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ALOJA-ML

Josep Lluís Berral, Nicolas Poggi, David Carrera, Aaron Call, Rob Reinauer, Daron Green
2015 Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '15  
This article presents ALOJA-Machine Learning (ALOJA-ML) an extension to the ALOJA project that uses machine learning techniques to interpret Hadoop benchmark performance data and performance tuning; here we detail the approach, efficacy of the model and initial results. Hadoop presents a complex execution environment, where costs and performance depends on a large number of software (SW) configurations and on multiple hardware (HW) deployment choices. These results are accompanied by a test bed
more » ... and tools to deploy and evaluate the cost-effectiveness of the different hardware configurations, parameter tunings, and Cloud services. Despite early success within ALOJA from expert-guided benchmarking, it became clear that a genuinely comprehensive study requires automation of modeling procedures to allow a systematic analysis of large and resource-constrained search spaces. ALOJA-ML provides such an automated system allowing knowledge discovery by modeling Hadoop executions from observed benchmarks across a broad set of configuration parameters. The resulting performance models can be used to forecast execution behavior of various workloads; they allow 'a-priori' prediction of the execution times for new configurations and HW choices and they offer a route to model-based anomaly detection. In addition, these models can guide the benchmarking exploration efficiently, by automatically prioritizing candidate future benchmark tests. Insights from ALOJA-ML's models can be used to reduce the operational time on clusters, speed-up the data acquisition and knowledge discovery process, and importantly, reduce running costs. In addition to learning from the methodology presented in this work, the community can benefit in general from ALOJA data-sets, framework, and derived insights to improve the design and deployment of Big Data applications.
doi:10.1145/2783258.2788600 dblp:conf/kdd/BerralPCCRG15 fatcat:3y7pnkbwxvbzjodjfwhm4ckjla

ALOJA: A Framework for Benchmarking and Predictive Analytics in Hadoop Deployments

Josep Lluis Berral, Nicolas Poggi, David Carrera, Aaron Call, Rob Reinauer, Daron Green
2017 IEEE Transactions on Emerging Topics in Computing  
This article presents the ALOJA project and its analytics tools, which leverages machine learning to interpret Big Data benchmark performance data and tuning. ALOJA is part of a long-term collaboration between BSC and Microsoft to automate the characterization of cost-effectiveness on Big Data deployments, currently focusing on Hadoop. Hadoop presents a complex run-time environment, where costs and performance depend on a large number of configuration choices. The ALOJA project has created an
more » ... en, vendor-neutral repository, featuring over 40,000 Hadoop job executions and their performance details. The repository is accompanied by a test-bed and tools to deploy and evaluate the cost-effectiveness of different hardware configurations, parameters and Cloud services. Despite early success within ALOJA, a comprehensive study requires automation of modeling procedures to allow an analysis of large and resource-constrained search spaces. The predictive analytics extension, ALOJA-ML, provides an automated system allowing knowledge discovery by modeling environments from observed executions. The resulting models can forecast execution behaviors, predicting execution times for new configurations and hardware choices. That also enables model-based anomaly detection or efficient benchmark guidance by prioritizing executions. In addition, the community can benefit from ALOJA data-sets and framework to improve the design and deployment of Big Data applications.
doi:10.1109/tetc.2015.2496504 fatcat:7kpa5wvwfzfs3jtd6aqjfbq5du

ALOJA: A systematic study of Hadoop deployment variables to enable automated characterization of cost-effectiveness

Nicolas Poggi, David Carrera, Aaron Call, Sergio Mendoza, Yolanda Becerra, Jordi Torres, Eduard Ayguade, Fabrizio Gagliardi, Jesus Labarta, Rob Reinauer, Nikola Vujic, Daron Green (+1 others)
2014 2014 IEEE International Conference on Big Data (Big Data)  
This article presents the ALOJA project, an initiative to produce mechanisms for an automated characterization of cost-effectiveness of Hadoop deployments and reports its initial results. ALOJA is the latest phase of a long-term collaborative engagement between BSC and Microsoft which, over the past 6 years has explored a range of different aspects of computing systems, software technologies and performance profiling. While during the last 5 years, Hadoop has become the de-facto platform for
more » ... Data deployments, still little is understood of how the different layers of the software and hardware deployment options affects its performance. Early ALOJA results show that Hadoop's runtime performance, and therefore its price, are critically affected by relatively simple software and hardware configuration choices e.g., number of mappers, compression, or volume configuration. Project ALOJA presents a vendor-neutral repository featuring over 5000 Hadoop runs, a test bed, and tools to evaluate the cost-effectiveness of different hardware, parameter tuning, and Cloud services for Hadoop. As few organizations have the time or performance profiling expertise, we expect our growing repository will benefit Hadoop customers to meet their Big Data application needs. ALOJA seeks to provide both knowledge and an online service to with which users make better informed configuration choices for their Hadoop compute infrastructure whether this be on-premise or cloud-based. The initial version of ALOJA's Web application and sources are available at http://hadoop.bsc.es
doi:10.1109/bigdata.2014.7004322 dblp:conf/bigdataconf/PoggiCCMBTAGLRVGB14 fatcat:mwznaa3urrcplbsmssebw2ppii

Page 3408 of The Journal of Neuroscience Vol. 20, Issue 9 [page]

2000 The Journal of Neuroscience  
We thank Kristina Schlegel for artwork, and Ying Lu and Rob Reinauer for fish care. Correspondence should be sent to Dr. M. Lynne McAnelly at the above address. E-mail: |.mcanelly@mail.utexas.edu.  ... 

Evolution and divergence of sodium channel genes in vertebrates

G. F. Lopreato, Y. Lu, A. Southwell, N. S. Atkinson, D. M. Hillis, T. P. Wilcox, H. H. Zakon
2001 Proceedings of the National Academy of Sciences of the United States of America  
We thank Gwen Gage and Katie Kendall for artwork, Jason Rall for help with the PCR, Rob Reinauer for fish care, and Klaus Linse at the Institute for Cellular and Molecular Biology Core Facility for sequencing  ... 
doi:10.1073/pnas.131171798 pmid:11416226 pmcid:PMC34712 fatcat:ppv5gkpt2vgwxj55umvj32cspq

Dialogue Term Extraction using Transfer Learning and Topological Data Analysis [article]

Renato Vukovic, Michael Heck, Benjamin Matthias Ruppik, Carel van Niekerk, Marcus Zibrowius, Milica Gasic
2022 Zenodo  
Fur-ther, persistence images (subsection 4.3) could be replaced by features tailored to downstream tasks, such as features obtained from the novel Persformer model (Reinauer et al., 2021) .  ...  , … , 𝑤 $ Tokenizer 𝑡 " , … , 𝑡 ' , … , 𝑡 & "𝑂", "𝐵", "𝐼", "𝑂", "𝐵", "𝑂" Upscaling layer Downscaling layer Convolutional layer Concatenation (b) MLM model (subsection 4.2) Transformer RoB  ... 
doi:10.5281/zenodo.6858565 fatcat:rjkn7pidajgmrlhqe2b6irf4t4

Moving forward? [chapter]

Joni Karjalainen, Rob Byrne
2021 Building Innovation Capabilities for Sustainable Industrialisation  
., 2015) , and in Thailand (Reinauer, 2019) , amongst others.  ... 
doi:10.4324/9781003054665-9 fatcat:5eifekokn5ffvj2676atg5ifwi

Great air base to host delegates

1959 National Civic Review  
Franklin Reinauer II it is possible to agree despite a diversity in their observations on the variable pleasures of public service. Mr.  ...  By Rob- ert K. Carr, Marver H. Bernstein, Don- ald H. Morrison and Joseph E. McLean. New York, Rinehart & Company, 1959. xxx, 1024 pp. $7.25. Disaster CONVERGENCE BEHAVIOR IN DISASTERS.  ... 
doi:10.1002/ncr.4100480802 fatcat:koun53smvfgf5hqretuoszh3lu

The Schulze Method of Voting [article]

Markus Schulze
2022 arXiv   pre-print
Acknowledgments I want to thank Lowell Bruce Anderson, Blake Cretney, James Green-Armytage, Jobst Heitzig, Ross Hyman, Aleksei Kondratev, Rob Lanphier, Rob LeGrand, Andrew Myers, Norman Petry, Nic Tideman  ...  03.001: Michels, Martina 03.002: Wolf, Udo 03.003: Matuschek, Jutta 03.004: Zillich, Steffen 03.005: İzgin, Figen 03.006: Günther, Andreas 03.007: Vordenbäumen, Vera 03.008: Krüger, Wolfgang 03.009: Reinauer  ...  03.001: Michels, Martina 03.002: Wolf, Udo 03.003: Matuschek, Jutta 03.004: Zillich, Steffen 03.005: İzgin, Figen 03.006: Günther, Andreas 03.007: Vordenbäumen, Vera 03.008: Krüger, Wolfgang 03.009: Reinauer  ... 
arXiv:1804.02973v11 fatcat:ychf6pfp5nevxovjmqmrng2rmu

Vermittlung von Gesprächsführung im Medizinstudium – Haltungs- oder technikorientiert

O Martin, K Rockenbauch, Y Stöbel-Richter
2011 Das Gesundheitswesen  
Int J Med Rob. 2004;1(1):36-42. DOI: 10.1002/rcs.4 7. Kabanza F, Bisson G, Charneau A, Jang TS. Implementing tutoring strategies into a patient simulator for clinical reasoning learning.  ...  Bitte zitieren als: Schürer C, Heitzmann N, Borucki K, Adler D, Illigen D, Schwarz P, Spannagl M, Reinauer H, Fischer MR. Virtuelle Ringversuche in der Labormedizin -ein Pilotprojekt.  ... 
doi:10.1055/s-0031-1283540 fatcat:tyiqyp57lbc2jiwcxoyzrzptvy

Das Gesprächsführungspraktikum im 2. Studienjahr des Modellstudiengangs HannibaL: Eine Evaluation mittels Selbsteinschätzungen der Studierenden

T von Lengerke, A Kursch, K Lange
2011 Das Gesundheitswesen  
Int J Med Rob. 2004;1(1):36-42. DOI: 10.1002/rcs.4 7. Kabanza F, Bisson G, Charneau A, Jang TS. Implementing tutoring strategies into a patient simulator for clinical reasoning learning.  ...  Bitte zitieren als: Schürer C, Heitzmann N, Borucki K, Adler D, Illigen D, Schwarz P, Spannagl M, Reinauer H, Fischer MR. Virtuelle Ringversuche in der Labormedizin -ein Pilotprojekt.  ... 
doi:10.1055/s-0031-1283667 fatcat:xte35uepfzcklo3cge63dphka4

25th Congress of the German Nephrology Society

1995 Kidney International  
Rob, K Sac/c and R. Nobilin,g Universities of Lübeck and Heidelbeig, Lflbeck and Heidelberg, Germany.  ...  Reinauer, and B. Grabensee, Department of Nephrology, Institute for Clinical Chemistry and Laboratory Diagnostics, Heinrich-Heine-University of Düsseldorf Düsseldorf Germany.  ... 
doi:10.1038/ki.1995.142 fatcat:j5mfdjgmhvdovnsx4b2w7oogii