Paper Info
Title
Performance and energy effects on task-based parallelized applications - User-directed versus manual vectorization.
Abstract
Heterogeneity, parallelization and vectorization are key techniques to improve the performance and energy efficiency of modern computing systems. However, programming and maintaining code for these architectures poses a huge challenge due to the ever-increasing architecture complexity. Task-based environments hide most of this complexity, improving scalability and usage of the available resources. In these environments, while there has been a lot of effort to ease parallelization and improve the usage of heterogeneous resources, vectorization has been considered a secondary objective. Furthermore, there has been a swift and unstoppable burst of vector architectures at all market segments, from embedded to HPC. Vectorization can no longer be ignored, but manual vectorization is tedious, error-prone and not practical for the average programmer. This work evaluates the feasibility of user-directed vectorization in task-based applications. Our evaluation is based on the OmpSs programming model, extended to support user-directed vectorization for different SIMD architectures (i.e., SSE, AVX2, AVX512). Results show that user-directed codes achieve manually optimized code performance and energy efficiency with minimal code modifications, favoring portability across different SIMD architectures.
Year
Venue
Field
2018
The Journal of Supercomputing
Programmer,Programming paradigm,Efficient energy use,Computer science,Parallel computing,SIMD,Vectorization (mathematics),Data parallelism,Software portability,Scalability
DocType
Volume
Issue
Journal
74
6
Citations 
PageRank 
References 
0
0.34
5
Authors
8
Name
Order
Citations
PageRank
Helena Caminal192.27
Diego Caballero2202.51
Juan Manuel Cebrian32410.19
Roger Ferrer412110.31
Marc Casas511123.61
Miquel Moretó620525.49
Xavier Martorell71470125.40
Mateo Valero84520355.94