2021 Technical Program

Workshop Talk Records

Technical Program [7:00 AM - 1:00 PM PDT]

Workshop Opening [7:00 AM - 7:05 AM PDT]

• Workshop Opening and Welcome
  Walfredo Cirne, Gonzalo P. Rodrigo and Dalibor Klusáček

Technical Papers (session 1) [7:05 AM - 8:00 AM PDT]

• Measurement and Modeling of Performance of HPC Applications towards Overcommitting Scheduling Systems.
  Shohei Minami, Toshio Endo and Akihiro Nomura [presentation slides]
• Scheduling Microservice Containers on Large Core Machines through Placement and Coalescing.
  Vishal Rao, Vishnu Singh, Goutham K. S., Bharani Ujjaini Kempaiah, Ruben John Mampilli, Subramaniam Kalambur and Dinkar Sitaram [presentation slides]

Keynote Lecture [8:00 AM - 9:00 AM PDT]

• Resampling with Feedback — A New Paradigm of Using Workload Data for Performance Evaluation [View the talk online]
  Dror Feitelson (Hebrew University, Israel).
  
  Abstract: Reliable performance evaluations require representative workloads. This has led to the use of accounting logs from production systems as a source for workload data in simulations. I will survey 20 years of ups and downs in the use of workload logs, culminating with the idea of resampling with feedback. It all started with the realization that using workload logs directly suffers from various deficiencies, such as providing data about only one specific situation, and lack of flexibility, namely the inability to adjust the workload as needed. Creating workload models solves some of these problems but creates others, most notably the danger of missing out on important details that were not recognized in advance, and therefore not included in the model. Resampling solves many of these deficiencies by combining the best of both worlds. It is based on partitioning the workload data into basic components (e.g. the jobs contributed by different users), and then generating new workloads by sampling from this pool of basic components. This allows analysts to create multiple varied but related workloads from the same original log, all the time retaining much of the structure that exists in the original workload. However, resampling should not be applied in an oblivious manner. Rather, the generated workloads need to be adjusted dynamically to the conditions of the simulated system using a feedback loop. Resampling with feedback is therefore a new way to use workload logs which benefits from the realism of logs while eliminating many of their drawbacks. In addition, it enables evaluations of throughput effects that are impossible with static workloads.
  
  Biography: Dror Feitelson is a professor of Computer Science at the Hebrew University of Jerusalem, where he has been on the faculty of the Rachel and Selim Benin School of Computer Science and Engineering since 1995. His research emphasizes experimental techniques and real-world data in computer systems performance evaluation and in software engineering. He is a founding co-organizer of the JSSPP series of workshops, and established and maintained the Parallel Workloads Archive. His book on Workload Modeling was published by Cambridge University Press in 2015.

Technical & OSP Papers (session 2) [9:00 AM - 9:50 AM PDT]

• Collection of Job Scheduling Prediction Methods (Open Scheduling Problem).
  Mehmet Soysal and Achim Streit [presentation slides]
• Modular Workload Format: extending SWF for modular systems.
  Julita Corbalan and Marco D'Amico [presentation slides]

Coffee Break & Discussion [9:50 AM - 10:00 AM PDT]

Technical Papers (session 3) [10:00 AM - 11:30 AM PDT]

• Learning-based Approaches to Estimate Job Wait Time in HTC Datacenters.
  Luc Gombert and Frederic Suter [presentation slides]
• A HPC Co-Scheduler with Reinforcement Learning.
  Abel Souza, Kristiaan Pelckmans and Johan Tordsson [presentation slides]
• Performance-Cost Optimization of Moldable Scientific Workflows.
  Marta Jaros and Jiri Jaros [presentation slides]

Short Break [11:30 AM - 11:35 AM PDT]

Technical Papers (session 4) [11:35 AM - 1:00 PM PDT]

• Temperature-Aware Energy-Optimal Scheduling of Moldable Streaming Tasks onto 2D-Mesh-Based Many-Core CPUs with DVFS.
  Christoph Kessler, Jörg Keller and Sebastian Litzinger [presentation slides]
• Scheduling Challenges for Variable Capacity Resources.
  Chaojie Zhang and Andrew Chien [presentation slides]
• GLUME: A Strategy for Reducing Workflow Execution Times on Batch-Scheduled Platforms.
  Evan Hataishi, Pierre-Francois Dutot, Rafael Ferreira da Silva and Henri Casanova [presentation slides]