scholarly journals Modeling and Implementation of a Power Estimation Methodology for SystemC

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Matthias Kuehnle ◽  
Andre Wagner ◽  
Alisson V. Brito ◽  
Juergen Becker
Keyword(s):  
Power Analysis ◽  
Input Data ◽  
Power Estimation ◽  
System Level ◽  
Power Monitoring ◽  
Simulation Based ◽  
Speed Up ◽  
Logic Modules ◽  
Implicit Power ◽  
Power Evaluation

This work describes a methodology to model power consumption of logic modules. A detailed mathematical model is presented and incorporated in a tool for translation of models written in VHDL to SystemC. The functionality for implicit power monitoring and estimation is inserted at module translation. The translation further implements an approach to wrap RTL to TLM interfaces so that the translated module can be connected to a system-level simulator. The power analysis is based on a statistical model of the underlying HW structure and an analysis of input data. The flexibility of the C++ syntax is exploited, to integrate the power evaluation technique. The accuracy and speed-up of the approach are illustrated and compared to a conventional power analysis flow using PPR simulation, based on Xilinx technology.

Simulation-Based Scheduling of Waterway Projects Using a Parallel Genetic Algorithm

2015 ◽  
pp. 334-347 ◽  
Author(s):  
Ning Yang ◽  
Shiaaulir Wang ◽  
Paul Schonfeld
Keyword(s):  
Genetic Algorithm ◽  
Parallel Computing ◽  
Message Passing ◽  
Message Passing Interface ◽  
Computation Time ◽  
Parallel Genetic Algorithm ◽  
Simulation Based ◽  
Multiple Processors ◽  
Simulation Based Optimization ◽  
Speed Up

A Parallel Genetic Algorithm (PGA) is used for a simulation-based optimization of waterway project schedules. This PGA is designed to distribute a Genetic Algorithm application over multiple processors in order to speed up the solution search procedure for a very large combinational problem. The proposed PGA is based on a global parallel model, which is also called a master-slave model. A Message-Passing Interface (MPI) is used in developing the parallel computing program. A case study is presented, whose results show how the adaption of a simulation-based optimization algorithm to parallel computing can greatly reduce computation time. Additional techniques which are found to further improve the PGA performance include: (1) choosing an appropriate task distribution method, (2) distributing simulation replications instead of different solutions, (3) avoiding the simulation of duplicate solutions, (4) avoiding running multiple simulations simultaneously in shared-memory processors, and (5) avoiding using multiple processors which belong to different clusters (physical sub-networks).

powmic: an R package for power assessment in microbiome case–control studies

2020 ◽  
Vol 36 (11) ◽  
pp. 3563-3565
Author(s):  
Li Chen
Keyword(s):  
Power Analysis ◽  
Real Data ◽  
Analytical Form ◽  
R Package ◽  
Case Control ◽  
Supplementary Information ◽  
Metagenomic Sequencing ◽  
Case Control Studies ◽  
Simulation Based ◽  
Over Dispersion

Abstract Summary Power analysis is essential to decide the sample size of metagenomic sequencing experiments in a case–control study for identifying differentially abundant (DA) microbes. However, the complexity of microbial data characteristics, such as excessive zeros, over-dispersion, compositionality, intrinsically microbial correlations and variable sequencing depths, makes the power analysis particularly challenging because the analytical form is usually unavailable. Here, we develop a simulation-based power assessment strategy and R package powmic, which considers the complexity of microbial data characteristics. A real data example demonstrates the usage of powmic. Availability and implementation powmic R package and online tutorial are available at https://github.com/lichen-lab/powmic. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

Automated and Optimal Actuation Voltage Waveform Design for Contact Bouncing Mitigation of MEMS Switches

2014 ◽  
Vol 609-610 ◽  
pp. 1248-1253
Author(s):  
Chen Xu Zhao ◽  
Xin Guo ◽  
Tao Deng ◽  
Ling Li ◽  
Ze Wen Liu
Keyword(s):  
Actuation Voltage ◽  
Waveform Design ◽  
Practical Case ◽  
Voltage Waveform ◽  
Mems Switches ◽  
Mems Switch ◽  
Simulation Based ◽  
Speed Up ◽  
Bouncing Effect

This paper presents an efficient methodology for automated optimal tailoring actuation voltage waveform of MEMS switches aiming at eliminating the detrimental contact bouncing effect to speed up the switching process and improve the mechanical reliability. This is a simulation-based approach where genetic algorithm (GA) is used in combination with a dedicated mechanical model of MEMS switch to derive optimal actuation waveform. The proposed technique has been implemented in SystemC-A, which is extremely well suited for complex modeling, implementation of post-processing of simulation results and optimization algorithms. Effectiveness of proposed approach is corroborated by a practical case study of automated actuation waveform design for a prefabricated DC-contact MEMS switch. The experimental results show that the switching time of the switch by employing optimized actuation voltage waveform is dramatically reduced to 60μs from 95μs, while the bouncing effect is successfully eliminated.

A Reliability-Based Design Method Using Simulation Techniques and Efficient Optimization Approach

2004 ◽  
Author(s):  
Tong Zou ◽  
Sankaran Mahadevan ◽  
Akhil Sopory
Keyword(s):  
Computational Cost ◽  
Nonlinear Problems ◽  
Side Impact ◽  
System Level ◽  
Optimization Approach ◽  
Sequential Approach ◽  
Model Based ◽  
Reliability Based Design ◽  
Reliability Method ◽  
Simulation Based

A novel reliability-based design optimization (RBDO) method using simulation-based techniques for reliability assessments and efficient optimization approach is presented in this paper. In RBDO, model-based reliability analysis needs to be performed to calculate the probability of not satisfying a reliability constraint and the gradient of this probability with respect to each design variable. Among model-based methods, the most widely used in RBDO is the first-order reliability method (FORM). However, FORM could be inaccurate for nonlinear problems and is not applicable for system reliability problems. This paper develops an efficient optimization methodology to perform RBDO using simulation-based techniques. By combining analytical and simulation-based reliability methods, accurate probability of failure and sensitivity information is obtained. The use of simulation also enables both component and system-level reliabilities to be included in RBDO formulation. Instead of using a traditional RBDO formulation in which optimization and reliability computations are nested, a sequential approach is developed to greatly reduce the computational cost. The efficiency of the proposed RBDO approach is enhanced by using a multi-modal adaptive importance sampling technique for simulation-based reliability assessment; and by treating the inactive reliability constraints properly in optimization. A vehicle side impact problem is used to demonstrate the capabilities of the proposed method.

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