Anwesha Das


Post-Doctoral Scholar
The University of Chicago

Contact: anweshaa AT uchicago.edu

I am a Computer Science Post-Doc at UChicago.

My general research interests are in reliability and performance of systems.

Publications

  • Performance Variability and Causality in Complex Systems
    Anwesha Das, Daniel Ratner, and Alex Aiken. [ACSOS'22]   [PDF]  
  • [IEEE International Conference on Autonomic Computing and Self-Organizing Systems]

  • Systemic Assessment of Node Failures in Production HPC Platforms
    Anwesha Das, Frank Mueller, and Barry Rountree. [IPDPS'21, Acceptance Rate: 22.7%]   [PDF]  
  • [IEEE International Parallel and Distributed Processing Symposium]

  • Aarohi: Making Real-time Node Failure Prediction Feasible
    Anwesha Das, Frank Mueller, and Barry Rountree. [IPDPS'20, Acceptance Rate: 24.66%]   [PDF]  
  • [IEEE International Parallel and Distributed Processing Symposium]

  • Desh: Deep Learning for System Health Prediction of Lead Times to Failure in HPC
    Anwesha Das, Frank Mueller, Charles Siegel, and Abhinav Vishnu. [HPDC'18, Acceptance Rate: 19.64%]   [PDF]
  • [ACM High-Performance Parallel and Distributed Computing]

  • Doomsday: Predicting Which Node Will Fail When on Supercomputers
    Anwesha Das, Frank Mueller, Paul Hargrove, Eric Roman, and Scott Baden. [SC'18, Acceptance Rate: 23.6%]   [PDF]  
  • [ACM/IEEE The International Conference for High Performance Computing, Networking, Storage, and Analysis]

  • KeyValueServe: Design and Performance Analysis of a Multi-Tenant Data Grid as a Cloud Service
    Anwesha Das, Arun Iyengar, and Frank Mueller. [CCPE'18, Concurrency and Computation: Practice and Experience 2018]   [PDF]

  • Performance Analysis of a Multi-Tenant In-memory Data Grid
    Anwesha Das, Frank Mueller, Xiaohui Gu, and Arun Iyengar. [IEEE Cloud 2016]   [PDF]

  • Dynamic Resource Management using Virtual Machine Migrations
    Mayank Mishra, Anwesha Das, Purushottam Kulkarni, and Anirudha Sahoo. [IEEE Communications Magazine 2012]   [PDF]

Short Papers and Posters in Peer-Reviewed Conference Proceedings

  • Anomaly Detection in Accelerator Facilities Using Machine Learning
    Anwesha Das, Daniel Ratner, M. Borland, L. Emery, X. Huang, H. Shang, G. Shen, R. Smith, and G. Wang.
    [International Particle Accelerator Conference, IPAC'21]   [PDF]

  • Holistic Root Cause Analysis of Node Failures in Production HPC
    Anwesha Das, Frank Mueller
    [ ACM SRC at Supercomputing, SC'18]   [PDF] [Poster]

  • Aarohi: Efficient Online Failure Prediction
    Anwesha Das, Frank Mueller
    [ ACM SRC at Architectural Support for Programming Languages and Operating Systems, ASPLOS'18]   [PDF] [Poster]

  • Desh: Deep Learning for HPC System Health Resilience
    Anwesha Das, Abhinav Vishnu, Charles Siegel, Frank Mueller
    [Supercomputing, SC'17]   [PDF] [Poster]

  • Pin-Pointing Node Failures in HPC Systems
    Anwesha Das, Frank Mueller, Paul Hargrove, Eric Roman
    [Supercomputing, SC'16]   [PDF] [Poster]