Duality Between Prefetching and Queued Writing with Parallel Disks

This is the published version, made available with the permission of the publisher. Copyright © 2005 Society for Industrial and Applied Mathematics.Parallel disks promise to be a cost effective means for achieving high bandwidth in applications involving massive data sets, but algorithms for parallel disks can be difficult to devise. To combat this problem, we define a useful and natural duality between writing to parallel disks and the seemingly more difficult problem of prefetching. We first explore this duality for applications involving read-once accesses using parallel disks. We get a simple linear time algorithm for computing optimal prefetch schedules and analyze the efficiency of the resulting schedules for randomly placed data and for arbitrary interleaved accesses to striped sequences. Duality also provides an optimal schedule for prefetching plus caching, where blocks can be accessed multiple times. Another application of this duality gives us the first parallel disk sorting algorithms that are provably optimal up to lower-order terms. One of these algorithms is a simple and practical variant of multiway mergesort, addressing a question that had been open for some time

Duality Between Prefetching and Queued Writing with Parallel Disks

AMS subject classifications. 68W10, 68W20, 68W40, 68M20, 68P10, 68P20, 68Q17 DOI. 10.1137/S0097539703431573Parallel disks promise to be a cost effective means for achieving high bandwidth in applications involving massive data sets, but algorithms for parallel disks can be difficult to devise. To combat this problem, we define a useful and natural duality between writing to parallel disks and the seemingly more difficult problem of prefetching. We first explore this duality for applications involving read-once accesses using parallel disks. We get a simple linear time algorithm for computing optimal prefetch schedules and analyze the efficiency of the resulting schedules for randomly placed data and for arbitrary interleaved accesses to striped sequences. Duality also provides an optimal schedule for prefetching plus caching, where blocks can be accessed multiple times. Another application of this duality gives us the first parallel disk sorting algorithms that are provably optimal up to lower-order terms. One of these algorithms is a simple and practical variant of multiway mergesort, addressing a question that had been open for some time

Metadata And Data Management In High Performance File And Storage Systems

With the advent of emerging e-Science applications, today\u27s scientific research increasingly relies on petascale-and-beyond computing over large data sets of the same magnitude. While the computational power of supercomputers has recently entered the era of petascale, the performance of their storage system is far lagged behind by many orders of magnitude. This places an imperative demand on revolutionizing their underlying I/O systems, on which the management of both metadata and data is deemed to have significant performance implications. Prefetching/caching and data locality awareness optimizations, as conventional and effective management techniques for metadata and data I/O performance enhancement, still play their crucial roles in current parallel and distributed file systems. In this study, we examine the limitations of existing prefetching/caching techniques and explore the untapped potentials of data locality optimization techniques in the new era of petascale computing. For metadata I/O access, we propose a novel weighted-graph-based prefetching technique, built on both direct and indirect successor relationship, to reap performance benefit from prefetching specifically for clustered metadata serversan arrangement envisioned necessary for petabyte scale distributed storage systems. For data I/O access, we design and implement Segment-structured On-disk data Grouping and Prefetching (SOGP), a combined prefetching and data placement technique to boost the local data read performance for parallel file systems, especially for those applications with partially overlapped access patterns. One high-performance local I/O software package in SOGP work for Parallel Virtual File System in the number of about 2000 C lines was released to Argonne National Laboratory in 2007 for potential integration into the production mode

Prefetching techniques for client server object-oriented database systems

The performance of many object-oriented database applications suffers from the page fetch latency which is determined by the expense of disk access. In this work we suggest several prefetching techniques to avoid, or at least to reduce, page fetch latency. In practice no prediction technique is perfect and no prefetching technique can entirely eliminate delay due to page fetch latency. Therefore we are interested in the trade-off between the level of accuracy required for obtaining good results in terms of elapsed time reduction and the processing overhead needed to achieve this level of accuracy. If prefetching accuracy is high then the total elapsed time of an application can be reduced significantly otherwise if the prefetching accuracy is low, many incorrect pages are prefetched and the extra load on the client, network, server and disks decreases the whole system performance. Access pattern of object-oriented databases are often complex and usually hard to predict accurately. The ..

Pervasive Data Access in Wireless and Mobile Computing Environments

The rapid advance of wireless and portable computing technology has brought a lot of research interests and momentum to the area of mobile computing. One of the research focus is on pervasive data access. with wireless connections, users can access information at any place at any time. However, various constraints such as limited client capability, limited bandwidth, weak connectivity, and client mobility impose many challenging technical issues. In the past years, tremendous research efforts have been put forth to address the issues related to pervasive data access. A number of interesting research results were reported in the literature. This survey paper reviews important works in two important dimensions of pervasive data access: data broadcast and client caching. In addition, data access techniques aiming at various application requirements (such as time, location, semantics and reliability) are covered

MapReduce analysis for cloud-archived data

Public storage clouds have become a popular choice for archiving certain classes of enterprise data - for example, application and infrastructure logs. These logs contain sensitive information like IP addresses or user logins due to which regulatory and security requirements often require data to be encrypted before moved to the cloud. In order to leverage such data for any business value, analytics systems (e.g. Hadoop/MapReduce) first download data from these public clouds, decrypt it and then process it at the secure enterprise site. We propose VNCache: an efficient solution for MapReduceanalysis of such cloud-archived log data without requiring an apriori data transfer and loading into the local Hadoop cluster. VNcache dynamically integrates cloud-archived data into a virtual namespace at the enterprise Hadoop cluster. Through a seamless data streaming and prefetching model, Hadoop jobs can begin execution as soon as they are launched without requiring any apriori downloading. With VNcache's accurate pre-fetching and caching, jobs often run on a local cached copy of the data block significantly improving performance. When no longer needed, data is safely evicted from the enterprise cluster reducing the total storage footprint. Uniquely, VNcache is implemented with NO changes to the Hadoop application stack. © 2014 IEEE

Optimizing Virtual Machine I/O Performance in Cloud Environments

Maintaining closeness between data sources and data consumers is crucial for workload I/O performance. In cloud environments, this kind of closeness can be violated by system administrative events and storage architecture barriers. VM migration events are frequent in cloud environments. VM migration changes VM runtime inter-connection or cache contexts, significantly degrading VM I/O performance. Virtualization is the backbone of cloud platforms. I/O virtualization adds additional hops to workload data access path, prolonging I/O latencies. I/O virtualization overheads cap the throughput of high-speed storage devices and imposes high CPU utilizations and energy consumptions to cloud infrastructures. To maintain the closeness between data sources and workloads during VM migration, we propose Clique, an affinity-aware migration scheduling policy, to minimize the aggregate wide area communication traffic during storage migration in virtual cluster contexts. In host-side caching contexts, we propose Successor to recognize warm pages and prefetch them into caches of destination hosts before migration completion. To bypass the I/O virtualization barriers, we propose VIP, an adaptive I/O prefetching framework, which utilizes a virtual I/O front-end buffer for prefetching so as to avoid the on-demand involvement of I/O virtualization stacks and accelerate the I/O response. Analysis on the traffic trace of a virtual cluster containing 68 VMs demonstrates that Clique can reduce inter-cloud traffic by up to 40%. Tests of MPI Reduce_scatter benchmark show that Clique can keep VM performance during migration up to 75% of the non-migration scenario, which is more than 3 times of the Random VM choosing policy. In host-side caching environments, Successor performs better than existing cache warm-up solutions and achieves zero VM-perceived cache warm-up time with low resource costs. At system level, we conducted comprehensive quantitative analysis on I/O virtualization overheads. Our trace replay based simulation demonstrates the effectiveness of VIP for data prefetching with ignorable additional cache resource costs

New techniques to model energy-aware I/O architectures based on SSD and hard disk drives

For years, performance improvements at the computer I/O subsystem and at other subsystems have advanced at their own pace, being less the improvements at the I/O subsystem, and making the overall system speed dependant of the I/O subsystem speed. One of the main factors for this imbalance is the inherent nature of disk drives, which has allowed big advances in disk densities, but not so many in disk performance. Thus, to improve I/O subsystem performance, disk drives have become a goal of study for many researchers, having to use, in some cases, different kind of models. Other research studies aim to improve I/O subsystem performance by tuning more abstract I/O levels. Since disk drives lay behind those levels, real disk drives or just models need to be used. One of the most common techniques to evaluate the performance of a computer I/O subsystem is found on detailed simulation models including specific features of storage devices like disk geometry, zone splitting, caching, read-ahead buffers and request reordering. However, as soon as a new technological innovation is added, those models need to be reworked to include new characteristics, making difficult to have general models up to date. Our alternative is modeling a storage device as a black-box probabilistic model, where the storage device itself, its interface and the interconnection mechanisms are modeled as a single stochastic process, defining the service time as a random variable with an unknown distribution. This approach allows generating disk service times needing less computational power by means of a variate generator included in a simulator. This approach allows to reach a greater scalability in I/O subsystems performance evaluations by means of simulation. Lately, energy saving for computing systems has become an important need. In mobile computers, the battery life is limited to a certain amount of time, and not wasting energy at certain parts would extend the usage of the computer. Here, again the computer I/O subsystem has pointed out as field of study, because disk drives, which are a main part of it, are one of the most power consuming elements due to their mechanical nature. In server or enterprise computers, where the number of disks increase considerably, power saving may reduce cooling requirements for heat dissipation and thus, great monetary costs. This dissertation also considers the question of saving energy in the disk drive, by making advantage of diverse devices in hybrid storage systems, composed of Solid State Disks (SSDs) and Disk drives. SSDs and Disk drives offer different power characteristics, being SSDs much less power consuming than disk drives. In this thesis, several techniques that use SSDs as supporting devices for Disk drives, are proposed. Various options for managing SSDs and Disk devices in such hybrid systems are examinated, and it is shown that the proposed methods save energy and monetary costs in diverse scenarios. A simulator composed of Disks and SSD devices was implemented. This thesis studies the design and evaluation of the proposed approaches with the help of realistic workloads. --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Durante años, las mejoras de rendimiento en el subsistema de E/S del ordenador y en otros subsistemas han avanzado a su propio ritmo, siendo menores las mejoras en el subsistema de E/S, y provocando que la velocidad global del sistema dependa de la velocidad del subsistema de E/S. Uno de los factores principales de este desequilibrio es la naturaleza inherente de las unidades de disco, la cual que ha permitido grandes avances en las densidades de disco, pero no así en su rendimiento. Por lo tanto, para mejorar el rendimiento del subsistema de E/S, las unidades de disco se han convertido en objetivo de estudio para muchos investigadores, que se ven obligados a utilizar, en algunos casos, diferentes tipos de modelos o simuladores. Otros estudios de investigación tienen como objetivo mejorar el rendimiento del subsistema de E/S, estudiando otros niveles más abstractos. Como los dispositivos de disco siguen estando detrás de esos niveles, tanto discos reales como modelos pueden usarse para esos estudios. Una de las técnicas más comunes para evaluar el rendimiento del subsistema de E/S de un ordenador se ha encontrado en los modelos de simulación detallada, los cuales modelan características específicas de los dispositivos de almacenamiento como la geometría del disco, la división en zonas, el almacenamiento en caché, el comportamiento de los buffers de lectura anticipada y la reordenación de solicitudes. Sin embargo, cuando se agregan innovaciones tecnológicas, los modelos tienen que ser revisados a fin de incluir nuevas características que incorporen dichas innovaciones, y esto hace difícil el tener modelos generales actualizados. Nuestra alternativa es el modelado de un dispositivo de almacenamiento como un modelo probabilístico de caja negra, donde el dispositivo de almacenamiento en sí, su interfaz y sus mecanismos de interconexión se tratan como un proceso estocástico, definiendo el tiempo de servicio como una variable aleatoria con una distribución desconocida. Este enfoque permite la generación de los tiempos de servicio del disco, de forma que se necesite menos potencia de cálculo a través del uso de un generador de variable aleatoria incluido en un simulador. De este modo, se permite alcanzar una mayor escalabilidad en la evaluación del rendimiento del subsistema de E/S a través de la simulación. En los últimos años, el ahorro de energía en los sistemas de computación se ha convertido en una necesidad importante. En ordenadores portátiles, la duración de la batería se limita a una cierta cantidad de tiempo, y no desperdiciar energía en ciertas partes haría más largo el uso del ordenador. Aquí, de nuevo el subsistema de E/S se señala como campo de estudio, ya que las unidades de disco, que son una parte principal del mismo, son uno de los elementos de más consumo de energía debido a su naturaleza mecánica. En los equipos de servidor o de empresa, donde el número de discos aumenta considerablemente, el ahorro de energía puede reducir las necesidades de refrigeración para la disipación de calor y por lo tanto, grandes costes monetarios. Esta tesis también considera la cuestión del ahorro energético en la unidad de disco, haciendo uso de diversos dispositivos en sistemas de almacenamiento híbridos, que emplean discos de estado sólido (SSD) y unidades de disco. Las SSD y unidades de disco ofrecen diferentes características de potencia, consumiendo las SSDs menos energía que las unidades de disco. En esta tesis se proponen varias técnicas que utilizan los SSD como apoyo a los dispositivos de disco. Se examinan las diversas opciones para la gestión de las SSD y los dispositivos de disco en tales sistemas híbridos, y se muestra que los métodos propuestos ahorran energía y costes monetarios en diversos escenarios. Se ha implementado un simulador compuesto por discos y dispositivos SSD. Esta tesis estudia el diseño y evaluación de los enfoques propuestos con la ayuda de las cargas de trabajo reales