scholarly journals Control Variate Approximation for DNN Accelerators

Author(s):  
Georgios Zervakis ◽  
Ourania Spantidi ◽  
Iraklis Anagnostopoulos ◽  
Hussam Amrouch ◽  
Jorg Henkel
Keyword(s):  
2021 ◽  
Vol 31 (4) ◽  
Author(s):  
Rémi Leluc ◽  
François Portier ◽  
Johan Segers

1992 ◽  
Vol 38 (3) ◽  
pp. 388-399 ◽  
Author(s):  
Mohamed A. Ahmed ◽  
Donald Gross ◽  
Douglas R. Miller

2014 ◽  
Vol 620 ◽  
pp. 417-423 ◽  
Author(s):  
Zhong Wen Xing ◽  
Zhi Wei Xu ◽  
Hong Liang Yang ◽  
Cheng Xi Lei

A finite element model of high-strength rectangular section steel tube in rotary-draw bending is established to study the stress and strain in the bending process. Based on control variate method, this paper analyzes the influence laws of three geometric parameters on rotary-draw bending. The results show that bending radius is the most important factor, forming property increases significantly with the increase of bending radius, the trends of cracking and wrinkling are all decreased. The thickness of wall has influence on the strain of inwall, thinner tube may cause crack and wrinkle. Fillet radius has no effect on ektexine, the strain of inwall decreases slightly with the increase of fillet radius.


2018 ◽  
Vol 24 (2) ◽  
pp. 101-115 ◽  
Author(s):  
Mohamed-Slim Alouini ◽  
Nadhir Ben Rached ◽  
Abla Kammoun ◽  
Raul Tempone

Abstract The sum of log-normal variates is encountered in many challenging applications such as performance analysis of wireless communication systems and financial engineering. Several approximation methods have been reported in the literature. However, these methods are not accurate in the tail regions. These regions are of primordial interest as small probability values have to be evaluated with high precision. Variance reduction techniques are known to yield accurate, yet efficient, estimates of small probability values. Most of the existing approaches have focused on estimating the right-tail of the sum of log-normal random variables (RVs). Here, we instead consider the left-tail of the sum of correlated log-normal variates with Gaussian copula, under a mild assumption on the covariance matrix. We propose an estimator combining an existing mean-shifting importance sampling approach with a control variate technique. This estimator has an asymptotically vanishing relative error, which represents a major finding in the context of the left-tail simulation of the sum of log-normal RVs. Finally, we perform simulations to evaluate the performances of the proposed estimator in comparison with existing ones.


2021 ◽  
Vol 43 (3) ◽  
pp. A2268-A2294
Author(s):  
Jamie Fox ◽  
Giray Ökten

1992 ◽  
Vol 24 (01) ◽  
pp. 172-201 ◽  
Author(s):  
Søren Asmussen ◽  
Reuven Y. Rubinstein

This paper studies computer simulation methods for estimating the sensitivities (gradient, Hessian etc.) of the expected steady-state performance of a queueing model with respect to the vector of parameters of the underlying distribution (an example is the gradient of the expected steady-state waiting time of a customer at a particular node in a queueing network with respect to its service rate). It is shown that such a sensitivity can be represented as the covariance between two processes, the standard output process (say the waiting time process) and what we call the score function process which is based on the score function. Simulation procedures based upon such representations are discussed, and in particular a control variate method is presented. The estimators and the score function process are then studied under heavy traffic conditions. The score function process, when properly normalized, is shown to have a heavy traffic limit involving a certain variant of two-dimensional Brownian motion for which we describe the stationary distribution. From this, heavy traffic (diffusion) approximations for the variance constants in the large sample theory can be computed and are used as a basis for comparing different simulation estimators. Finally, the theory is supported by numerical results.


Materials ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 1864 ◽  
Author(s):  
Ziling Cao ◽  
Chen Zhang ◽  
Zhuoxin Yang ◽  
Qing Qin ◽  
Zhihua Zhang ◽  
...  

Carbon aerogel (CA) has a rich porous structure, in which micropores and mesopores provide a huge specific surface area to form electric double layers. This property can be applied to the application of capacitive deionization (CDI). The adsorption effect of CA electrode on Cu2+ in an aqueous solution was explored for solving heavy metal water pollution. The CAs were synthesized by a sol-gel process using an atmospheric drying method. The structure of CAs was characterized by scanning in an electron microscope (SEM) and nitrogen adsorption/desorption techniques. The adsorption system was built using Cu2+ solution as the simulation of heavy metal pollution solution. The control variate method was used to investigate the effect of the anion species in copper solution, the molar ratio of resorcinol to catalyst (R/C) of CA, and the applied voltage and concentration of copper ion on the adsorption results.


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