Monday, 2017-06-12

Workshop Discussion

In addition to discussing the presented papers (see program and ACM digital library), we had breakout group discussions on

  • SPE Challenges for Embedded Systems (notes)
  • SPE Challenges in Cloud Computing (notes)
  • DevOps Performance (notes)

Overall, we discussed several issues listed in the following

  • performance aware software migration: How should a performance model be evolved/calibrated so that it can predict a software's performance on a newer hardware/OS/virtualization platform?  Typically no measurement data is available for that software from the newer system although there might be some standard benchmark data available.
  • SPE for cloud-based applications: How should SPE be adapted to fit with a world where applications are deployed on cloud systems, which typically deliver highly variable performance.
  • What challenges does Big Data bring to SPE? How to make Data a first-class citizen in performance modelling and prediction?
  • Trends like DevOps are giving to the developer greater control over the runtime environment. What's the baseline of SPE in supporting the runtime and what challenges lie ahead?
  • Software is increasingly asked to control the physical world (e.g., cyber-phsyical systems). What are the challenges and limitations of SPE in this area?
  • indoctrinating stakeholders in a performance-oriented mindset
  • characterizing performance requirements for heterogeneous and time-varying workloads
  • software performance challenges for systems with many components that communicate with one another, as well as with a central server (such as embedded systems that send their status to and are controlled by a control station)
  • new challenges in new kinds of software, of development, of service delivery (examples, problems raised)
  • process challenges that still need to be solved (e.g. how to derive models efficiently)
  • new opportunities in new analysis capabilities? new kinds of models?