Large Scale In Silico Screening on Grid Infrastructures

Large-scale grid infrastructures for in silico drug discovery open opportunities of particular interest to neglected and emerging diseases. In 2005 and 2006, we have been able to deploy large scale in silico docking within the framework of the WISDOM initiative against Malaria and Avian Flu requiring about 105 years of CPU on the EGEE, Auvergrid and TWGrid infrastructures. These achievements demonstrated the relevance of large-scale grid infrastructures for the virtual screening by molecular docking. This also allowed evaluating the performances of the grid infrastructures and to identify specific issues raised by large-scale deployment.Comment: 14 pages, 2 figures, 2 tables, The Third International Life Science Grid Workshop, LSGrid 2006, Yokohama, Japan, 13-14 october 2006, to appear in the proceeding

Virtual Screening on Large Scale Grids

PCSV, article in press in Parallel ComputingLarge scale grids for in silico drug discovery open opportunities of particular interest to neglected and emerging diseases. In 2005 and 2006, we have been able to deploy large scale virtual docking within the framework of the WISDOM initiative against malaria and avian influenza requiring about 100 years of CPU on the EGEE, Auvergrid and TWGrid infrastructures. These achievements demonstrated the relevance of large scale grids for the virtual screening by molecular docking. This also allowed evaluating the performances of the grid infrastructures and to identify specific issues raised by large scale deployment

Methodology for malleable applications on distributed memory systems

A la portada logo BSC(English) The dominant programming approach for scientific and industrial computing on clusters is MPI+X. While there are a variety of approaches within the node, denoted by the ``X'', Message Passing interface (MPI) is the standard for programming multiple nodes with distributed memory. This thesis argues that the OmpSs-2 tasking model can be extended beyond the node to naturally support distributed memory, with three benefits: First, at small to medium scale the tasking model is a simpler and more productive alternative to MPI. It eliminates the need to distribute the data explicitly and convert all dependencies into explicit message passing. It also avoids the complexity of hybrid programming using MPI+X. Second, the ability to offload parts of the computation among the nodes enables the runtime to automatically balance the loads in a full-scale MPI+X program. This approach does not require a cost model, and it is able to transparently balance the computational loads across the whole program, on all its nodes. Third, because the runtime handles all low-level aspects of data distribution and communication, it can change the resource allocation dynamically, in a way that is transparent to the application. This thesis describes the design, development and evaluation of OmpSs-2@Cluster, a programming model and runtime system that extends the OmpSs-2 model to allow a virtually unmodified OmpSs-2 program to run across multiple distributed memory nodes. For well-balanced applications it provides similar performance to MPI+OpenMP on up to 16 nodes, and it improves performance by up to 2x for irregular and unbalanced applications like Cholesky factorization. This work also extended OmpSs-2@Cluster for interoperability with MPI and Barcelona Supercomputing Center (BSC)'s state-of-the-art Dynamic Load Balance (DLB) library in order to dynamically balance MPI+OmpSs-2 applications by transparently offloading tasks among nodes. This approach reduces the execution time of a microscale solid mechanics application by 46% on 64 nodes and on a synthetic benchmark, it is within 10% of perfect load balancing on up to 8 nodes. Finally, the runtime was extended to transparently support malleability for pure OmpSs-2@Cluster programs and interoperate with the Resources Management System (RMS). The only change to the application is to explicitly call an API function to control the addition or removal of nodes. In this regard we additionally provide the runtime with the ability to semi-transparently save and recover part of the application status to perform checkpoint and restart. Such a feature hides the complexity of data redistribution and parallel IO from the user while allowing the program to recover and continue previous executions. Our work is a starting point for future research on fault tolerance. In summary, OmpSs-2@Cluster expands the OmpSs-2 programming model to encompass distributed memory clusters. It allows an existing OmpSs-2 program, with few if any changes, to run across multiple nodes. OmpSs-2@Cluster supports transparent multi-node dynamic load balancing for MPI+OmpSs-2 programs, and enables semi-transparent malleability for OmpSs-2@Cluster programs. The runtime system has a high level of stability and performance, and it opens several avenues for future work.(Español) El modelo de programación dominante para clusters tanto en ciencia como industria es actualmente MPI+X. A pesar de que hay alguna variedad de alternativas para programar dentro de un nodo (indicado por la "X"), el estandar para programar múltiples nodos con memoria distribuida sigue siendo Message Passing Interface (MPI). Esta tesis propone la extensión del modelo de programación basado en tareas OmpSs-2 para su funcionamiento en sistemas de memoria distribuida, destacando 3 beneficios principales: En primer lugar; a pequeña y mediana escala, un modelo basado en tareas es más simple y productivo que MPI y elimina la necesidad de distribuir los datos explícitamente y convertir todas las dependencias en mensajes. Además, evita la complejidad de la programacion híbrida MPI+X. En segundo lugar; la capacidad de enviar partes del cálculo entre los nodos permite a la librería balancear la carga de trabajo en programas MPI+X a gran escala. Este enfoque no necesita un modelo de coste y permite equilibrar cargas transversalmente en todo el programa y todos los nodos. En tercer lugar; teniendo en cuenta que es la librería quien maneja todos los aspectos relacionados con distribución y transferencia de datos, es posible la modificación dinámica y transparente de los recursos que utiliza la aplicación. Esta tesis describe el diseño, desarrollo y evaluación de OmpSs-2@Cluster; un modelo de programación y librería que extiende OmpSs-2 permitiendo la ejecución de programas OmpSs-2 existentes en múltiples nodos sin prácticamente necesidad de modificarlos. Para aplicaciones balanceadas, este modelo proporciona un rendimiento similar a MPI+OpenMP hasta 16 nodos y duplica el rendimiento en aplicaciones irregulares o desbalanceadas como la factorización de Cholesky. Este trabajo incluye la extensión de OmpSs-2@Cluster para interactuar con MPI y la librería de balanceo de carga Dynamic Load Balancing (DLB) desarrollada en el Barcelona Supercomputing Center (BSC). De este modo es posible equilibrar aplicaciones MPI+OmpSs-2 mediante la transferencia transparente de tareas entre nodos. Este enfoque reduce el tiempo de ejecución de una aplicación de mecánica de sólidos a micro-escala en un 46% en 64 nodos; en algunos experimentos hasta 8 nodos se pudo equilibrar perfectamente la carga con una diferencia inferior al 10% del equilibrio perfecto. Finalmente, se implementó otra extensión de la librería para realizar operaciones de maleabilidad en programas OmpSs-2@Cluster e interactuar con el Sistema de Manejo de Recursos (RMS). El único cambio requerido en la aplicación es la llamada explicita a una función de la interfaz que controla la adición o eliminación de nodos. Además, se agregó la funcionalidad de guardar y recuperar parte del estado de la aplicación de forma semitransparente con el objetivo de realizar operaciones de salva-reinicio. Dicha funcionalidad oculta al usuario la complejidad de la redistribución de datos y las operaciones de lectura-escritura en paralelo, mientras permite al programa recuperar y continuar ejecuciones previas. Este es un punto de partida para futuras investigaciones en tolerancia a fallos. En resumen, OmpSs-2@Cluster amplía el modelo de programación de OmpSs-2 para abarcar sistemas de memoria distribuida. El modelo permite la ejecución de programas OmpSs-2 en múltiples nodos prácticamente sin necesidad de modificarlos. OmpSs-2@Cluster permite además el balanceo dinámico de carga en aplicaciones híbridas MPI+OmpSs-2 ejecutadas en varios nodos y es capaz de realizar maleabilidad semi-transparente en programas OmpSs-2@Cluster puros. La librería tiene un niveles de rendimiento y estabilidad altos y abre varios caminos para trabajos futuro.Arquitectura de computador

Holistic Characterization of Parallel Programming Models in a Distributed Memory Environment

The popularity of cluster computing has increased focus on usability, especially in the area of programmability. Languages and libraries that require explicit message passing have been the standard. New languages, designed for cluster computing, are coming to the forefront as a way to simplify parallel programming. Titanium and Fortress are examples of this new class of programming paradigms. This work holistically characterizes these languages and contrasts them with the standard model of parallel programming, and presents benchmark results of small computational kernels written in these languages and models

Déploiement d'applications parallèles sur une architecture distribuée matériellement reconfigurable

Among the architectural targets that could be buid a system on chip (SoC), dynamically reconfigurable architectures (DRA) offer interesting potential for flexibility and dynamicity . However this potential is still difficult to use in massively parallel on chip applications. In our work we identified and analyzed the solutions currently proposed to use DRA and found their limitations including: the use of a particular technology or proprietary architecture, the lack of parallel applications consideration, the difficult scalability, the lack of a common language adopted by the community to use the flexibility of DRA ...In our work we propose a solution for deployment on an DRA of a parallel application using standard SoC design flows. This solution is called MATIP ( textit {MPI Application Platform Task Integreation}) and uses primitives of MPI standard Version 2 to make communications and to reconfigure the MP-RSoC architecture . MATIP is a Platform-Based Design (PBD) level solution.The MATIP platform is modeled in three layers: interconnection, communication and application. Each layer is designed to satisfies the requirements of heterogeneity and dynamicity of parallel applications. For this, MATIP uses a distributed memory architecture and utilizes the message passing parallel programming paradigm to enhance scalability of the platform.MATIP frees the designer of all the details related to interconnection, communication between tasks and management of dynamic reconfiguration of the hardware target. A demonstrator of MATIP was performed on Xilinx FPGA through the implementation of an application consisting of two static and two dynamic hardware tasks. MATIP offers a bandwidth of 2.4 Gb / s and latency of 3.43 microseconds for the transfer of a byte. Compared to other MPI platforms (TMD-MPI, SOC-MPI MPI HAL), MATIP is in the state of the art.Parmi les cibles architecturales susceptibles d'être utilisées pour réaliser un système de traitement sur puce (SoC), les architectures reconfigurables dynamiquement (ARD) offrent un potentiel de flexibilité et de dynamicité intéressant. Cependant ce potentiel est encore difficile à exploiter pour réaliser des applications massivement parallèles sur puce. Dans nos travaux nous avons recensé et analysé les solutions actuellement proposées pour utiliser les ARD et nous avons constaté leurs limites parmi lesquelles : l'utilisation d'une technologie particulière ou d'architecture propriétaire, l'absence de prise en compte des applications parallèles, le passage à l'échelle difficile, l'absence de langage adopté par la communauté pour l'utilisation de la flexibilité des ARD, ...Pour déployer une application sur une ARD il est nécessaire de considérer l'hétérogénéité et la dynamicité de l'architecture matérielle d'une part et la parallélisation des traitements d'autre part. L'hétérogénéité permet d'avoir une architecture de traitement adaptée aux besoins fonctionnels de l'application. La dynamicité permet de prendre en compte la dépendance des applications au contexte et de la nature des données. Finalement, une application est naturellement parallèle.Dans nos travaux nous proposons une solution pour le déploiement sur une ARD d'une application parallèle en utilisant les flots de conception standard des SoC. Cette solution est appelée MATIP (MPI Application Task Integreation Platform) et utilise des primitives du standard MPI version 2 pour effectuer les communications et reconfigurer l'architecture de traitement. MATIP est une solution de déploiement au niveau de la conception basée plate-forme (PBD).La plateforme MATIP est modélisée en trois couches : interconnexion, communication et application. Nous avons conçu chaque couche pour que l'ensemble satisfasse les besoins en hétérogénéité et dynamicité des applications parallèles . Pour cela MATIP utilise une architecture à mémoire distribuée et exploite le paradigme de programmation parallèle par passage de message qui favorise le passage à l'échelle de la plateforme.MATIP facilite le déploiement d'une application parallèle sur puce à travers un template en langage Vhdl d'intégration de tâches. L'utilisation des primitives de communication se fait en invoquant des procédures Vhdl.MATIP libère le concepteur de tous les détails liés à l'interconnexion, la communication entre les tâches et à la gestion de la reconfiguration dynamique de la cible matérielle. Un démonstrateur de MATIP a été réalisée sur des FPGA Xilinx à travers la mise en oe{}uvre d'une application constituée de deux tâches statiques et deux tâches dynamiques. MATIP offre une bande passante de 2,4 Gb/s et une la latence pour le transfert d'un octet de 3,43 µs ce qui comparée à d'autres plateformes MPI (TMD-MPI, SOC-MPI, MPI HAL) met MATIP à l'état de l'art

Communications à hautes performances portables en environnements hiérarchiques, hétérogènes et dynamiques

Cette thèse a pour cadre les communications dans les machines para llèles dans une optique de calcul haute-performance. Les évolutions du matériel ont rendu nécessaire les adaptations des logiciels destinés à exploiter les machines parallèles. En effet, les architectures de type “grappes” sont maintenant très répandues et l'apparition des grilles de calcul complique encore plus la situation car l'obtention des hautes performances passe par une exploitation des différents réseaux rapides disponibles et une prise en compte de la hiérarchie intrinsèque des configurations considérées. Au niveau applicatif, de nouvelles exigences émergent comme la dynamicité. Or, ces aspects sont trop souvent partiellement traités, en particulier dans les implémentations du standard de programmation par passage de messages MPI. Les solutions existantes se concentrent sur la hiérarchie et l'hétérogénéité ou la dynamicité, exceptionnellement les deux. En ce qui concerne les premiers aspects, des simplifications conduisent à une exploitation suboptimale du matériel potentiellement disponible. Nous avons analysé des implémentations existantes de MPI et avons proposé une architecture répondant aux besoins formulés. Cette architecture repose sur une forte interaction entre communications et processus légers et son coeur est constitué par un moteur de progression des communications qui permet d'améliorer substantiellement les mécanismes existants. Les deux éléments logiciels fondamentaux sont une bibliothèque de processus légers (Marcel) ainsi qu'une couche générique de communication (Madeleine). L'implémentation de cette architecture a débouché sur le logiciel MPICH-Madeleine, utilisé ou évalué par plusieurs équipes et projets de recherche en France comme à l'étranger. L'évalution des performances (comparaisons avec Madeleine, mesures des opérations point-à-point, noyaux applicatifs) menée avec plusieurs réseaux haut-débit sur des grappes homogènes de machines multi-processeurs et les comparaisons avec MPICH-G2 ou PACX-MPI en environnement hétérogène démontrent que MPICH-Madeleine atteint des résultats de niveau similaire voire supérieur à ceux d'implémentations spécialisées de MPI.This thesis targets communication within parallel computers with an emphasis on highperformance computing. The software exploiting parallel computers had to adapt to their evolutions. Indeed, architectures such as PC clusters are now widespread and the emergence of grids tends to add new levels of complexity since high-performance can be obtained through exploitating the different high-speed networks available as well as taking into account the inherent hierarchy of the configurations. And as far as applications are concerned, new functionalities are also required, such as dynamicity. Those aspects are far too often neglected or partially tackled in existing implementations of the message passing standard, that is, MPI. Current solutions do focus on hierarchy and heterogeneity or on dynamicity, rarely both and regarding the first aspects, some simplifications do not lead to a full exploitation of the underlying hardware. We have analyzed existing MPI implementations and have proposed an architecture that answers the needs we pointed out. This architecture relies on a strong interaction between threads and communication and its core is build above a progression engine that improves existing mechanisms. The two key elements used are a user-level thread library (Marcel) and generic communication library (Madeleine). The implementation of this architecture, MPICH-MAdeleine, is used or evaluated by several research groups, both french and foreign. The performance assessment carried out with several high-speed networks in both homogenous and heterogenous environments shows that MPICHMadeleine's performance level is equal or superior to that of the software it challenges

Dynamic Process Management in an MPI Setting

We propose extensions to the Message-Passing Interface (MPI) Standard that provide for dynamic process management, including spawning of new processes by a running application. Such extensions are needed if more of the runtime environment for parallel programs is to be accessible to MPI programs or to be themselves written using MPI. The extensions proposed here are motivated by real applications and fit cleanly with existing concepts of MPI. No changes to the existing MPI Standard are proposed, thus all present MPI programs will run unchanged. 1 Introduction During 1993 and 1994 a group composed of parallel computer vendors, library writers, and application scientists created a standard message passing library interface specification [1, 2, 6]. This group, which called itself the MPI Forum, chose to propose a standard only for the message-passing library, attempting to unify and subsume the plethora of existing libraries. They deliberately and explicitly did not propose a stan..