Guillaume Iooss

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Tiling is a crucial program transformation with many benefits: it improves locality, exposes parallelism, allows for adjusting the ops-to-bytes balance of codes, and can be applied at multiple levels. Allowing tile sizes to be symbolic parameters at compile time has many benefits, including efficient autotuning, and run-time adaptability to system(More)
We present a formulation, solution method, and program acceleration techniques for two dynamic control scenarios, both with the common goal of optimizing resource allocations. These approaches allocate resources in a non-myopic way, accounting for long-term impacts of current control decisions via nominal belief-state optimization (NBO). In both scenarios,(More)
DETECTION OF LINEAR ALGEBRA OPERATIONS IN POLYHEDRAL PROGRAMS Writing a code which uses an architecture at its full capability has become an increasingly difficult problem over the last years. For some key operations, a dedicated accelerator or a finely tuned implementation exists and delivers the best performance. Thus, when compiling a code, identifying(More)
As computing moves to exascale, it will be dominated by energy-efficiency. We propose a new GPU-like accelerator called the Stencil Processing Unit (SPU), for implementing dense stencil computations in an energy-efficient manner. We address all the levels of the programming stack, from architecture, programming API, runtime system and compilation. First, a(More)
Polyhedral compilers perform optimizations such as tiling and parallelization; when doing both, they usually generate code that executes “barrier-synchronized wavefronts” of tiles. We present a system to express and generate code for hybrid schedules, where some constraints are automatically satisfied through the structure of the code, and the remainder are(More)
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