Deconstructing iterative optimization

A Deconstructing Iterative Optimization

Iterative optimization is a popular compiler optimization approach that has been studied extensively over the past decade. In this paper, we deconstruct iterative optimization by evaluating whether it works across data sets and by analyzing why it works. Up to now, most iterative optimization studies are based on a premise which was never truly evaluated: that it is possible to learn the best c...

Efficient iterative policy optimization

We tackle the issue of finding a good policy when the number of policy updates is limited. This is done by approximating the expected policy reward as a sequence of concave lower bounds which can be efficiently maximized, drastically reducing the number of policy updates required to achieve good performance. We also extend existing methods to negative rewards, enabling the use of control variates.

Fficient Iterative Policy Optimization

We tackle the issue of finding a good policy when the number of policy updates is limited. This is done by approximating the expected policy reward as a sequence of concave lower bounds which can be efficiently maximized, drastically reducing the number of policy updates required to achieve good performance. We also extend existing methods to negative rewards, enabling the use of control variates.

Iterative Methods for Optimization

Iterative Compilation in Program Optimization

In this paper we describe a novel approach to program optimization, namely, iterative compilation. This technique enables compilers to deliver e cient code by searching for the best sequence of optimizations using pro le-directed feedback. We have implemented this iterative approach in an existing compiler system which is designed for embedded systems and compared its performance to two of the ...