SELECTIVE CODE GENERATION OPTIMIZATION FOR AN ADVANCED DUAL-REPRESENTATION POLYHEDRAL LOOP TRANSFORMATION FRAMEWORK

Patent №

US 8,087,010

Granted

2011-12-27

Filed 2007

Owner

INTERNATIONAL BUSINESS MACHINES CORPORATION

AI components

2

nlp · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

11861493

Mechanisms for selective code generation optimization for an advanced dual-representation polyhedral loop transformation framework are provided. The mechanisms of the illustrative embodiments address the weaknesses of the known polyhedral loop transformation based approaches by providing mechanisms for performing code generation transformations on individual statement instances in an intermediate representation generated by the polyhedral loop transformation optimization of the source code. These code generation transformations have the important property that they do not change program order of the statements in the intermediate representation. This property allows the result of the code generation transformations to be provided back to the polyhedral loop transformation mechanisms in a program statement view, via a new re-entrance path of the illustrative embodiments, for additional optimization.

AI classification

AI hardware1.00
Natural language0.97
Knowledge representation0.05
Machine learning0.01
Planning0.00
Evolutionary computation0.00
Speech0.00
Vision0.00

Ownership

INTERNATIONAL BUSINESS MACHINES CORPORATION

assignment · 198870693

Assignors

EICHENBERGER, ALEXANDRE E., O'BRIEN, JOHN KEVIN PATRICK, O'BRIEN, KATHRYN M., VASILACHE, NICOLAS T.

On an employer assignment, the assignors are typically the inventors.

From the same owner

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