Add to ORKGAlthough Single Instruction Multiple Data (SIMD) units are available in general purpose processors already since the 1990s, state-of-the-art compilers are often still not capable to fully exploit them, i.e., they may miss to achieve the best possible performance. We present a new hardware-aware and adaptive loop tiling approach that is based on polyhedral transformations and explicitly dedicated to improve on auto-vectorization
High-level synthesis (HLS) tools are now capable of generating high-quality RTL codes for a number o...
To this day, polyhedral optimizing compilers use either extremely rigid (but accurate) cost models, ...
International audienceIn many cases, applications are not optimized for the hardware on which they r...
Although Single Instruction Multiple Data (SIMD) units are available in general purpose processors a...
Modern compilers offer more and more capabilities to automatically parallelize code-regions if these...
International audienceOptimizing compilers apply numerous inter- dependent optimizations, leading to...
The Single Instruction Multiple Data (SIMD) paradigm promises speedup at relatively low silicon area...
In the last years, there has been much effort in commercial compilers (icc, gcc) to exploit efficien...
The polyhedral model is known to be a powerful framework to reason about high level loop transformat...
Abstract. SIMD hardware accelerators offer an alternative to manycores when energy consumption and p...
Data locality and parallelism are critical optimization objectives for performance on modern multi-c...
Abstract mathematical representations such as integer polyhedra have shown to be useful to precise...
The Cerebras CS-1 is a computing system based on a wafer-scale processor having nearly 400,000 compu...
International audienceIn many cases, applications are not optimized for the hardware on which they r...
Many advances in automatic parallelization and optimization have been achieved through the polyhedra...
High-level synthesis (HLS) tools are now capable of generating high-quality RTL codes for a number o...
To this day, polyhedral optimizing compilers use either extremely rigid (but accurate) cost models, ...
International audienceIn many cases, applications are not optimized for the hardware on which they r...
Although Single Instruction Multiple Data (SIMD) units are available in general purpose processors a...
Modern compilers offer more and more capabilities to automatically parallelize code-regions if these...
International audienceOptimizing compilers apply numerous inter- dependent optimizations, leading to...
The Single Instruction Multiple Data (SIMD) paradigm promises speedup at relatively low silicon area...
In the last years, there has been much effort in commercial compilers (icc, gcc) to exploit efficien...
The polyhedral model is known to be a powerful framework to reason about high level loop transformat...
Abstract. SIMD hardware accelerators offer an alternative to manycores when energy consumption and p...
Data locality and parallelism are critical optimization objectives for performance on modern multi-c...
Abstract mathematical representations such as integer polyhedra have shown to be useful to precise...
The Cerebras CS-1 is a computing system based on a wafer-scale processor having nearly 400,000 compu...
International audienceIn many cases, applications are not optimized for the hardware on which they r...
Many advances in automatic parallelization and optimization have been achieved through the polyhedra...
High-level synthesis (HLS) tools are now capable of generating high-quality RTL codes for a number o...
To this day, polyhedral optimizing compilers use either extremely rigid (but accurate) cost models, ...
International audienceIn many cases, applications are not optimized for the hardware on which they r...