The need for compilers to generate highly vectorized code is at an all-time high with the increasing vectorization capabilities of modern processors. To this end, the information that compilers have at their disposal, either through code analysis or via user annotations, is instrumental for auto-vectorization, and hence for the overall performance. However, the information that is available to compilers at compile time and its accuracy varies greatly, as does the resulting performance of vectorizing compilers. Benchmarks like the Test Suite for Vectorizing Compilers (TSVC) have been developed to evaluate the vectorization capability of such compilers. The overarching approach of TSVC and similar benchmarks is to evaluate the compilers under...
International audienceReal-time systems have become ubiquitous, and many play an important role in o...
Recent hardware trends with GPUs and the increasing vector lengths of SSE-like ISA extensions for mu...
Compiler optimization passes employ cost models to determine if a code transformation will yield per...
The need for compilers to generate highly vectorized code is at an all-time high with the increasing...
Vectorization support in hardware continues to expand and grow as well we still continue on supersca...
Leveraging the SIMD capability of modern CPU architectures is mandatory to take full advantage of th...
So-called SIMD instructions, which trigger operations that process in each clock cycle a data tuple,...
Abstract. We compare the capabilities of several commercially available, vectorizing Fortran compile...
International audienceHeterogeneity is a confirmed trend of computing systems. Bytecode formats and ...
Vectorization support in hardware continues to expand and grow as we still continue on superscalar a...
Compiler optimization passes employ cost models to determine if a code transformation will yield per...
Newer architectures continue to expand vector sizes and increase the different number of vec-tor ins...
Abstract—SIMD vectors are widely adopted in modern general purpose processors as they can boost perf...
Automatic vectorization is critical to enhancing performance of compute-intensive programs on modern...
International audienceReal-time systems have become ubiquitous, and many play an important role in o...
Recent hardware trends with GPUs and the increasing vector lengths of SSE-like ISA extensions for mu...
Compiler optimization passes employ cost models to determine if a code transformation will yield per...
The need for compilers to generate highly vectorized code is at an all-time high with the increasing...
Vectorization support in hardware continues to expand and grow as well we still continue on supersca...
Leveraging the SIMD capability of modern CPU architectures is mandatory to take full advantage of th...
So-called SIMD instructions, which trigger operations that process in each clock cycle a data tuple,...
Abstract. We compare the capabilities of several commercially available, vectorizing Fortran compile...
International audienceHeterogeneity is a confirmed trend of computing systems. Bytecode formats and ...
Vectorization support in hardware continues to expand and grow as we still continue on superscalar a...
Compiler optimization passes employ cost models to determine if a code transformation will yield per...
Newer architectures continue to expand vector sizes and increase the different number of vec-tor ins...
Abstract—SIMD vectors are widely adopted in modern general purpose processors as they can boost perf...
Automatic vectorization is critical to enhancing performance of compute-intensive programs on modern...
International audienceReal-time systems have become ubiquitous, and many play an important role in o...
Recent hardware trends with GPUs and the increasing vector lengths of SSE-like ISA extensions for mu...
Compiler optimization passes employ cost models to determine if a code transformation will yield per...