File server scaling with network-attached secure disks

Gibson, Garth A.; Nagle, David F.; Amiri, Khalil; Chang, Fay W.; Feinberg, Eugene M.; Gobioff, Howard; Lee, Chen; Ozceri, Berend; Riedel, Erik; Rochberg, David; Zelenka, Jim

doi:10.1145/258623.258696

Cited by 35 publications

(28 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Of these, Lustre [8], PVFS2 [19,28], and NASD [11,12] (and the commercial version Panasas [25]) are the most widely used. LWFS distinguishes itself from these other file systems in two areas: how services are partitioned, and the trust relationship between components.…”

Section: Related Workmentioning

confidence: 99%

Lightweight I/O for Scientific Applications

Oldfield

Ward

Riesen

et al. 2006

2006 IEEE International Conference on Cluster Computing

View full text Add to dashboard Cite

Today's high-end massively parallel processing (MPP) machines have thousands to tens of thousands of processors, with next-generation systems planned to have in excess of one hundred thousand processors. For systems of such scale, efficient I/O is a significant challenge that cannot be solved using traditional approaches. In particular, general purpose parallel file systems that limit applications to standard interfaces and access policies do not scale and will likely be a performance bottleneck for many scientific applications.In this paper, we investigate the use of a "lightweight" approach to I/O that requires the application or I/O-library developer to extend a core set of critical I/O functionality with the minimum set of features and services required by its target applications. We argue that this approach allows the development of I/O libraries that are both scalable and secure. We support our claims with preliminary results for a lightweight checkpoint operation on a development cluster at Sandia.

show abstract

Section: Related Workmentioning

confidence: 99%

Lightweight I/O for Scientific Applications

Oldfield

Ward

Riesen

et al. 2006

2006 IEEE International Conference on Cluster Computing

View full text Add to dashboard Cite

show abstract

“…Inspired by the evolution from node-attached to networkattached storage [1], we propose a novel cluster architecture where the mapping between general-purpose nodes and accelerators is dynamic. Instead of attaching accelerators statically to individual nodes, our architecture maintains a pool of network-attached accelerators that can be assigned to their hosts on demand.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Accelerator-Cluster Architecture

Rinke

Becker

Lippert³

et al. 2012

2012 41st International Conference on Parallel Processing Workshops

View full text Add to dashboard Cite

Accelerators such as graphics processing units (GPUs) provide an inexpensive way of improving the performance of cluster systems. In such an arrangement, the individual nodes of the cluster are directly connected to one or more accelerator devices via PCI Express. This results in a static mapping of accelerators onto compute nodes, where each accelerator can only be accessed from exactly one compute node. While this static mapping enables efficient data transfers between a given accelerator and the compute node it belongs to, differing computational demands across jobs may, however, produce either underutilized accelerators or nodes whose computational demands cannot be satisfied with the number of accelerators available to them. In particular, smaller numbers of GPUs available per node may enforce explicit MPI parallelism across compute nodes where it is not necessary. To address this limitation, we propose a novel acceleratorcluster architecture in which network-attached accelerators are dynamically assigned to compute nodes. This allows not only their optimal utilization but also a more precise match between application requirements and accelerator hardware. We outline the general concept of our dynamic architecture and show that it can offer substantial benefits to certain classes of applications without significantly harming the performance of others.

show abstract

“…Several researchers have recently explored the concept of programmable disks [3,10,13,18,26,33]. Initial studies on using Active Disks for databases compared the performance of a moderate size Active Disk farm ( 32 disks) with that of uniprocessor servers with conventional disks [3,26].…”

Section: Related Workmentioning

confidence: 99%

“…Unlike the limited repertoire of operations performed by database machines, Active Disks take advantage of algorithmic research for shared-nothing architectures to provide efficient implementations of a wide variety of operations. Furthermore, Active Disks can be used to perform operations for non-relational data such as image processing [3,26] and file-system and security-related processing [10,13,33,34].…”

Section: Related Workmentioning

confidence: 99%

Evaluation of active disks for decision support databases

Uysal

Acharya²,

Saltz³

Proceedings Sixth International Symposium on High-Performance Computer Architecture. HPCA-6 (Cat. No.PR00550)

View full text Add to dashboard Cite

Growth and usage trends for large decision support databases indicate that there is a need for architectures that scale the processing power as the dataset grows. To meet this need, several researchers have recently proposed Active Disk architectures which integrate substantial processing power and memory into disk units. In this paper, we evaluate Active Disks for decision support databases. First, we compare the performance of Active Disks with that of existing scalable server architectures: SMP-based conventional disk farms and commodity clusters of PCs. Second, we evaluate the impact of several design choices on the performance of Active Disks. We focus on the performance impact of interconnect bandwidth, amount of disk memory and disk-to-disk communication architecture on decision support workloads. Our results show that for identical disks, number of processors and I/O interconnect, Active Disks provide better price/performance than both SMPbased conventional disk farms and commodity clusters. Experiments evaluating the impact of design alternatives in Active Disk architectures indicate that: (1) for configurations up to 64 disks, a dual fibre channel arbitrated loop interconnect is sufficient even for the most communicationintensive decision support tasks; (2) most decision support tasks do not require a large amount of memory; and (3) direct disk-to-disk communication is necessary for achieving good performance on tasks that repartition all (or a large fraction of) their dataset.

show abstract

File server scaling with network-attached secure disks

Cited by 35 publications

References 39 publications

Lightweight I/O for Scientific Applications

Lightweight I/O for Scientific Applications

A Dynamic Accelerator-Cluster Architecture

Evaluation of active disks for decision support databases

Contact Info

Product

Resources

About