Jean-Christophe Mignot

Comparison and tuning of MPI implementations in a grid context

Today, clusters are often interconnected by long distance networks to compose grids and to provide users with a huge number of available resources. To write parallel applications, developers are generally using the standard communication library MPI, which has been optimized for clusters. However, two main features of grids-long distance networks and technological heterogeneity-raise the question of MPI efficiency in grids. This paper presents an evaluation and tuning of four recent MPI implementations (MPICH2, MPICH-Madeleine, OpenMPI and YAMPII) in a research grid: Gridpsila5000. The comparison is based on the execution of pingpong and NAS parallel benchmarks. We show that these implementations present several performance differences. We show that YAMPII performs better results than the others. But we argue that executing MPI applications on a grid can be beneficial if some specific parameters are well tuned. The paper details, for each implementation, the tuning leading the best performances.

Providing Green Services in HPC Data Centers: A Methodology Based on Energy Estimation

A supercomputer is an infrastructure built from an interconnection of computers capable of performing tasks in parallel in order to achieve very high performance. They are used in order to run scientific applications in various fields like the prediction of severe weather phenomena and seismic waves. To meet new scientific challenges, the HPC community has set a new performance objective for the end of the decade: Exascale. To achieve such performance (1018 FLoat Operations Per Second), an exascale supercomputer will gather several millions of CPU cores running up to a billion trends and will consume several megawatts. The energy consumption issue at the exascale becomes even more worrying when we know that we already reach energy consumptions higher than 17 MW at the petascale while the DARPA set to 20 MW the threshold for exascale supercomputers. Hence, these systems that will be 30 times more performant than the current systems have to achieve an energy efficiency of 50 gigaFLOPS per watt while the current ones achieve between 2 and 3 gigaFLOPS per watt. As a consequence, reducing the energy consumption of high-performance computing infrastructures is a major challenge for the next years in order to be able to move to the exascale era.

Splitting TCP for MPI Applications Executed on Grids

In this paper, we first study the interaction between MPI applications and TCP on grids. Then, we propose MPI5000, a transparent applicative layer between MPI and TCP, using proxies to improve the execution of MPI applications on a grid. Proxies aim at splitting TCP connections in order to detect losses faster and avoid to return in a slow-start phase after an idle time. Finally, we evaluate our layer executing the NAS Parallel Benchmarks on Grid5000, the French research grid, using MPICH2. The results show that our architecture reduces the number of idle timeout and of long-distance retransmissions for BT, SP and LU benchmarks. Using MPI5000, these applications can decrease their execution time by 35%, 28%, and, 15% respectively. A comparison with MPICH-G2 performances shows that our layer can even outperform a grid enabled MPI implementation.