scholarly journals Measurement-Based Power Optimization Technique for OpenCV on Heterogeneous Multicore Processor

Symmetry ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 1488 ◽  
Author(s):  
Hyeonseok Jung ◽  
Kyoseung Koo ◽  
Hoeseok Yang

Today’s embedded systems often operate computer-vision applications, and are associated with timing and power constraints. Since it is not simple to capture the symmetry between the application and the model, the model-based design approach is generally not applicable to the optimization of computer-vision applications. Thus, in this paper, we propose a measurement-based optimization technique for an open-source computer-vision application library, OpenCV, on top of a heterogeneous multicore processor. The proposed technique consists of two sub-systems: the optimization engine running on a separate host PC, and the measurement library running on the target board. The effectiveness of the proposed optimization technique has been verified in the case study of latency-power co-optimization by using two OpenCV applications—canny edge detection and squeezeNet. It has been shown that the proposed technique not only enables broader design space exploration, but also improves optimality.

Author(s):  
Pablo Bellocq ◽  
Inaki Garmendia ◽  
Jordane Legrand ◽  
Vishal Sethi

Direct Drive Open Rotors (DDORs) have the potential to significantly reduce fuel consumption and emissions relative to conventional turbofans. However, this engine architecture presents many design and operational challenges both at engine and aircraft level. At preliminary design stages, a broad design space exploration is required to identify potential optimum design regions and to understand the main trade offs of this novel engine architecture. These assessments may also aid the development process when compromises need to be performed as a consequence of design, operational or regulatory constraints. Design space exploration assessments are done with 0-D or 1-D models for computational purposes. These simplified 0-D and 1-D models have to capture the impact of the independent variation of the main design and control variables of the engine. Historically, it appears that for preliminary design studies of DDORs, Counter Rotating Turbines (CRTs) have been modelled as conventional turbines and therefore it was not possible to assess the impact of the variation of the number of stages (Nb) of the CRT and rotational speed of the propellers. Additionally, no preliminary design methodology for CRTs was found in the public domain. Part I of this two-part publication proposes a 1-D preliminary design methodology for DDOR CRTs which allows an independent definition of both parts of the CRT. A method for calculating the off-design performance of a known CRT design is also described. In Part II, a 0-D design point efficiency calculation for CRTs is proposed and verified with the 1-D methods. The 1-D and 0-D CRT models were used in an engine control and design space exploration case study of a DDOR with a 4.26m diameter an 10% clipped propeller for a 160 PAX aircraft. For this application: • the design and performance of a 20 stage CRT rotating at 860 rpm (both drums) obtained with the 1-D methods is presented. • differently from geared open rotors, negligible cruise fuel savings can be achieved by an advanced propeller control. • for rotational speeds between 750 and 880 rpm (relatively low speeds for reduced noise), 22 and 20 stages CRTs are required. • engine weight can be kept constant for different design rotational speeds by using the minimum required Nb. • for any target engine weight, TOC and cruise SFC are reduced by reducing the rotational speeds and increasing Nb (also favourable for reducing CRP noise). However additional CRT stages increase engine drag, mechanical complexity and cost.


Author(s):  
Laura Ziegler ◽  
Kemper Lewis

A unique set of cognitive and computational challenges arise in large-scale decision making, in relation to trade-off processing and design space exploration. While several multi-attribute decision making methods exist in the current design literature, many are insufficient or not fully explored for many-attribute decision problems of six or more attributes. To address this scaling in complexity, the methodology presented in this paper strategically elicits preferences over iterative attribute subsets while leveraging principles of the Hypothetical Equivalents and Inequivalents Method (HEIM). A case study demonstrates the effectiveness of the approach in the construction of a systematic representation of preferences and the convergence to a single ‘best’ alternative.


Author(s):  
Pablo Bellocq ◽  
Inaki Garmendia ◽  
Jordane Legrand ◽  
Vishal Sethi

Direct Drive Open Rotors (DDORs) have the potential to significantly reduce fuel consumption and emissions relative to conventional turbofans. However, this engine architecture presents many design and operational challenges both at engine and aircraft level. At preliminary design stages, a broad design space exploration is required to identify potential optimum design regions and to understand the main trade offs of this novel engine architecture. These assessments may also aid the development process when compromises need to be performed as a consequence of design, operational or regulatory constraints. Design space exploration assessments are done with 0-D or 1-D models for computational purposes. These simplified 0-D and 1-D models have to capture the impact of the independent variation of the main design and control variables of the engine. Historically, it appears that for preliminary design studies of DDORS, Counter Rotating Turbines (CRTs) have been modeled as conventional turbines and therefore it was not possible to assess the impact of the variation of the number of stages (Nb) and rotational speed of the propellers. Additionally, no preliminary design methodology for CRTs was found in the public domain. Part I of this two-part publication proposes a 1-D preliminary design methodology for DDOR CRTs. It allows an independent definition of the Nb, rotational speeds of both parts of the CRT, inlet flow conditions, inlet and outlet annulus geometry as well as power extraction. It includes criteria and procedures to calculate: power extraction in each stage, gas path geometry, blade metal angles, flow conditions at each turbine plane and overall CRT efficiency. The feasible torque ratios of a CRT are discussed in this paper. A form factor for the CRT velocity triangles is defined (similar to stage reaction on conventional turbines) and its impact on performance and blade design is discussed. A method for calculating the off-design performance of a CRT is also described in Part I. In Part II, a 0-D design point (DP) efficiency calculation for CRTs is proposed as well as a case study of a DDOR for a 160 PAX aircraft. In the case study, three main aspects are investigated: A) the design and performance of a 20 stage CRT for the DDOR application; B) the impact of the control of the propellers on cruise specific fuel consumption, C) the impact of the design rotational speeds and Nb of the CRT on its DP efficiency, engine fuel consumption and engine weight.


2017 ◽  
Vol 2017 ◽  
pp. 1-12
Author(s):  
Andreas G. Savva ◽  
Theocharis Theocharides ◽  
Chrysostomos Nicopoulos

This work presents a design exploration framework for developing a high level Artificial Neural Network (ANN) for fault detection in hardware systems. ANNs can be used for fault detection purposes since they have excellent characteristics such as generalization capability, robustness, and fault tolerance. Designing an ANN in order to be used for fault detection purposes includes different parameters. Through this work, those parameters are presented and analyzed based on simulations. Moreover, after the development of the ANN, in order to evaluate it, a case study scenario based on Networks on Chip is used for detection of interrouter link faults. Simulation results with various synthetic traffic models show that the proposed work can detect up to 96–99% of interrouter link faults with a delay less than 60 cycles. Added to this, the size of the ANN is kept relatively small and they can be implemented in hardware easily. Synthesis results indicate an estimated amount of 0.0523 mW power consumption per neuron for the implemented ANN when computing a complete cycle.


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