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Dive into the research topics where Jim Zelenka is active.

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Featured researches published by Jim Zelenka.


architectural support for programming languages and operating systems | 1998

A cost-effective, high-bandwidth storage architecture

Garth A. Gibson; David F. Nagle; Khalil Amiri; Jeff Butler; Fay W. Chang; Howard Gobioff; Charles Hardin; Erik Riedel; David Rochberg; Jim Zelenka

This paper describes the Network-Attached Secure Disk (NASD) storage architecture, prototype implementations oj NASD drives, array management for our architecture, and three, filesystems built on our prototype. NASD provides scalable storage bandwidth without the cost of servers used primarily, for transferring data from peripheral networks (e.g. SCSI) to client networks (e.g. ethernet). Increasing datuset sizes, new attachment technologies, the convergence of peripheral and interprocessor switched networks, and the increased availability of on-drive transistors motivate and enable this new architecture. NASD is based on four main principles: direct transfer to clients, secure interfaces via cryptographic support, asynchronous non-critical-path oversight, and variably-sized data objects. Measurements of our prototype system show that these services can be cost-effectively integrated into a next generation disk drive ASK. End-to-end measurements of our prototype drive andfilesysterns suggest that NASD cun support conventional distributed filesystems without performance degradation. More importantly, we show scaluble bandwidth for NASD-specialized filesystems. Using a parallel data mining application, NASD drives deliver u linear scaling of 6.2 MB/s per clientdrive pair, tested with up to eight pairs in our lab.


measurement and modeling of computer systems | 1997

File server scaling with network-attached secure disks

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

By providing direct data transfer between storage and client, network-attached storage devices have the potential to improve scalability for existing distributed file systems (by removing the server as a bottleneck) and bandwidth for new parallel and distributed file systems (through network striping and more efficient data paths). Together, these advantages influence a large enough fraction of the storage market to make commodity network-attached storage feasible. Realizing the technologys full potential requires careful consideration across a wide range of file system, networking and security issues. This paper contrasts two network-attached storage architectures---(1) Networked SCSI disks (NetSCSI) are network-attached storage devices with minimal changes from the familiar SCSI interface, while (2) Network-Attached Secure Disks (NASD) are drives that support independent client access to drive object services. To estimate the potential performance benefits of these architectures, we develop an analytic model and perform trace-driven replay experiments based on AFS and NFS traces. Our results suggest that NetSCSI can reduce file server load during a burst of NFS or AFS activity by about 30%. With the NASD architecture, server load (during burst activity) can be reduced by a factor of up to five for AFS and up to ten for NFS.


ieee computer society international conference | 1995

The Scotch parallel storage systems

Garth A. Gibson; Daniel Stodolsky; Fay W. Chang; William V. Courtright Ii; C. G. Demetriou; Eka Ginting; Mark Holland; Qingming Ma; L. Neal; R. H. Patterson; J. Su; R. Youssef; Jim Zelenka

To meet the bandwidth needs of modern computer systems, parallel storage systems are evolving beyond RAID levels 1 through 5. The parallel Data Lab at Carnegie Mellon University has constructed three Scotch parallel storage testbeds to explore and evaluate five directions in RAID evolution: first, the development of new RAID architectures to reduce the cost/performance penalty of maintaining redundant data; second, an extensible software framework for rapid prototyping of new architectures; third, mechanisms to reduce the complexity of and automate error-handling in RAID subsystems; fourth, a file system extension that allows serial programs to exploit parallel storage; and lastly, a parallel file system that extends the RAID advantages to distributed parallel computing environments. This paper describes these five RAID evolutions and the testbeds in which they are being implemented and evaluated.


measurement and modeling of computer systems | 1996

RAIDframe: rapid prototyping for disk arrays

William V. Courtright Ii; Garth A. Gibson; Mark Holland; Jim Zelenka

Abstract : The complexity of advanced disk array architectures makes accurate representation necessary arduous, and error-prone. In this paper, we present RAIDframe, an array framework that separates architectural policy from execution mechanism. RAIDframe facilitations rapid prototyping of new RAID architectures by localizing modifications and providing libraries of existing architectures to extend. In addition, RAIDframe implemented architectures run the same code as a synthetic and trace-driven simulator, as a user-level application managing raw disks, and as a Digital Unix device-driver capable of mounting a filesystem. Evaluation shows that RAIDframe performance is equivalent to less complex array implementations and thance is equivalent to less complex array implementations and that case studies of RAID levels 0, 1, 4, 5, 6, and parity declustering achieve expected performance.


Proceedings of IEEE International Computer Performance and Dependability Symposium | 1996

A structured approach to redundant disk array implementation

William V. Courtright Ii; Garth A. Gibson; Mark Holland; Jim Zelenka

Error recovery in redundant disk arrays is typically performed in an ad hoc fashion, requiring architecture-specific code which limits extensibility and is difficult to verify. In this paper, we describe a technique for automating the execution of redundant disk array operations, including recovery from errors, independent of array architecture. Our approach employs a graphical representation of array operations and a two-phase error recovery scheme we refer to as roll-away error recovery. We demonstrate the validity of this approach in RAID-frame, a prototyping framework that separates architectural policy from execution mechanism. RAID-frame facilitates rapid prototyping of new RAID architectures by localizing modifications. In addition, RAID-frame implemented architectures run the same code when configured as an event-driven simulator, a user-level application managing raw disks, and as a Digital Unix device-driver capable of mounting a filesystem. Evaluation shows that RAID-frame performance is equivalent to less complex array implementations and that case studies of RAID levels 0, 1, 4, 5, 6, and parity declustering achieve expected performance.


symposium on operating systems principles | 1995

Informed prefetching and caching

R. H. Patterson; Garth A. Gibson; Eka Ginting; Daniel Stodolsky; Jim Zelenka


file and storage technologies | 2008

Scalable performance of the Panasas parallel file system

Brent Welch; Marc Unangst; Zainul Abbasi; Garth A. Gibson; Brian Mueller; Jason Small; Jim Zelenka; Bin Zhou


Archive | 1999

NASD Scalable Storage Systems

Garth A. Gibson; David F. Nagle; William V. Courtright Ii; Nat Lanza; Paul Mazaitis; Marc Unangst; Jim Zelenka


Archive | 1997

RAIDframe: A Rapid Prototyping Tool for RAID Systems

William V. Courtright Ii; Garth A. Gibson; Mark Holland; LeAnn Neal-Reilly; Jim Zelenka


architectural support for programming languages and operating systems | 1998

High-bandwidth storage architecture

Garth A. Gibson; David F. Nagle; Khalil Amiri; Fay W. Chang; Howard Gobio; Charles Hardin; Erik Riedel; David Rochberg; Jim Zelenka

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Garth A. Gibson

Carnegie Mellon University

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Mark Holland

Carnegie Mellon University

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David F. Nagle

Carnegie Mellon University

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Daniel Stodolsky

Carnegie Mellon University

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David Rochberg

Carnegie Mellon University

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Eka Ginting

Carnegie Mellon University

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Khalil Amiri

Carnegie Mellon University

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