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Alexandru Iosup | Alexandru Uta | Valeriu Codreanu | Damian Podareanu | Laurens Versluis | Mehmet Cetin | Caspar Greeven | Kristian Laursen | V. Codreanu | Damian Podareanu | A. Iosup | M. Cetin | K. Laursen | Alexandru Uta | L. Versluis | Caspar Greeven | Kristian B. Laursen | M. Çetin
[1] W. Allcock,et al. Job Characteristics on Large-Scale Systems: Long-Term Analysis, Quantification, and Implications , 2020, SC20: International Conference for High Performance Computing, Networking, Storage and Analysis.
[2] Valeriu Codreanu,et al. DDLBench: Towards a Scalable Benchmarking Infrastructure for Distributed Deep Learning , 2020, 2020 IEEE/ACM Fourth Workshop on Deep Learning on Supercomputers (DLS).
[3] Ewa Deelman,et al. WorkflowHub: Community Framework for Enabling Scientific Workflow Research and Development , 2020, 2020 IEEE/ACM Workflows in Support of Large-Scale Science (WORKS).
[4] Tirthak Patel,et al. What does Power Consumption Behavior of HPC Jobs Reveal? : Demystifying, Quantifying, and Predicting Power Consumption Characteristics , 2020, 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS).
[5] Mor Harchol-Balter,et al. Borg: the next generation , 2020, EuroSys.
[6] Ricardo Bianchini,et al. Serverless in the Wild: Characterizing and Optimizing the Serverless Workload at a Large Cloud Provider , 2020, USENIX Annual Technical Conference.
[7] Eric Masanet,et al. Recalibrating global data center energy-use estimates , 2020, Science.
[8] Alexandru Iosup,et al. Is Big Data Performance Reproducible in Modern Cloud Networks? , 2019, NSDI.
[9] M. Schulz,et al. DCDB Wintermute: Enabling Online and Holistic Operational Data Analytics on HPC Systems , 2019, HPDC.
[10] Alexandru Iosup,et al. The Workflow Trace Archive: Open-Access Data From Public and Private Computing Infrastructures , 2019, IEEE Transactions on Parallel and Distributed Systems.
[11] Alexandru Iosup,et al. Beneath the SURFace: An MRI-like View into the Life of a 21st-Century Datacenter , 2020, login Usenix Mag..
[12] Akbar Siami Namin,et al. The Performance of LSTM and BiLSTM in Forecasting Time Series , 2019, 2019 IEEE International Conference on Big Data (Big Data).
[13] Norman Bourassa,et al. Operational Data Analytics: Optimizing the National Energy Research Scientific Computing Center Cooling Systems , 2019, ICPP Workshops.
[14] Florina M. Ciorba,et al. Anomaly Detection in High Performance Computers: A Vicinity Perspective , 2019, 2019 18th International Symposium on Parallel and Distributed Computing (ISPDC).
[15] Wencong Xiao,et al. Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads , 2019, USENIX Annual Technical Conference.
[16] Michael M. Swift,et al. Your Programmable NIC Should be a Programmable Switch , 2018, HotNets.
[17] Shane Snyder,et al. A Year in the Life of a Parallel File System , 2018, SC18: International Conference for High Performance Computing, Networking, Storage and Analysis.
[18] Alexandru Iosup,et al. A Reference Architecture for Datacenter Scheduling: Design, Validation, and Experiments , 2018, SC18: International Conference for High Performance Computing, Networking, Storage and Analysis.
[19] Robert Ricci,et al. Taming Performance Variability , 2018, OSDI.
[20] Gregory R. Ganger,et al. On the diversity of cluster workloads and its impact on research results , 2018, USENIX Annual Technical Conference.
[21] Xiao Feng,et al. Comparison and evaluation of air cooling and water cooling in resource consumption and economic performance , 2018, Energy.
[22] John K. Ousterhout. Always measure one level deeper , 2018, Commun. ACM.
[23] Christian Haas,et al. Predicting Amazon Spot Prices with LSTM Networks , 2018, ScienceCloud@HPDC.
[24] David A. Patterson,et al. Motivation for and Evaluation of the First Tensor Processing Unit , 2018, IEEE Micro.
[25] Christa Boer,et al. Correlation Coefficients: Appropriate Use and Interpretation , 2018, Anesthesia and analgesia.
[26] Tian Li,et al. Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads , 2017, Proc. VLDB Endow..
[27] Robert B. Ross,et al. Fail-Slow at Scale: Evidence of Hardware Performance Faults in Large Production Systems , 2018, FAST.
[28] Devesh Tiwari,et al. GUIDE: A Scalable Information Directory Service to Collect, Federate, and Analyze Logs for Operational Insights into a Leadership HPC Facility , 2017, SC17: International Conference for High Performance Computing, Networking, Storage and Analysis.
[29] Andrea Rosà,et al. Failure Analysis and Prediction for Big-Data Systems , 2017, IEEE Transactions on Services Computing.
[30] Ricardo Bianchini,et al. Resource Central: Understanding and Predicting Workloads for Improved Resource Management in Large Cloud Platforms , 2017, SOSP.
[31] Claudia Canali,et al. Identifying Communication Patterns between Virtual Machines in Software-Defined Data Centers , 2017, PERV.
[32] Kang G. Shin,et al. Efficient Memory Disaggregation with Infiniswap , 2017, NSDI.
[33] Yu Luo,et al. Non-Intrusive Performance Profiling for Entire Software Stacks Based on the Flow Reconstruction Principle , 2016, OSDI.
[34] Chunming Rong,et al. Using Spearman's correlation coefficients for exploratory data analysis on big dataset , 2015, Concurr. Comput. Pract. Exp..
[35] Alexandru Uta,et al. Towards Resource Disaggregation — Memory Scavenging for Scientific Workloads , 2016, 2016 IEEE International Conference on Cluster Computing (CLUSTER).
[36] Erik Schultes,et al. The FAIR Guiding Principles for scientific data management and stewardship , 2016, Scientific Data.
[37] Yonggang Wen,et al. Data Center Energy Consumption Modeling: A Survey , 2016, IEEE Communications Surveys & Tutorials.
[38] Erik Elmroth,et al. Performance Anomaly Detection and Bottleneck Identification , 2015, ACM Comput. Surv..
[39] Andrea Rosà,et al. Predicting and Mitigating Jobs Failures in Big Data Clusters , 2015, 2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing.
[40] Alexandru Iosup,et al. Statistical Characterization of Business-Critical Workloads Hosted in Cloud Datacenters , 2015, 2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing.
[41] Abhishek Verma,et al. Large-scale cluster management at Google with Borg , 2015, EuroSys.
[42] Ewa Deelman,et al. Community Resources for Enabling Research in Distributed Scientific Workflows , 2014, 2014 IEEE 10th International Conference on e-Science.
[43] Dan Tsafrir,et al. Experience with using the Parallel Workloads Archive , 2014, J. Parallel Distributed Comput..
[44] Calton Pu,et al. vPerfGuard: an automated model-driven framework for application performance diagnosis in consolidated cloud environments , 2013, ICPE '13.
[45] David Atienza,et al. Correlation-aware virtual machine allocation for energy-efficient datacenters , 2013, 2013 Design, Automation & Test in Europe Conference & Exhibition (DATE).
[46] Evgenia Smirni,et al. Data Centers in the Cloud: A Large Scale Performance Study , 2012, 2012 IEEE Fifth International Conference on Cloud Computing.
[47] Roy H. Campbell,et al. Two Sides of a Coin: Optimizing the Schedule of MapReduce Jobs to Minimize Their Makespan and Improve Cluster Performance , 2012, 2012 IEEE 20th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems.
[48] Bianca Schroeder,et al. Temperature management in data centers: why some (might) like it hot , 2012, SIGMETRICS '12.
[49] Eric Bouwers,et al. Getting What You Measure , 2012, Commun. ACM.
[50] Jordi Torres,et al. GreenSlot: Scheduling energy consumption in green datacenters , 2011, 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC).
[51] Fang Liu,et al. NIST Cloud Computing Reference Architecture , 2011, 2011 IEEE World Congress on Services.
[52] Benjamin Hindman,et al. Dominant Resource Fairness: Fair Allocation of Multiple Resource Types , 2011, NSDI.
[53] Hong Liu,et al. Fiber optic communication technologies: What's needed for datacenter network operations , 2010, IEEE Communications Magazine.
[54] Yasushi Inoguchi,et al. Performance evaluation of a Green Scheduling Algorithm for energy savings in Cloud computing , 2010, 2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW).
[55] Donald Beaver,et al. Dapper, a Large-Scale Distributed Systems Tracing Infrastructure , 2010 .
[56] Iosif Legrand,et al. Monitoring and control of large systems with MonALISA , 2009, CACM.
[57] Sally A. McKee,et al. Machine learning based online performance prediction for runtime parallelization and task scheduling , 2009, 2009 IEEE International Symposium on Performance Analysis of Systems and Software.
[58] Alexandru Iosup,et al. The Grid Workloads Archive , 2008, Future Gener. Comput. Syst..
[59] Robert D. van der Mei,et al. A prediction method for job runtimes on shared processors: Survey, statistical analysis and new avenues , 2007, Perform. Evaluation.
[60] Douglas Thain,et al. Distributed computing in practice: the Condor experience , 2005, Concurr. Pract. Exp..
[61] Richard Wolski,et al. Multivariate Resource Performance Forecasting in the Network Weather Service , 2002, ACM/IEEE SC 2002 Conference (SC'02).
[62] Warren Smith,et al. Benchmarks and Standards for the Evaluation of Parallel Job Schedulers , 1999, JSSPP.