Anwesha Das

Das, A., Mueller, F., & Rountree, B. (2021). Systemic Assessment of Node Failures in HPC Production Platforms. 2021 IEEE 35TH INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM (IPDPS), pp. 267–276. https://doi.org/10.1109/IPDPS49936.2021.00035

Das, A., Mueller, F., & Rountree, B. (2020). Aarohi: Making Real-Time Node Failure Prediction Feasible. 2020 IEEE 34TH INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM IPDPS 2020, pp. 1092–1101. https://doi.org/10.1109/IPDPS47924.2020.00115

Das, A., Mueller, F., Siegel, C., & Vishnu, A. (2018). Desh: Deep Learning for System Health Prediction of Lead Times to Failure in HPC. HPDC '18: PROCEEDINGS OF THE 27TH INTERNATIONAL SYMPOSIUM ON HIGH-PERFORMANCE PARALLEL AND DISTRIBUTED COMPUTING, pp. 40–51. https://doi.org/10.1145/3208040.3208051

Das, A., Iyengar, A., & Mueller, F. (2018). KeyValueServe(dagger): Design and performance analysis of a multi-tenant data grid as a cloud service. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 30(14). https://doi.org/10.1002/cpe.4424

Das, A., Mueller, F., Gu, X. H., & Iyengar, A. (2016). Performance analysis of a multi-tenant in-memory data grid. Proceedings of 2016 ieee 9th international conference on cloud computing (cloud), 956–959. https://doi.org/10.1109/cloud.2016.0144