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APOLLO released - runtime speculative polyhedral loop optimizer

We are glad to announce the first release of APOLLO, the runtime speculative polyhedral loop optimizer and parallelizer. APOLLO is based on several innovative strategies, making polyhedral loop analyses and transformations applicable to loops that can not be handled using compile-time optimizers, e.g. while loops, with memory references through pointers or indirections, etc.

While the target loops are running, APOLLO automatically detects phases that are polyhedral-compliant (i.e. linear), or quasi-compliant (i.e. nonlinear) but modeled using “tubes”, and then applies speculatively polyhedral code transformations that extract parallelism and optimize data locality. The applied transformations are selected thanks to a runtime usage of the polyhedral compiler Pluto. The optimized transformed codes are generated on-the-fly by using building blocks called “code bones”, and by invoking the polyhedral code generator CLooG and the LLVM JIT compiler.

APOLLO is very easy to use. It is made of a static compiler based on Clang-LLVM to prepare the code, and a runtime system orchestrating the program execution. It has been released under the BSD 3-Clause Open Source License.

The installation package and more details with examples can be found on APOLLO’s website: http://apollo.gforge.inria.fr

We look forward to your feedbacks!

The APOLLO crew: Juan Manuel Martinez Caamano, Aravind Sukumaran-Rajam, Artiom Baloian, Willy Wolff, Philippe Clauss

Philippe Clauss