STOKE is one of the Superoptimizers which are programs that given a function and a set of instructions of a processor, traverse through a space of programs that compute a given function and try to find the optimal usually in terms of execution speed or size of the binary. Authors of STOKE make some extraordinary claims. They suggest that it is able to produce programs that are multiple times faster than programs without any optimization, and programs which are at least as efficient as programs produced by gcc -O3 and sometimes expert handwritten assembly. The goal of this paper is to check these claims. In this paper classes of programs that STOKE may handle particularly well and any class of programs that stochastic optimization might not ...
This article aims at making iterative optimization practical and usable by speeding up the evaluatio...
In this research the Metropolis-Hastings algorithmis implemented for the problem of program synthesi...
We revisit the well-known greedy algorithm for scheduling independent jobs on parallel processors, w...
The superoptimizer STOKE has previously been shown to be effective at optimizing programs containing...
We formulate the loop-free, binary superoptimization task as a stochastic search problem. The compet...
Modern compilers exploit syntax \& semantics to optimize input programs.Often such optimization ...
This paper discussed two computationally intensive optimisation algorithms for 0-1 integer programs,...
Abstract Peephole optimizers are typically constructed using human-writtenpattern matching rules, an...
This thesis talks about techniques which can be used to optimize run time of algorithms. For a demon...
The classical meaning of superoptimization is to find the optimal code sequence for a single, loop-f...
This article aims at making iterative optimization practical and usable by speeding up the evaluatio...
In theoretical computer science, various notions of efficiency are used for algorithms. The most com...
Automatic algorithm configuration techniques have proved to be successful in finding performance-opt...
This paper theoretically compares the performance of simulated annealing and evolutionary algorithms...
Code super-optimization is the task of transforming any given program to a more efficient version wh...
This article aims at making iterative optimization practical and usable by speeding up the evaluatio...
In this research the Metropolis-Hastings algorithmis implemented for the problem of program synthesi...
We revisit the well-known greedy algorithm for scheduling independent jobs on parallel processors, w...
The superoptimizer STOKE has previously been shown to be effective at optimizing programs containing...
We formulate the loop-free, binary superoptimization task as a stochastic search problem. The compet...
Modern compilers exploit syntax \& semantics to optimize input programs.Often such optimization ...
This paper discussed two computationally intensive optimisation algorithms for 0-1 integer programs,...
Abstract Peephole optimizers are typically constructed using human-writtenpattern matching rules, an...
This thesis talks about techniques which can be used to optimize run time of algorithms. For a demon...
The classical meaning of superoptimization is to find the optimal code sequence for a single, loop-f...
This article aims at making iterative optimization practical and usable by speeding up the evaluatio...
In theoretical computer science, various notions of efficiency are used for algorithms. The most com...
Automatic algorithm configuration techniques have proved to be successful in finding performance-opt...
This paper theoretically compares the performance of simulated annealing and evolutionary algorithms...
Code super-optimization is the task of transforming any given program to a more efficient version wh...
This article aims at making iterative optimization practical and usable by speeding up the evaluatio...
In this research the Metropolis-Hastings algorithmis implemented for the problem of program synthesi...
We revisit the well-known greedy algorithm for scheduling independent jobs on parallel processors, w...