An optimized predication execution for SIMD extensions
| Autor: | Barredo Ferreira, Adrián, Cebrián González, Juan Manuel, Moreto Planas, Miquel, Casas Guix, Marc, Valero Cortés, Mateo |
|---|---|
| Přispěvatelé: | Universitat Politècnica de Catalunya. Doctorat en Arquitectura de Computadors, Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Barcelona Supercomputing Center, Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Data level parallelism
Parallel processing (Electronic computers) Power Processament en paral·lel (Ordinadors) Superordinadors -- Consum d'energia Vector Efficiency DLP Informàtica::Arquitectura de computadors::Arquitectures paral·leles [Àrees temàtiques de la UPC] High performance computing -- Energy consumption SIMD |
| Zdroj: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) |
| Popis: | Vector processing is a widely used technique to improve performance and energy efficiency in modern processors. Most of them rely on predication to support divergence control. However, performance and energy consumption in predicated instructions are usually independent on the number of true values in a mask. This means that the efficiency of the system becomes sub-optimal as vector length increases. In this work we propose the Optimized Predication Execution (OPE) technique. OPE delays the execution of sparse masked vector instructions sharing the same PC, extracts their active elements and creates a new dense instruction with a higher mask density. After executing such dense instruction, results are restored to the original sparse instructions. Our approach improves performance by up to 25% and reduces dynamic energy consumption by up to 43% on real applications with predication. This work has been partially supported by the RoMoL ERC Advanced Grant (GA 321253), the European HiPEAC Network of Excellence and the Spanish Government (contract TIN2015-65316-P). A. Barredo has been supported by the Spanish Government under Formación del Personal Investigador fellowship number BES-2017-080635. M. Moretó has been partially supported by the Spanish Ministry of Economy, Industry and Competitiveness under Ramon y Cajal fellowship number RYC-2016-21104. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|