Sequential Performance: Raising Awareness of the Gory Details

• Published in: Procedia Computer Science
• Main Authors: Rohou, Erven, Guyon, David
• Other Authors: Amdahl's Law is Forever (ALF), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-ARCHITECTURE (IRISA-D3), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2015
• Subjects: [INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]; Iceland
• Online Access: https://hal.inria.fr/hal-01162336; https://hal.inria.fr/hal-01162336/document; https://hal.inria.fr/hal-01162336/file/ICCS2015-final.pdf; https://doi.org/10.1016/j.procs.2015.05.347

International audience The advent of multicore and manycore processors, including GPUs, in the customer market encouraged developers to focus on extraction of parallelism. While it is certainly true that parallelism can deliver performance boosts, parallelization is also a very complex and error-prone task, and any applications are still dominated by sequential sections. Micro-architectures have become extremely complex, and they usually do a very good job at executing fast a given sequence of instructions. When they occasionally fail, however, the penalty is severe. Pathological behaviors often have their roots in very low-level details of the micro-architecture, hardly available to the programmer. We argue that the impact of these low-level features on performance has been overlooked, often relegated to experts. We show that a few metrics can be easily defined to help assess the overall performance of an application, and quickly diagnose a problem. Finally, we illustrate our claim with a simple prototype, along with use cases.