In order to improve the accuracy of loop unrolling factor in the compiler, we propose a loop unrolling method based on improved random decision forest. First, we improve the traditional random decision forest through adding weight value. Second, BSC algorithm based on SMOTE algorithm is proposed to solve the problem of unbalanced data sets. Nearly 1000 loops are selected from several benchmarks, and features extracted from these loops constitute the training set of the loop unrolling factor prediction model. The model has a prediction accuracy of 81 % for the unrolling factor, and the existing Open64 compiler gives 36 % only
Numerous code optimization techniques, including loop nest optimizations, have been developed over t...
Designing a compiler so that it produces optimised code is a difficult task because modern processo...
Loops in programs are the source of many optimizations for improv-ing program performance, particula...
In order to deliver the promise of MooreÂs Law to the enduser, compilers must make decisions that ar...
Compilers base many critical decisions on abstracted architectural models. While recent research has...
We introduce Approximate Unrolling, a loop optimization that reduces execution time and energy consu...
International audienceThis paper improves our previous research effort [1] by providing an efficient...
The development of embedded applications typically faces memory and/or execution time con-straints. ...
International audienceThis article studies an important open problem in backend compilation regardin...
It is well-known that, to optimize a program for speed-up, efforts should be focused on the regions ...
International audienceSoftware pipelining is a powerful technique to expose fine-grain parallelism, ...
ii The high performance of today’s microprocessors is achieved mainly by fast, multipleissuing hardw...
Loop unrolling is a widely adopted loop transformation, commonly used for enabling subsequent optimi...
Modern architectural trends in instruction-level parallelism (ILP) are to increase the computational...
Compiler writers are expected to create effective and inexpensive solutions to NP-hard prob-lems suc...
Numerous code optimization techniques, including loop nest optimizations, have been developed over t...
Designing a compiler so that it produces optimised code is a difficult task because modern processo...
Loops in programs are the source of many optimizations for improv-ing program performance, particula...
In order to deliver the promise of MooreÂs Law to the enduser, compilers must make decisions that ar...
Compilers base many critical decisions on abstracted architectural models. While recent research has...
We introduce Approximate Unrolling, a loop optimization that reduces execution time and energy consu...
International audienceThis paper improves our previous research effort [1] by providing an efficient...
The development of embedded applications typically faces memory and/or execution time con-straints. ...
International audienceThis article studies an important open problem in backend compilation regardin...
It is well-known that, to optimize a program for speed-up, efforts should be focused on the regions ...
International audienceSoftware pipelining is a powerful technique to expose fine-grain parallelism, ...
ii The high performance of today’s microprocessors is achieved mainly by fast, multipleissuing hardw...
Loop unrolling is a widely adopted loop transformation, commonly used for enabling subsequent optimi...
Modern architectural trends in instruction-level parallelism (ILP) are to increase the computational...
Compiler writers are expected to create effective and inexpensive solutions to NP-hard prob-lems suc...
Numerous code optimization techniques, including loop nest optimizations, have been developed over t...
Designing a compiler so that it produces optimised code is a difficult task because modern processo...
Loops in programs are the source of many optimizations for improv-ing program performance, particula...