Add to ORKGWe develop an online optimisation framework for self tuning of computer systems. Towards this, we first discuss suitable objective functions. We then develop an iterative technique that is robust to noisy measurements of objective function and also requires fewer perturbations on the configuration. We essentially adapt the Nelder-Mead algorithm to work with constrained variables and also allow noisy measurements. Extensive experimental results on a queueing model and on an actual system illustrate the performance of our scheme
We develop an online gradient algorithm for optimizing the performance of product-form networks thro...
In the autonomic computing context, the system is perceived as a set of autonomous elements capable ...
Abstract Optimisation algorithms with good anytime behaviour try to return as high-quality solutions...
Computer systems hosting critical e-commerce applications must typically satisfy stringent quality-o...
Recent advances in technology and computer sci- ence play a key role towards the design of the next ...
Automatic tuning (auto-tuning) of software has emerged in recent years as a promising method that tr...
La plupart des composants des systèmes à Haute Performance, qu'ils soient matériels ou logiciels, so...
This paper proposes uRace, a unified race algorithm for efficient offline parameter tuning of determ...
A new optimization algorithm is introduced for online optimization applications. The algorithm was m...
Due to their complexity, modern systems expose many con-figuration parameters which users must ...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
Many optimisation problems are of an online—also called dynamic—nature, where new information is exp...
The end of Moore's Law and the breakdown of Dennard's scaling mean thatincreasing hardware ...
A new method for designing self-tuning control systems is proposed. The ultimate goal of the present...
We develop a gradient algorithm for optimizing the performance of product-form networks through onli...
We develop an online gradient algorithm for optimizing the performance of product-form networks thro...
In the autonomic computing context, the system is perceived as a set of autonomous elements capable ...
Abstract Optimisation algorithms with good anytime behaviour try to return as high-quality solutions...
Computer systems hosting critical e-commerce applications must typically satisfy stringent quality-o...
Recent advances in technology and computer sci- ence play a key role towards the design of the next ...
Automatic tuning (auto-tuning) of software has emerged in recent years as a promising method that tr...
La plupart des composants des systèmes à Haute Performance, qu'ils soient matériels ou logiciels, so...
This paper proposes uRace, a unified race algorithm for efficient offline parameter tuning of determ...
A new optimization algorithm is introduced for online optimization applications. The algorithm was m...
Due to their complexity, modern systems expose many con-figuration parameters which users must ...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
Many optimisation problems are of an online—also called dynamic—nature, where new information is exp...
The end of Moore's Law and the breakdown of Dennard's scaling mean thatincreasing hardware ...
A new method for designing self-tuning control systems is proposed. The ultimate goal of the present...
We develop a gradient algorithm for optimizing the performance of product-form networks through onli...
We develop an online gradient algorithm for optimizing the performance of product-form networks thro...
In the autonomic computing context, the system is perceived as a set of autonomous elements capable ...
Abstract Optimisation algorithms with good anytime behaviour try to return as high-quality solutions...