HPCwire: Stork Data Scheduler Now Available

The Leading Source for Global News and Information Covering the Ecosystem of High Productivity Computing

HPCwire >> Off the Wire

December 03, 2008

Stork Data Scheduler Now Available

Dec. 3 -- Louisiana State University Stork team announced today that first full release of Stork Data Scheduler (Stork 1.0) is now available on the Stork Project Web page.

Stork is a batch scheduler specialized in data placement and data movement, which is based on the concept of making data placement a first class entity in a distributed computing environment. Stork understands the semantics and characteristics of data placement tasks and implements techniques specific to queuing, scheduling, and optimization of these type of tasks.

One key benefit of distributed resources is that it allows institutions and organizations to gain access to resources needed for large-scale applications that they would not otherwise have. But in order to facilitate the sharing of compute, storage, and network resources between collaborating parties, middleware is needed for planning, scheduling, and management of the tasks as well as the resources. The majority of existing research has been on the management of compute tasks and resources, as they are widely considered to be the most expensive. As scientific applications become more data intensive, however, the management of storage resources and data movement between the storage and compute resources is becoming the main bottleneck. Many jobs executing in distributed environments are failed or are inhibited by overloaded storage servers. These failures prevent scientists from making progress in their research.

Accessing and transferring widely distributed data can be extremely inefficient and can introduce unreliability. For instance, an application may suffer from insufficient storage space when staging-in the input data, generating the output, and staging-out the generated data to a remote storage. This can lead to trashing of the storage server and subsequent timeout due to too many concurrent read data transfers, ultimately causing server crashes due to an overload of write data transfers. Other third party data transfers may stall indefinitely due to loss of acknowledgment. And even if transfer is performed efficiently, faulty hardware involved in staging and hosting can cause data corruption. Furthermore, remote access will suffer from unforeseeable contingencies such as performance degradation due to unplanned data transfers, and intermittent network outages.

Traditional distributed computing systems closely couple data handling and computation. They consider data resources as second class entities, and access to data as a side effect of computation. Data placement (i.e. access, retrieval, and/or movement of data) is either embedded in the computation and causes the computation to delay, or performed as simple scripts which do not have the privileges of a job. The insufficiency of the traditional systems and existing CPU-oriented schedulers in dealing with the complex data handling problem has yielded a new scheduler specializing in data placement: the Stork Data Scheduler.

Using Stork, the users can transfer very large data sets via single command. The checkpointing, error recovery and retry mechanisms ensure the completion of the tasks even in case of unexpected failures. Multi-protocol support makes Stork one of the most powerful data transfer tools available. This feature does not only allow Stork to access and manage different data storage systems, but can also be used a s a fall-back mechanism when one of the protocols fails in transferring the desired data. Optimizations such as request ordering, task aggregation, and connection caching provide enhanced performance compared to other data transfer tools.

The Stork Data Scheduler can also interact with higher level planners and workflow managers for the coordination of compute and data tasks. This allows the users to schedule both CPU resources and storage resources asynchronously as two parallel universes, overlapping computation and I/O. Currently, some of the widely used workflow tools such as Condor DAGMan and Pegasus already come with Stork support.

The Stork Data Scheduler is currently being used in several NSF, DOE, and ONR funded projects such as PetaShare, UCoMS, and SCOOP.

For more information on the Stork Project, contact the project lead Dr. Tevfik Kosar at kosar@cct.lsu.edu.

Stork Project Web page: http://www.storkproject.org.

-----

Source: Louisiana State University

Article Tools

Share Options

(Digg, Technorati, more)

Subscribe

Subscribe to HPCwire

Discussion

There are 0 discussion items posted.

Join the Discussion

You must be a registered user in order to comment on HPCwire stories.

Members enjoy:

	Access to Special Content, including Podcasts, Webcasts, and Whitepapers and more!
	Ability to take an active role in the discussions that are shaping the HPC technology discipline!
	Special offers available only to HPCwire members!

Become a Registered User Today!

Registered Users Log in Here to Comment

Email Address:	Password (case sensitive)

Remember me	Forgot Password?

RSS Feeds

Feeds by Topic

Feeds by Industry

Feeds by Content Type

Feature Articles

The Week in Review

C-DAC announces plans for a petaflop system; IBM researchers are working on vertical integration techniques to extend Moore's Law another 15 years. We recap those stories and more in our weekly wrapup.
Read More...

Moscow State University Supercomputer Has Petaflop Aspirations

The Moscow State University supercomputer, Lomonosov, has been selected for a high-performance makeover, with the goal of tripling its processing power to achieve petaflop-level performance in 2010. T-Platforms, who developed and manufactured the supercomputer, is the odds-on favorite to lead the project.
Read More...

Intel Ups Performance Ante with Westmere Server Chips

Right on schedule, Intel has launched its Xeon 5600 processors, codenamed "Westmere EP." The 5600 represents the 32nm sequel to the Xeon 5500 (Nehalem EP) for dual-socket servers. Intel is touting better performance and energy efficiency, along with new security features, as the big selling points of the new Xeons.
Read More...

Read more HPCwire features...

Top Headlines

Australia Commissions Cray Supercomputer

Mar 19 | OfficialWire | New super to support intelligence work Down Under. Read more...

Intel Partners See 'Easy' Upgrade Path With Xeon 5600 Chips

Mar 18 | ChannelWeb | Westmere parts already showing up in HPC machines. Read more...

AMD: OEMs primed for Opteron 6100s

Mar 17 | The Register | But what about the tier ones? Read more...

Arrival of the Desktop Supercomputer

Mar 17 | Cadalyst Magazine | A new generation of workstations is changing the nature of technical computing. Read more...

Scheduling HPC In The Cloud

Mar 17 | Linux Magazine | Latest iteration of Sun Grid Engine able to tap into Cloud. Read more...

Read more headlines...

Featured Whitepapers

Virtualization for Aggregation And The vSMP Architecture™

Jan 12 | | In-depth look at vSMP Foundation server virtualization technology, technical implementation, use cases and capabilities. The technical whitepaper provides an architectural overview and details on the three vSMP Foundation products: vSMP Foundation for SMP, vSMP Foundation for Cluster and vSMP Foundation for Cloud.

Copper Cable Technologies for High Performance Computing

Jan 18 | | This white paper discusses Gore’s copper cable assemblies, and how they continue to exceed the standards for providing reliable, cost-effective solutions for high-performance computer applications.

View the White Paper Library

Multimedia

Webcast: Virtualized Data Center Roundtable

Join this online panel discussion for live Q&A with leading industry experts, analysts, and end-users to discuss the latest innovations, best practices, barriers to implementation, and measurable benefits of server virtualization with a particular focus on today's real world solutions.

Webcast: Watch SC09 Birds of a Feather Video: Scalable Fault-Tolerant HPC Supercomputers

Learn about scalable fault-tolerant architectures and examples of energy efficient and scalable supercomputing clusters using dual QDR InfiniBand to combine capacity computing with network failover capabilities with the help of programming languages such as MPI and a robust Linux cluster management package.

Webcast: High Performance Computing for a Smarter Planet

LIVE@SCO9: The IBM team discusses new innovations in hardware, software and services that help clients better understand their workloads and get insight from their R&D efforts. Technology demonstrations include the soon-to-be-released Power7 HPC processor, the DCS990 system with 2.4 petabytes of storage, the xCAT management tool, secure HPC cloud computing and more. Winners of two HPCwire Readers' and Editors’ Choice Awards! Take the IBM virtual tour at SC09 or more information go online to: http://www-03.ibm.com/systems/deepcomputing/sc09.html