Direct-pNFS: Scalable, transparent, and versatile access to parallel file systems

Grid computations require global access to massive data stores. To meet this need, the GridNFS project aims to provide scalable, high-performance, transparent, and secure wide-area data management as well as a scalable and agile name space. While parallel file systems give high I/O throughput, they are highly specialized, have limited operating system and hardware platform support, and often lack strong security mechanisms. Remote data access tools such as NFS and GridFTP overcome some of these limitations, but fail to provide universal, transparent, and scalable remote data access. As part of GridNFS, this paper introduces Direct-pNFS, which builds on the NFSv4.1 protocol to meet a key challenge in accessing remote parallel file systems: high-performance and scalable data access without sacrificing transparency, security, orportability. Experiments with Direct-pNFS demonstrate I/O throughput that equals or out performs the exported parallel file system across a range of workloads.http://deepblue.lib.umich.edu/bitstream/2027.42/107917/1/citi-tr-07-2.pd

A shared-disk parallel cluster file system

Dissertação apresentada para obtenção do Grau de Doutor em Informática Pela Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaToday, clusters are the de facto cost effective platform both for high performance computing (HPC) as well as IT environments. HPC and IT are quite different environments and differences include, among others, their choices on file systems and storage: HPC favours parallel file systems geared towards maximum I/O bandwidth, but which are not fully POSIX-compliant and were devised to run on top of (fault prone) partitioned storage; conversely, IT data centres favour both external disk arrays (to provide highly available storage) and POSIX compliant file systems, (either general purpose or shared-disk cluster file systems, CFSs). These specialised file systems do perform very well in their target environments provided that applications do not require some lateral features, e.g., no file locking on parallel file systems, and no high performance writes over cluster-wide shared files on CFSs. In brief, we can say that none of the above approaches solves the problem of providing high levels of reliability and performance to both worlds. Our pCFS proposal makes a contribution to change this situation: the rationale is to take advantage on the best of both – the reliability of cluster file systems and the high performance of parallel file systems. We don’t claim to provide the absolute best of each, but we aim at full POSIX compliance, a rich feature set, and levels of reliability and performance good enough for broad usage – e.g., traditional as well as HPC applications, support of clustered DBMS engines that may run over regular files, and video streaming. pCFS’ main ideas include: · Cooperative caching, a technique that has been used in file systems for distributed disks but, as far as we know, was never used either in SAN based cluster file systems or in parallel file systems. As a result, pCFS may use all infrastructures (LAN and SAN) to move data. · Fine-grain locking, whereby processes running across distinct nodes may define nonoverlapping byte-range regions in a file (instead of the whole file) and access them in parallel, reading and writing over those regions at the infrastructure’s full speed (provided that no major metadata changes are required). A prototype was built on top of GFS (a Red Hat shared disk CFS): GFS’ kernel code was slightly modified, and two kernel modules and a user-level daemon were added. In the prototype, fine grain locking is fully implemented and a cluster-wide coherent cache is maintained through data (page fragments) movement over the LAN. Our benchmarks for non-overlapping writers over a single file shared among processes running on different nodes show that pCFS’ bandwidth is 2 times greater than NFS’ while being comparable to that of the Parallel Virtual File System (PVFS), both requiring about 10 times more CPU. And pCFS’ bandwidth also surpasses GFS’ (600 times for small record sizes, e.g., 4 KB, decreasing down to 2 times for large record sizes, e.g., 4 MB), at about the same CPU usage.Lusitania, Companhia de Seguros S.A, Programa IBM Shared University Research (SUR

A multi-tier cached I/O architecture for massively parallel supercomputers

Recent advances in storage technologies and high performance interconnects have made possible in the last years to build, more and more potent storage systems that serve thousands of nodes. The majority of storage systems of clusters and supercomputers from Top 500 list are managed by one of three scalable parallel file systems: GPFS, PVFS, and Lustre. Most large-scale scientific parallel applications are written in Message Passing Interface (MPI), which has become the de-facto standard for scalable distributed memory machines. One part of the MPI standard is related to I/O and has among its main goals the portability and efficiency of file system accesses. All of the above mentioned parallel file systems may be accessed also through the MPI-IO interface. The I/O access patterns of scientific parallel applications often consist of accesses to a large number of small, non-contiguous pieces of data. For small file accesses the performance is dominated by the latency of network transfers and disks. Parallel scientific applications lead to interleaved file access patterns with high interprocess spatial locality at the I/O nodes. Additionally, scientific applications exhibit repetitive behaviour when a loop or a function with loops issues I/O requests. When I/O access patterns are repetitive, caching and prefetching can effectively mask their access latency. These characteristics of the access patterns motivated several researchers to propose parallel I/O optimizations both at library and file system levels. However, these optimizations are not always integrated across different layers in the systems. In this dissertation we propose a novel generic parallel I/O architecture for clusters and supercomputers. Our design is aimed at large-scale parallel architectures with thousands of compute nodes. Besides acting as middleware for existing parallel file systems, our architecture provides on-line virtualization of storage resources. Another objective of this thesis is to factor out the common parallel I/O functionality from clusters and supercomputers in generic modules in order to facilitate porting of scientific applications across these platforms. Our solution is based on a multi-tier cache architecture, collective I/O, and asynchronous data staging strategies hiding the latency of data transfer between cache tiers. The thesis targets to reduce the file access latency perceived by the data-intensive parallel scientific applications by multi-layer asynchronous data transfers. In order to accomplish this objective, our techniques leverage the multi-core architectures by overlapping computation with communication and I/O in parallel threads. Prototypes of our solutions have been deployed on both clusters and Blue Gene supercomputers. Performance evaluation shows that the combination of collective strategies with overlapping of computation, communication, and I/O may bring a substantial performance benefit for access patterns common for parallel scientific applications.-----------------------------------------------------------------------------------------------------------------------------En los últimos años se ha observado un incremento sustancial de la cantidad de datos producidos por las aplicaciones científicas paralelas y de la necesidad de almacenar estos datos de forma persistente. Los sistemas de ficheros paralelos como PVFS, Lustre y GPFS han ofrecido una solución escalable para esta demanda creciente de almacenamiento. La mayoría de las aplicaciones científicas son escritas haciendo uso de la interfaz de paso de mensajes (MPI), que se ha convertido en un estándar de-facto de programación para las arquitecturas de memoria distribuida. Las aplicaciones paralelas que usan MPI pueden acceder a los sistemas de ficheros paralelos a través de la interfaz ofrecida por MPI-IO. Los patrones de acceso de las aplicaciones científicas paralelas consisten en un gran número de accesos pequeños y no contiguos. Para tamaños de acceso pequeños, el rendimiento viene limitado por la latencia de las transferencias de red y disco. Además, las aplicaciones científicas llevan a cabo accesos con una alta localidad espacial entre los distintos procesos en los nodos de E/S. Adicionalmente, las aplicaciones científicas presentan típicamente un comportamiento repetitivo. Cuando los patrones de acceso de E/S son repetitivos, técnicas como escritura demorada y lectura adelantada pueden enmascarar de forma eficiente las latencias de los accesos de E/S. Estas características han motivado a muchos investigadores en proponer optimizaciones de E/S tanto a nivel de biblioteca como a nivel del sistema de ficheros. Sin embargo, actualmente estas optimizaciones no se integran siempre a través de las distintas capas del sistema. El objetivo principal de esta tesis es proponer una nueva arquitectura genérica de E/S paralela para clusters y supercomputadores. Nuestra solución está basada en una arquitectura de caches en varias capas, una técnica de E/S colectiva y estrategias de acceso asíncronas que ocultan la latencia de transferencia de datos entre las distintas capas de caches. Nuestro diseño está dirigido a arquitecturas paralelas escalables con miles de nodos de cómputo. Además de actuar como middleware para los sistemas de ficheros paralelos existentes, nuestra arquitectura debe proporcionar virtualización on-line de los recursos de almacenamiento. Otro de los objeticos marcados para esta tesis es la factorización de las funcionalidades comunes en clusters y supercomputadores, en módulos genéricos que faciliten el despliegue de las aplicaciones científicas a través de estas plataformas. Se han desplegado distintos prototipos de nuestras soluciones tanto en clusters como en supercomputadores. Las evaluaciones de rendimiento demuestran que gracias a la combicación de las estratégias colectivas de E/S y del solapamiento de computación, comunicación y E/S, se puede obtener una sustancial mejora del rendimiento en los patrones de acceso anteriormente descritos, muy comunes en las aplicaciones paralelas de caracter científico

Αποθηκευτικά συστήματα με δυνατότητα κλιμάκωσης σε eXascale περιβάλλοντα

Οι επιστημονικοί υπολογισμοί μεγάλης κλίμακας είναι εξαιρετικά απαιτητικοί με αποτέλεσμα να έχουν μεγάλες ανάγκες σε υπολογιστική ισχύ. Οι παράλληλοι υπολογισμοί και τα παράλληλα συστήματα αρχείων αναγνωρίζονται ως η μόνη εφικτή λύση σε αυτού του είδους τα προβλήματα, ενώ οι διεργασίες εισόδου/εξόδου αποτελούν το σημαντικότερο σημείο συμφόρησης στην απόδοση των εφαρμογών. Οι σημαντικότεροι παράγοντες που επηρεάζουν την I/O απόδοση είναι ο αριθμός των παράλληλων διεργασιών που συμμετέχουν στις μεταφορές των δεδομένων, το μέγεθος της κάθε μεταφοράς καθώς και τα διάφορα I/O μοτίβα πρόσβασης. Τα διαμοιραζόμενα συστήματα αρχείων έχουν σημαντικούς περιορισμούς όταν εφαρμόζονται σε μεγάλης κλίμακας συστήματα, επειδή το εύρος ζώνης δεν κλιμακώνει οικονομικά αλλά και γιατί η I/O κίνηση στην δικτυακή υποδομή και στους αποθηκευτικούς κόμβους μπορεί να επηρεαστεί από άλλες ξένες διεργασίες/εφαρμογές. Στοχεύοντας στην επίλυση των πιο πάνω περιορισμών αναπτύχθηκε το πλαίσιο ΙΚΑΡΟΣ ως ένας μηχανισμός που επιτρέπει το συντονισμό, με δυναμικό τρόπο, της Ι/Ο αρχιτεκτονικής, χρησιμοποιώντας συγκεκριμένες παραμέτρους εισόδου. Το ΙΚΑΡΟΣ παρέχει συντονισμένες παράλληλες μεταφορές δεδομένων στην συνολική ροή (τοπική- απομακρυσμένη πρόσβαση), με αποτέλεσμα τη μείωση του ανταγωνισμού, για πόρους, μεταξύ των αποθηκευτικών και δικτυακών μέσων. Δημιουργεί, δυναμικά, αποκλειστικές/ήμι-αποκλειστικές συστοιχίες αποθηκευτικών μέσων ανά διεργασία, με αποτέλεσμα τη βελτίωση της Ι/Ο απόδοσης κατά 33% χρησιμοποιώντας το 1/3 των διαθέσιμων σκληρών δίσκων.High performance computing (HPC) has crossed the Petaflop mark and is reaching the Exaflop range quickly. The exascale system is projected to have millions of nodes, with thousands of cores for each node. At such an extreme scale, the substantial amount of concurrency can cause a critical contention issue for I/O system. This study proposes a dynamically coordinated I/O architecture for addressing some of the limitations that current parallel file systems and storage architectures are facing with very large-scale systems. The fundamental idea is to coordinate I/O accesses according to the topology/profile of the infrastructure, the load metrics, and the I/O demands of each application. The measurements have shown that by using IKAROS approach we can fully utilize the provided I/O and network resources, minimize disk and network contention, and achieve better performance

Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA)

The Helmholtz Association funded the "Large-Scale Data Management and Analysis" portfolio theme from 2012-2016. Four Helmholtz centres, six universities and another research institution in Germany joined to enable data-intensive science by optimising data life cycles in selected scientific communities. In our Data Life cycle Labs, data experts performed joint R&D together with scientific communities. The Data Services Integration Team focused on generic solutions applied by several communities

Service-oriented models for audiovisual content storage

What are the important topics to understand if involved with storage services to hold digital audiovisual content? This report takes a look at how content is created and moves into and out of storage; the storage service value networks and architectures found now and expected in the future; what sort of data transfer is expected to and from an audiovisual archive; what transfer protocols to use; and a summary of security and interface issues

File system metadata virtualization

The advance of computing systems has brought new ways to use and access the stored data that push the architecture of traditional file systems to its limits, making them inadequate to handle the new needs. Current challenges affect both the performance of high-end computing systems and its usability from the applications perspective. On one side, high-performance computing equipment is rapidly developing into large-scale aggregations of computing elements in the form of clusters, grids or clouds. On the other side, there is a widening range of scientific and commercial applications that seek to exploit these new computing facilities. The requirements of such applications are also heterogeneous, leading to dissimilar patterns of use of the underlying file systems. Data centres have tried to compensate this situation by providing several file systems to fulfil distinct requirements. Typically, the different file systems are mounted on different branches of a directory tree, and the preferred use of each branch is publicised to users. A similar approach is being used in personal computing devices. Typically, in a personal computer, there is a visible and clear distinction between the portion of the file system name space dedicated to local storage, the part corresponding to remote file systems and, recently, the areas linked to cloud services as, for example, directories to keep data synchronized across devices, to be shared with other users, or to be remotely backed-up. In practice, this approach compromises the usability of the file systems and the possibility of exploiting all the potential benefits. We consider that this burden can be alleviated by determining applicable features on a per-file basis, and not associating them to the location in a static, rigid name space. Moreover, usability would be further increased by providing multiple dynamic name spaces that could be adapted to specific application needs. This thesis contributes to this goal by proposing a mechanism to decouple the user view of the storage from its underlying structure. The mechanism consists in the virtualization of file system metadata (including both the name space and the object attributes) and the interposition of a sensible layer to take decisions on where and how the files should be stored in order to benefit from the underlying file system features, without incurring on usability or performance penalties due to inadequate usage. This technique allows to present multiple, simultaneous virtual views of the name space and the file system object attributes that can be adapted to specific application needs without altering the underlying storage configuration. The first contribution of the thesis introduces the design of a metadata virtualization framework that makes possible the above-mentioned decoupling; the second contribution consists in a method to improve file system performance in large-scale systems by using such metadata virtualization framework; finally, the third contribution consists in a technique to improve the usability of cloud-based storage systems in personal computing devices.Postprint (published version