An Application-Based Performance Characterization of the Columbia Supercluster

Biswas, Rupak; Djomehri, M. Jahed; Hood, Robert; Jin, Haoqiang; Kiris, Cetin C.; Saini, Subhash

doi:10.1109/sc.2005.11

Cited by 21 publications

(15 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Much work has been put into the evaluation of novel supercomputers [27], [29], [30], [31], [47], [48] and nontraditional systems [5], [32], [37], [49], [70] for scientific computing. We share much of the used methodology with previous work; we see this as an advantage in that our results are readily comparable with existing results.…”

Section: Related Workmentioning

confidence: 99%

Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing

Iosup

Ostermann

Yigitbasi

et al. 2011

IEEE Trans. Parallel Distrib. Syst.

734

368

View full text Add to dashboard Cite

Performance analysis of cloud computing services for many-tasks scientific computingIosup Document VersionPublisher's PDF, also known as Version of Record (includes final page, issue and volume numbers)Please check the document version of this publication:• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Abstract-Cloud computing is an emerging commercial infrastructure paradigm that promises to eliminate the need for maintaining expensive computing facilities by companies and institutes alike. Through the use of virtualization and resource time sharing, clouds serve with a single set of physical resources a large user base with different needs. Thus, clouds have the potential to provide to their owners the benefits of an economy of scale and, at the same time, become an alternative for scientists to clusters, grids, and parallel production environments. However, the current commercial clouds have been built to support web and small database workloads, which are very different from typical scientific computing workloads. Moreover, the use of virtualization and resource time sharing may introduce significant performance penalties for the demanding scientific computing workloads. In this work, we analyze the performance of cloud computing services for scientific computing workloads. We quantify the presence in real scientific computing workloads of Many-Task Computing (MTC) users, that is, of users who employ loosely coupled applications comprising many tasks to achieve their scientific goals. Then, we perform an empirical evaluation of the performance of four commercial cloud computing services including Amazon EC2, which is currently the largest commercial cloud. Last, we compare through tra...

show abstract

Section: Related Workmentioning

confidence: 99%

Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing

Iosup

Ostermann

Yigitbasi

et al. 2011

IEEE Trans. Parallel Distrib. Syst.

734

368

View full text Add to dashboard Cite

show abstract

“…Depending of its main objective, the corresponding performance analysis focuses on the hardware system, on the application to be executed, or both. For example, the performance of the Columbia cluster has been evaluated [26]. The results obtained from this study demonstrate that several features concerning configurations have a direct impact on the overall system performance for the same application.…”

Section: Related Workmentioning

confidence: 95%

A formal framework to analyze cost and performance in Map-Reduce based applications

Núñez

Merayo

2014

Journal of Computational Science

View full text Add to dashboard Cite

“…The computations were performed with the CFD flow solver OVERFLOW, version 2.1ae on NASA Ames Columbia 18,19 and Pleiades 20 supercomputers. OVERFLOW is a viscous compressible code developed by NASA, which solves the time-dependent RANS equations using structured overset 21 grids.…”

Section: Computational Approachmentioning

confidence: 99%

CFD Assessment of Forward Booster Separation Motor Ignition Overpressure on ET XT 718 Ice/Frost Ramp

Tejnil¹,

Rogers

2012

50th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition

View full text Add to dashboard Cite

Computational fluid dynamics assessment of the forward booster separation motor ignition over-pressure was performed on the space shuttle external tank X T 718 ice/frost ramp using the flow solver OVERFLOW. The main objective of this study was the investigation of the over-pressure during solid rocket booster separation and its affect on the local pressure and air-load environments. Delta pressure and plume impingement were investigated as a possible contributing factor to the cause of the debris loss on shuttle missions STS-125 and STS-127. A simplified computational model of the Space Shuttle Launch Vehicle was developed consisting of just the external tank and the solid rocket boosters with separation motor nozzles and plumes. The simplified model was validated by comparison to full fidelity computational model of the Space Shuttle without the separation motors. Quasi steady-state plume solutions were used to calibrate the thrust of the separation motors. Time-accurate simulations of the firing of the booster-separation motors were performed. Parametric studies of the time-step size and the number of sub-iterations were used to find the best converged solution. The computed solutions were compared to previous OVERFLOW steady-state runs of the separation motors with reaction control system jets and to ground test data. The results indicated that delta pressure from the overpressure was small and within design limits, and thus was unlikely to have contributed to the foam losses. NomenclatureA t /A i = nozzle throat to inlet area ratio = angle of attack = angle of side slip P = difference in pressure P max = maximum difference in pressure t = dimensional physical time step T = dimensional simulation time step DT = computational time step DTPHYS = physical time step = circumferential coordinate of the tank = specific heat ratio ITIME = time-step scaling option L ref = reference length MW = molecular weight NITNWT = number of Newton/dual-time sub-iterations P = pressure P 0 = nozzle inlet total pressure P = free-stream pressure

show abstract

An Application-Based Performance Characterization of the Columbia Supercluster

Cited by 21 publications

References 14 publications

Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing

Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing

A formal framework to analyze cost and performance in Map-Reduce based applications

CFD Assessment of Forward Booster Separation Motor Ignition Overpressure on ET XT 718 Ice/Frost Ramp

Contact Info

Product

Resources

About