Computational capabilities and data are critical to science. Scientists run models and data analyses on large-scale systems including clusters and supercomputers. These systems are complex to use, and users have to learn the software, policies, and associated ecosystems.
Performance, the quantum of work performed in unit time by a system, is an important metric used in the high performance computing (HPC) community. It is a measure of system productivity and does
not measure the productivity of the scientist or of the entire socio-technical system.
We posit that there is a need in this community for a process that goes beyond capturing system productivity and captures the trade-offs in the socio-technical system. The ultimate goal would be
to identify a metric or set of metrics that captures the productivity of the socio-technical system. In previous work, we considered temporal rhythms of scientific work and identified collective time as an important consideration within the HPC socio-technical system. Capturing the different dimensions of productivity will require deeper analyses, and our intent is to start with the time dimension in a quantified workplace for computational science.
We believe the HPC community will benefit from a hybrid process that includes traditional user research and ethnographic qualitative techniques in conjunction with system techniques of log and workload analyses. We will discuss our ideas to date on the hybrid process to derive insights into a productivity metric at the Quantified Workplace Workshop at CSCW.
Performance, the quantum of work performed in unit time by a system, is an important metric used in the high performance computing (HPC) community. It is a measure of system productivity and does
not measure the productivity of the scientist or of the entire socio-technical system.
We posit that there is a need in this community for a process that goes beyond capturing system productivity and captures the trade-offs in the socio-technical system. The ultimate goal would be
to identify a metric or set of metrics that captures the productivity of the socio-technical system. In previous work, we considered temporal rhythms of scientific work and identified collective time as an important consideration within the HPC socio-technical system. Capturing the different dimensions of productivity will require deeper analyses, and our intent is to start with the time dimension in a quantified workplace for computational science.
We believe the HPC community will benefit from a hybrid process that includes traditional user research and ethnographic qualitative techniques in conjunction with system techniques of log and workload analyses. We will discuss our ideas to date on the hybrid process to derive insights into a productivity metric at the Quantified Workplace Workshop at CSCW.
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