm for GPUs, called NURA, that provides high potential to improve resource utilization and ensures fairness and Quality-of-Service (QoS). The key idea is that each streaming multiprocessor (SM) executes Cooperative Thread Arrays (CTAs) belong to only one application (similar to the...
NURA: A framework for supporting non-uniform resource accesses in GPUs
, Article Performance Evaluation Review ; Volume 50, Issue 1 , 2022 , Pages 39-40 ; 01635999 (ISSN) ; Mahani, N ; Baxishi, H ; Yousefzadeh, E ; Sadrosadati, M ; Sarbazi Azad, H ; Sharif University of Technology
Association for Computing Machinery
2022
Abstract
Multi-application execution in Graphics Processing Units (GPUs), a promising way to utilize GPU resources, is still challenging. Some pieces of prior work (e.g. spatial multitasking) have limited opportunity to improve resource utilization, while others, e.g. simultaneous multi-kernel, provide fine-grained resource sharing at the price of unfair execution. This paper proposes a new multi-application paradigm for GPUs, called NURA, that provides high potential to improve resource utilization and ensure fairness and Quality-of-Service(QoS). The key idea is that each streaming multiprocessor (SM) executes the Cooperative Thread Arrays (CTAs) that belong to only one application (similar to...
NURA: A framework for supporting non-uniform resource accesses in GPUs
, Article 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS/PERFORMANCE 2022, 6 June 2022 through 10 June 2022 ; 2022 , Pages 39-40 ; 9781450391412 (ISBN) ; Mahani, N ; Baxishi, H ; Yousefzadeh, E ; Sadrosadati, M ; Sarbazi Azad, H ; ACM SIGMETRICS ; Sharif University of Technology
Association for Computing Machinery, Inc
2022
Abstract
Multi-application execution in Graphics Processing Units (GPUs), a promising way to utilize GPU resources, is still challenging. Some pieces of prior work (e.g. spatial multitasking) have limited opportunity to improve resource utilization, while others, e.g. simultaneous multi-kernel, provide fine-grained resource sharing at the price of unfair execution. This paper proposes a new multi-application paradigm for GPUs, called NURA, that provides high potential to improve resource utilization and ensure fairness and Quality-of-Service(QoS). The key idea is that each streaming multiprocessor (SM) executes the Cooperative Thread Arrays (CTAs) that belong to only one application (similar to...
Three-dimensional continuous-time integrated guidance and control design using model predictive control
, Article Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering ; 2022 ; 09544100 (ISSN) ; Khankalantary, S ; Sharif University of Technology
SAGE Publications Ltd
2022
Abstract
In this study, a novel three-dimensional continuous-time integrated guidance and control (IGC) scheme is presented. The proposed method is developed on the basis of generalized model predictive control (GMPC) approach and super-twisting extended state observer (STESO). The GMPC is used to generate the optimal closed form control law for the interceptor and the STESO is applied to estimate the maneuvering target lateral accelerations as well as the lumped disturbances. To the aim of IGC design, a six-degrees-of-freedom model based on the interceptor-target kinematics and interceptor dynamics is constructed. Afterward, the GMPC control law formulation for a nonlinear system exposed to...
Multi-task learning from fixed-wing UAV images for 2D/3D city modelling
, Article American Society for Photogrammetry and Remote Sensing, ASPRS 2021 Annual Conference, 29 March 2021 through 2 April 2021 ; Volume 44, Issue M-3 , 2021 , Pages 1-5 ; 16821750 (ISSN) ; Khoshboresh Masouleh, M ; Sharif University of Technology
International Society for Photogrammetry and Remote Sensing
2021
Abstract
Single-task learning in artificial neural networks will be able to learn the model very well, and the benefits brought by transferring knowledge thus become limited. In this regard, when the number of tasks increases (e.g., semantic segmentation, panoptic segmentation, monocular depth estimation, and 3D point cloud), duplicate information may exist across tasks, and the improvement becomes less significant. Multi-task learning has emerged as a solution to knowledge-transfer issues and is an approach to scene understanding which involves multiple related tasks each with potentially limited training data. Multi-task learning improves generalization by leveraging the domain-specific information...
Efficient nearest-neighbor data sharing in GPUs
, Article ACM Transactions on Architecture and Code Optimization ; Volume 18, Issue 1 , 2021 ; 15443566 (ISSN) ; Sadrosadati, M ; Falahati, H ; Barkhordar, M ; Drumond, M. P ; Sarbazi Azad, H ; Falsafi, B ; Sharif University of Technology
Association for Computing Machinery
2021
Abstract
Stencil codes (a.k.a. nearest-neighbor computations) are widely used in image processing, machine learning, and scientific applications. Stencil codes incur nearest-neighbor data exchange because the value of each point in the structured grid is calculated as a function of its value and the values of a subset of its nearest-neighbor points. When running on Graphics Processing Unit (GPUs), stencil codes exhibit a high degree of data sharing between nearest-neighbor threads. Sharing is typically implemented through shared memories, shuffle instructions, and on-chip caches and often incurs performance overheads due to the redundancy in memory accesses. In this article, we propose Neighbor Data...
Direction finding and beamforming using cylindrical array of dipole antennas in the presence of cylindrical scatterer/reflector including the mutual coupling effect
, Article IET Microwaves, Antennas and Propagation ; Volume 15, Issue 5 , 2021 , Pages 521-528 ; 17518725 (ISSN) ; Farzaneh, F ; Banai, A ; Sharif University of Technology
John Wiley and Sons Inc
2021
Abstract
Three-dimensional dipole arrays are normally used at the proximity of a reflective structure. Filamentary short-circuited dipoles are proposed to model the effect of the reflector structure. The computational burden is significantly reduced by using mutual impedance matrices. An analytical method of modelling the effect of the cylindrical reflector in a three-dimensional cylindrical geometry of dipole antenna arrays is introduced both for direction finding and beamforming applications in the presence of mutual coupling. The results of the implementation of the MUSIC (multiple signal classification) direction-finding algorithm show that the proposed model for accounting the cylindrical...
Simulation of the multi-purpose gamma irradiator dose distribution based on the GEANT4 and GPU system
, Article Journal of Instrumentation ; Volume 16, Issue 7 , 2021 ; 17480221 (ISSN) ; Hosseini, S. A ; Sharif University of Technology
IOP Publishing Ltd
2021
Abstract
Gamma irradiation systems are used extensively in the industry in order to sterilize medical devices, disinfect hygienic products and increase the shelf life of agricultural products. The method of gamma irradiation is superior to the older methods of heat or chemical treatment because it is by far a simpler operation. In this method, only one parameter, the exposure time is controlled, whereas in the other mentioned methods five or six different parameters need to be controlled. The design of irradiation systems generally includes the size and the location of products, and the arrangement of source rack pencils. In order to optimize the design of the gamma irradiation systems, it is needed...
Highly concurrent latency-tolerant register files for GPUs
, Article ACM Transactions on Computer Systems ; Volume 37, Issue 1-4 , 2021 ; 07342071 (ISSN) ; Mirhosseini, A ; Hajiabadi, A ; Ehsani, S. B ; Falahati, H ; Sarbazi Azad, H ; Drumond, M ; Falsafi, B ; Ausavarungnirun, R ; Mutlu, O ; Sharif University of Technology
Association for Computing Machinery
2021
Abstract
Graphics Processing Units (GPUs) employ large register files to accommodate all active threads and accelerate context switching. Unfortunately, register files are a scalability bottleneck for future GPUs due to long access latency, high power consumption, and large silicon area provisioning. Prior work proposes hierarchical register file to reduce the register file power consumption by caching registers in a smaller register file cache. Unfortunately, this approach does not improve register access latency due to the low hit rate in the register file cache. In this article, we propose the Latency-Tolerant Register File (LTRF) architecture to achieve low latency in a two-level hierarchical...
NRSfPP: non-rigid structure-from-perspective projection
, Article Multimedia Tools and Applications ; Volume 80, Issue 6 , 2021 , Pages 9093-9108 ; 13807501 (ISSN) ; Kasaei, S ; Sharif University of Technology
Springer
2021
Abstract
A state-of-the-art algorithm for perspective projection reconstruction of non-rigid surfaces from single-view and realistic videos is proposed. It overcomes the limitations arising from the usage of orthographic camera model and also the complexity and non-linearity issues of perspective projection equation. Unlike traditional non-rigid structure-from-motion (NRSfM) methods, which have been studied only on synthetic datasets and controlled lab environments that require some prior constraints (such as manually segmented objects, limited rotations and occlusions, and full-length trajectories); the proposed method can be used in realistic video sequences. In addition, contrary to previous...
A hybrid of statistical and conditional generative adversarial neural network approaches for reconstruction of 3D porous media (ST-CGAN)
, Article Advances in Water Resources ; Volume 158 , 2021 ; 03091708 (ISSN) ; Masihi, M ; Bozorgmehry Boozarjomehry, R ; Blunt, M. J ; Sharif University of Technology
Elsevier Ltd
2021
Abstract
A coupled statistical and conditional generative adversarial neural network is used for 3D reconstruction of both homogeneous and heterogeneous porous media from a single two-dimensional image. A statistical approach feeds the deep network with conditional data, and then the reconstruction is trained on a deep generative network. The conditional nature of the generative model helps in network stability and convergence which has been optimized through a gradient-descent-based optimization method. Moreover, this coupled approach allows the reconstruction of heterogeneous samples, a critical and serious challenge in conventional reconstruction methods. The main contribution of this work is to...
An exploratory study on application of various classification models to distinguish switchable-hydrophilicity solvents based on 3D-descriptors
, Article Separation Science and Technology (Philadelphia) ; Volume 56, Issue 5 , 2021 , Pages 961-969 ; 01496395 (ISSN) ; Shiri, F ; Sharif University of Technology
Bellwether Publishing, Ltd
2021
Abstract
A set of solvents were classified into the switchable-hydrophilicity solvents (SHSs) and non-switchable-hydrophilicity solvents based on forming or not forming a biphasic mixture with water. SHSs have been developed to make the reaction and product separation processes easier. Herein, three classifier algorithms and various feature selection techniques relay on 3D-molecular descriptors to characterize chemicals and forecast their classes were employed. Cfs-SVM method was employed to perform a classification study. The importance of this study helps to understand more about the presence of hydrophobic groups, their position, and their shape in the molecule. © 2020 Taylor & Francis Group, LLC
3M2RNet: Multi-modal multi-resolution refinement network for semantic segmentation
, Article Computer Vision Conference, CVC 2019, 25 April 2019 through 26 April 2019 ; Volume 944 , 2020 , Pages 544-557 ; Kasaei, S ; Sharif University of Technology
Springer Verlag
2020
Abstract
One of the most important steps towards 3D scene understanding is the semantic segmentation of images. The 3D scene understanding is considered as the crucial requirement in computer vision and robotic applications. With the availability of RGB-D cameras, it is desired to improve the accuracy of the scene understanding process by exploiting the depth along with appearance features. One of the main problems in RGB-D semantic segmentation is how to fuse or combine these two modalities to achieve more advantages of the common and specific features of each modality. Recently, the methods that encounter deep convolutional neural networks have reached the state-of-the-art results in dense...
Prediction of the thorax/pelvis orientations and L5–S1 disc loads during various static activities using neuro-fuzzy
, Article Journal of Mechanical Science and Technology ; Volume 34, Issue 8 , 7 August , 2020 , Pages 3481-3485 ; ISSN: 1738494X ; Sayyaadi, H ; Arjmand, N ; Sharif University of Technology
Korean Society of Mechanical Engineers
2020
Abstract
Spinal posture including thorax/pelvis orientations as well as loads on the intervertebral discs are crucial parameters in biomechanical models and ergonomics to evaluate the risk of low back injury. In vivo measurement of spinal posture toward estimation of spine loads requires the common motion capture techniques and laboratory instruments that are costly and time-consuming. Hence, a closed loop algorithm including an artificial neural network (ANN) and fuzzy logic is proposed here to predict the L5–S1 segment loads and thorax/pelvis orientations in various 3D reaching activities. Two parts namely a fuzzy logic strategy and an ANN from this algorithm; the former, developed based on the...
High-dimensional sparse recovery using modified generalised SL0 and its application in 3D ISAR imaging
, Article IET Radar, Sonar and Navigation ; Volume 14, Issue 8 , 6 July , 2020 , Pages 1267-1278 ; Mehrpooya, A ; Bastani, M. H ; Nayebi, M ; Abbasi, Z ; Sharif University of Technology
Institution of Engineering and Technology
2020
Abstract
Sparse representation can be extended to high dimensions and can be used in many applications, including three-dimensional (3D) Inverse synthetic aperture radar (ISAR) imaging. In this study, the high-dimensional sparse representation problem and a recovery method called high-dimensional smoothed least zero-norm (HDSL0) are formulated. In this method, the theory and computation of tensors and approximating L0 norm using Gaussian functions are used for sparse recovery of high-dimensional data. To enhance the performance of HDSL0, modified regularised high-dimensional SL0 (MRe-HDSL0) algorithm, which benefits from the regularised form of SL0 and an additional hard thresholding step, is...
NRSfPP: non-rigid structure-from-perspective projection
, Article Multimedia Tools and Applications ; 2020 ; Kasaei, S ; Sharif University of Technology
Springer
2020
Abstract
A state-of-the-art algorithm for perspective projection reconstruction of non-rigid surfaces from single-view and realistic videos is proposed. It overcomes the limitations arising from the usage of orthographic camera model and also the complexity and non-linearity issues of perspective projection equation. Unlike traditional non-rigid structure-from-motion (NRSfM) methods, which have been studied only on synthetic datasets and controlled lab environments that require some prior constraints (such as manually segmented objects, limited rotations and occlusions, and full-length trajectories); the proposed method can be used in realistic video sequences. In addition, contrary to previous...
An exploratory study on application of various classification models to distinguish switchable-hydrophilicity solvents based on 3D-descriptors
, Article Separation Science and Technology (Philadelphia) ; 2020 ; Shiri, F ; Sharif University of Technology
Taylor and Francis Inc
2020
Abstract
A set of solvents were classified into the switchable-hydrophilicity solvents (SHSs) and non-switchable-hydrophilicity solvents based on forming or not forming a biphasic mixture with water. SHSs have been developed to make the reaction and product separation processes easier. Herein, three classifier algorithms and various feature selection techniques relay on 3D-molecular descriptors to characterize chemicals and forecast their classes were employed. Cfs-SVM method was employed to perform a classification study. The importance of this study helps to understand more about the presence of hydrophobic groups, their position, and their shape in the molecule. © 2020, © 2020 Taylor & Francis...
Proposal of winding function model for geometrical optimization of linear sinusoidal area resolvers
, Article IEEE Sensors Journal ; Volume 19, Issue 14 , 2019 , Pages 5506-5513 ; 1530437X (ISSN) ; Alipour Sarabsi, R ; Nasiri Gheidari, Z ; Tootoonchian, F ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
This paper proposes an analytical model based on winding function method for analysis of linear sinusoidal area resolver. The accuracy of the proposed model is verified using 3-D time variant finite element analysis and then an optimization based on genetic algorithm is employed for performance improvement of the sensor. Afterwards, the influence of longitudinal end effect on the position error of the studied sensor is investigated and a proper compensating method is presented. Finally, the optimal, compensated sensor is built for experimental measurements. Close agreement between the simulation and the measured position verified the design, analysis, and optimization process. © 2001-2012...
Coordinated DVFS and Precision Control for Deep Neural Networks
, Article IEEE Computer Architecture Letters ; Volume 18, Issue 2 , 2019 , Pages 136-140 ; 15566056 (ISSN) ; Hafez Kolahi, H ; Reda, S ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
Traditionally, DVFS has been the main mechanism to trade-off performance and power. We observe that Deep Neural Network (DNN) applications offer the possibility to trade-off performance, power, and accuracy using both DVFS and numerical precision levels. Our proposed approach, Power-Inference accuracy Trading (PIT), monitors the server's load, and accordingly adjusts the precision of the DNN model and the DVFS setting of GPU to trade-off the accuracy and power consumption with response time. At high loads and tight request arrivals, PIT leverages INT8-precision instructions of GPU to dynamically change the precision of deployed DNN models and boosts GPU frequency to execute the requests...