AbstractThe use of an OpenMP compiler optimized for the corresponding multicore system is a good option, but it is possible in a system to have access to more than one compiler and different compilers can appropriately optimize different parts of the code. In this paper we present a proposal for an autotuning system for linear algebra routines that decides the best compiler for each situation, as well as other parameter values, as, for example, the number of threads to generate
This thesis describes novel techniques and test implementations for optimizing numerically intensive...
Abstract. We present a systematic methodology for deriving and implementing linear algebra libraries...
Autotuning is a method which enables a program to automatically choose the most suitable parameters ...
AbstractThe use of an OpenMP compiler optimized for the corresponding multicore system is a good opt...
AbstractThe introduction of auto-tuning techniques in linear algebra routines using hybrid combinati...
Abstract. In this paper we describe an autotuning tool for optimiza-tion of OpenMP applications on h...
The final publication is available at Springer via http://dx.doi.org/10.1007/s10766-013-0249-6The in...
Abstract. Autotuning technology has emerged recently as a systematic process for evaluating alternat...
AbstractIn this work the behavior of the multithreaded implementation of some LAPACK routines on PLA...
This paper describes an approach for the automatic generation and optimization of numerical softwar...
Abstract. We present a prototypical linear algebra compiler that automatically exploits domain-speci...
This report summarizes the progress made as part of a one year lab-directed research and development...
This paper presents a dynamic task scheduling approach to executing dense linear algebra algorithms ...
This paper presents a self-optimization methodology for parallel linear algebra rou-tines on heterog...
With the emergence of thread-level parallelism as the primary means for continued improvement of per...
This thesis describes novel techniques and test implementations for optimizing numerically intensive...
Abstract. We present a systematic methodology for deriving and implementing linear algebra libraries...
Autotuning is a method which enables a program to automatically choose the most suitable parameters ...
AbstractThe use of an OpenMP compiler optimized for the corresponding multicore system is a good opt...
AbstractThe introduction of auto-tuning techniques in linear algebra routines using hybrid combinati...
Abstract. In this paper we describe an autotuning tool for optimiza-tion of OpenMP applications on h...
The final publication is available at Springer via http://dx.doi.org/10.1007/s10766-013-0249-6The in...
Abstract. Autotuning technology has emerged recently as a systematic process for evaluating alternat...
AbstractIn this work the behavior of the multithreaded implementation of some LAPACK routines on PLA...
This paper describes an approach for the automatic generation and optimization of numerical softwar...
Abstract. We present a prototypical linear algebra compiler that automatically exploits domain-speci...
This report summarizes the progress made as part of a one year lab-directed research and development...
This paper presents a dynamic task scheduling approach to executing dense linear algebra algorithms ...
This paper presents a self-optimization methodology for parallel linear algebra rou-tines on heterog...
With the emergence of thread-level parallelism as the primary means for continued improvement of per...
This thesis describes novel techniques and test implementations for optimizing numerically intensive...
Abstract. We present a systematic methodology for deriving and implementing linear algebra libraries...
Autotuning is a method which enables a program to automatically choose the most suitable parameters ...