AbstractUbiquitous multicore architectures require that many levels of parallelism have to be found in codes. Dependence analysis is the main approach in compilers for the detection of parallelism. It enables vectorisation and automatic parallelisation, among many other optimising transformations, and is therefore of crucial importance for optimising compilers.This paper presents new open source software, FADAlib, performing an instance-wise dataflow analysis for scalar and array references. The software is a C++ implementation of the Fuzzy Array Dataflow Analysis (FADA) method. This method can be applied on codes with irregular control such as while-loops, if-then-else or non-regular array accesses, and computes exact instance-wise dataflo...
Standard array data dependence testing algorithms give information about the aliasing of array ref...
International audienceStarting from a generalization of induction variables,we present a dependence ...
Thesis (Ph. D.)--University of Rochester. Dept. of Computer Science, 2012.Speculative parallelizatio...
International audienceUbiquitous multicore architectures require that many levels of parallelism hav...
Ubiquitous multicore architectures require that many levels of parallelism have to be found in codes...
Exact array dataflow analysis can be achieved in the general case if the only control structures are...
Array dataflow dependence analysis is paramount for automatic parallelization. The description of de...
This paper addresses the data-flow analysis of access to arrays in recursive imperative programs. Wh...
Automatic parallelization of real FORTRAN programs does not live up to users expectations yet, ...
Parallelizing compilers are increasingly relying on accurate data dependence information to exploit ...
International audienceWith the widespread of multicore systems, automatic parallelization becomes mo...
We developed a dataflow framework which provides a basis for rigorously defining strategies to make ...
International audienceRecently, with the wide usage of multicore architectures, automatic paralleliz...
This paper presents a new analysis for parallelizing compilers called predicated array data-flow ana...
Writing parallel code is traditionally considered a difficult task, even when it is tackled from the...
Standard array data dependence testing algorithms give information about the aliasing of array ref...
International audienceStarting from a generalization of induction variables,we present a dependence ...
Thesis (Ph. D.)--University of Rochester. Dept. of Computer Science, 2012.Speculative parallelizatio...
International audienceUbiquitous multicore architectures require that many levels of parallelism hav...
Ubiquitous multicore architectures require that many levels of parallelism have to be found in codes...
Exact array dataflow analysis can be achieved in the general case if the only control structures are...
Array dataflow dependence analysis is paramount for automatic parallelization. The description of de...
This paper addresses the data-flow analysis of access to arrays in recursive imperative programs. Wh...
Automatic parallelization of real FORTRAN programs does not live up to users expectations yet, ...
Parallelizing compilers are increasingly relying on accurate data dependence information to exploit ...
International audienceWith the widespread of multicore systems, automatic parallelization becomes mo...
We developed a dataflow framework which provides a basis for rigorously defining strategies to make ...
International audienceRecently, with the wide usage of multicore architectures, automatic paralleliz...
This paper presents a new analysis for parallelizing compilers called predicated array data-flow ana...
Writing parallel code is traditionally considered a difficult task, even when it is tackled from the...
Standard array data dependence testing algorithms give information about the aliasing of array ref...
International audienceStarting from a generalization of induction variables,we present a dependence ...
Thesis (Ph. D.)--University of Rochester. Dept. of Computer Science, 2012.Speculative parallelizatio...