MPI Support on the Grid

Grids as infrastructures offer access to computing, storage and other resources in a transparent way. The user does not have to be aware where and how the job is being executed. Grid clusters in particular are an interesting target for running computation-intensive calculations. Running MPI-parallel applications on such clusters is a logical approach that is of interest to both computer scientists and to engineers. This paper gives an overview of the issues connected to running MPI applications on a heterogenous Grid consisting of different clusters located at different sites within the Int.EU.Grid project. The role of a workload management system (WMS) for such a scenario, as well as important modifications that need to be made to a WMS oriented towards sequential batch jobs for better support of MPI applications and tools are discussed. In order to facilitate the adoption of MPI-parallel applications on heterogeneous Grids, the application developer should be made aware of performance problems, as well as MPI-standard issues within its code. Therefore tools for these issues are also supported within Int.EU.Grid. Also, the special case of running MPI applications on different clusters simultaneously as a more Grid-oriented computational approach is described

Comparison and tuning of MPI implementations in a grid context

Today, clusters are often interconnected by long distance networks within grids to offer a huge number of available ressources to a range of users. MPI, the standard communication library used to write parallel applications, has been implemented for clusters. Two main features of grids: long distance networks and technological heterogeneity, raise the question of MPI efficiency in grids. This report presents an evaluation of four recent MPI implementations (MPICH2, MPICH-Madeleine, OpenMPI and GridMPI) in the french research grid: Grid'5000. The comparison is based on the execution of pingpong, NAS Parallel Benchmarks and a real application in geophysics. We show that this implementations present performance differences. Executing MPI applications on the grid can be beneficial if the parameters are well tuned. The paper details the tuning required on each implementation to get the best performances

Interaction between MPI and TCP in grids.

As MPI applications are more and more resource consuming, they need to be executed on grids. The communications on the WAN interconnecting clusters mostly use TCP which suffers from WAN features: high latency, sharing between users, bandwidth smaller than the aggregate bandwidth of the nodes. In this report, we first study the interaction between MPI and TCP on grids. We show why the nature of MPI traffic raises problems while using TCP on WAN links. TCP's loss detection and congestion control mechanism can both slow down the application. 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 slowstart phase after an idle time. Finally, we test our layer on Grid'5000, the French research grid, using MPICH2. The results on the NPB (NAS Parallel Benchmarks) validate our architecture that reduces the number of idle timeout and the number of long-distance retransmissions for certain benchmarks, namely BT, SP and LU benchmarks. Using MPI5000, these applications can decrease their execution time by 35%, 28%, and, 15% respectively

MPICH-G2: A Grid-Enabled Implementation of the Message Passing Interface

Application development for distributed computing "Grids" can benefit from tools that variously hide or enable application-level management of critical aspects of the heterogeneous environment. As part of an investigation of these issues, we have developed MPICH-G2, a Grid-enabled implementation of the Message Passing Interface (MPI) that allows a user to run MPI programs across multiple computers, at the same or different sites, using the same commands that would be used on a parallel computer. This library extends the Argonne MPICH implementation of MPI to use services provided by the Globus Toolkit for authentication, authorization, resource allocation, executable staging, and I/O, as well as for process creation, monitoring, and control. Various performance-critical operations, including startup and collective operations, are configured to exploit network topology information. The library also exploits MPI constructs for performance management; for example, the MPI communicator construct is used for application-level discovery of, and adaptation to, both network topology and network quality-of-service mechanisms. We describe the MPICH-G2 design and implementation, present performance results, and review application experiences, including record-setting distributed simulations.Comment: 20 pages, 8 figure

Comparison and tuning of MPI implementation in a grid context

International audienceToday, clusters are often interconnected by long distance networks to compose grids and to provide users with a huge number of available ressources. To write parallel applica- tions, 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: Grid'5000. The comparison is based on the execution of pingpong and NAS Parallel Bench- marks. 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 appli- cations 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

Support to MPI Applications on the Grid

The current middleware stacks provide varying support for the Message Passing Interface (MPI) programming paradigm. Users face a complex and heterogeneous environment where too many low level details have to be specified to execute even the simplest parallel jobs. MPI-Start is a tool that provides an interoperable MPI execution framework across the different middleware implementations to abstract the user interfaces from the underlying middleware and to allow users to execute parallel applications in a uniform way, thus bridging the gap between HPC and HTC. In this work we present the latest developments in MPI-Start and how it can be integrated in the different middleware stacks available as part of EMI, providing a unified user experience for MPI jobs

Etude d'implémentations MPI dans une grille de calcul

National audienceThis paper presents an evaluation on the GRID'5000 platform of four MPI implementation: MPICH2, MPICH-Madeleine, OpenMPI et GridMPI. The comparison is based on a simple pingpong and the NAS parallel benchmarks. We show that GridMPI has the best results with regards to performances on the Grid if the implementation is well tuned. This paper details which parameters should be tuned.De nos jours, les grappes de PC ou clusters sont souvent interconnectés par des réseaux longue-distance de manière à former une grille afin d'offrir à un grand nombre d'utilisateurs un nombre plus conséquent de ressources. MPI, la bibliothèque de communication la plus utilisée pour les applications parallèles, a été efficacement implémentée dans un contexte de clusters. Deux caractéristiques des grilles, les réseaux longue-distance et l'hétérogénéité des processeurs et des réseaux, posent la question de l'efficacité de MPI sur les grilles. Cet article présente une évaluation sur la grille de recherche française GRID'5000, de 4 implémentations récentes de MPI : MPICH2, MPICH-Madeleine, OpenMPI et GridMPI. La comparaison est basée sur un pingpong, les NAS Parallel Benchmarks. Nous mettons en évidence les différences de performance obtenues avec les 4 implé- mentations. GridMPI montre les meilleures performances. L'exécution d'applications MPI sur la grille peut être bénéfique à condition de régler finement certains paramètres des implémentations. Cet article détaille les para- mètres mis en jeu et leurs réglages

Large-scale Reservoir Simulations on IBM Blue Gene/Q

This paper presents our work on simulation of large-scale reservoir models on IBM Blue Gene/Q and studying the scalability of our parallel reservoir simulators. An in-house black oil simulator has been implemented. It uses MPI for communication and is capable of simulating reservoir models with hundreds of millions of grid cells. Benchmarks show that our parallel simulator are thousands of times faster than sequential simulators that designed for workstations and personal computers, and the simulator has excellent scalability