Section: New Results

Power Efficiency and Computing Performance

Participants : Emilio Francesquini [UNICAMP, Campinas, Brazil] , Edson Luiz Padoin [PhD: UFRGS and UNIJUI, Brazil] , Marcio Castro [UFSC, Florianapolis, Brazil] , Pedro Penna [PUC Minas, Belo Horizonte, Brazil] , Henrique Cota de Freitas [PUC Minas, Belo Horizonte, Brazil] , Fabrice Dupros [BRGM, Orléans, France] , Philippe Navaux [UFRGS, Porto Alegre, Brazil] , Jean François Méhaut.

Until the last decade, performance of HPC architectures has been almost exclusively quantified by their processing power. However, energy efficiency is being recently considered as important as raw performance and has become a critical aspect to the development of scalable systems. These strict energy constraints guided the development of a new class of so-called light-weight manycore processors. This study evaluates the computing and energy performance of two well-known irregular NP-hard problems – the Traveling-Salesman Problem (TSP) and K-Means clustering – and a numerical seismic wave propagation simulation kernel – Ondes3D – on multicore, NUMA, and manycore platforms. First, we concentrate on the nontrivial task of adapting these applications to a manycore, specifically the Kalray/MPPA-256 manycore processor. Then, we analyze their performance and energy consumption on those different machines. Our results show that applications able to fully use the resources of a manycore can have better performance and may consume from 3.8 × to 13 × less energy when compared to low-power and general-purpose multicore processors, respectively.

This work is the fruit of collaborations with Brazil and several universities (UFRGS, UFSC, UNICAMP, PUC Minas, USP). This work has been published in the journal of parallel and distributed computing [6] and in the journal of IET Computers and Digtal Techniques [7] . This work was also part of several international projects (LICIA , CNPq/Inria HOSCAR project, Exase ).

Emilio Francesquini and Marcio Castro are also former PhD students of University Grenoble Alpes (UGA) and the LIG Laboratory.