This paper presents a unified approach for generalized induction variable recognition and substitution, pointer analysis, analysis of conditionally updated variables, value range analysis, array region analysis, and nonlinear dependence testing. The analysis techniques share a well-defined uniform approach based on the chains of recurrences algebra. The uniform algebraic approach provides a powerful unified framework for developing analysis algorithms for restructuring compilers. The paper introduces a new set of analysis algorithms that accurately handle conditional control flow, pointer arithmetic, and nonlinear symbolic expressions in loops, which are known to be problematic for conventional restructuring compilers
Most current data dependence tests cannot handle loop bounds or array subscripts that are symbolic, ...
Abstract. This paper presents the design of an induction variable an-alyzer suitable for the analysi...
Memory-related anti- and output dependences are false dependences because they do not represent the ...
To effectively translate real programs written in standard, sequential languages into parallel compu...
Code restructuring compilers rely heavily on program analysis tech-niques to automatically detect da...
Induction variable detection is usually closely tied to the strength reduction optimization. This pa...
Dependence analysis is an indispensable tool in the automatic vectorization and parallelization of s...
Compiling for efficient execution on advanced computer architectures requires extensive program anal...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/16...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/19...
Induction variable analysis is an important part of the symbolic analysis in parallelizing compilers...
Modern compilers perform wholesale restructuring of programs to improve their efficiency. Dependence...
Traditional schemes for abstract interpretation-based global analysis of logic programs generally f...
This paper presents the design of an induction variable analyzer suitable for the analysis of typed,...
Symbolic analysis is an enabling technique that improves the effectiveness of compiler optimizations...
Most current data dependence tests cannot handle loop bounds or array subscripts that are symbolic, ...
Abstract. This paper presents the design of an induction variable an-alyzer suitable for the analysi...
Memory-related anti- and output dependences are false dependences because they do not represent the ...
To effectively translate real programs written in standard, sequential languages into parallel compu...
Code restructuring compilers rely heavily on program analysis tech-niques to automatically detect da...
Induction variable detection is usually closely tied to the strength reduction optimization. This pa...
Dependence analysis is an indispensable tool in the automatic vectorization and parallelization of s...
Compiling for efficient execution on advanced computer architectures requires extensive program anal...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/16...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/19...
Induction variable analysis is an important part of the symbolic analysis in parallelizing compilers...
Modern compilers perform wholesale restructuring of programs to improve their efficiency. Dependence...
Traditional schemes for abstract interpretation-based global analysis of logic programs generally f...
This paper presents the design of an induction variable analyzer suitable for the analysis of typed,...
Symbolic analysis is an enabling technique that improves the effectiveness of compiler optimizations...
Most current data dependence tests cannot handle loop bounds or array subscripts that are symbolic, ...
Abstract. This paper presents the design of an induction variable an-alyzer suitable for the analysi...
Memory-related anti- and output dependences are false dependences because they do not represent the ...