Presentation
XALT and Related Technologies: Job-Level Usage Data on Today's Supercomputers
BoF Organizer/Speaker
Event Type
Birds of a Feather
HPC Centre Planning and Operations
HPC workflows
Reproducibility
TimeMonday, June 25th2pm - 3pm
LocationPikkolo
Descriptionet's continue talking about real, high value supercomputer analytics
at the level of each individual job. We’re interested in what users
are actually doing: everything from which applications, libraries, and
individual functions are in demand, to preventing the problems that
get in the way of successful computational research. Moreover, we want
to do this for every single job running on our systems. And this year
we’re especially interested in some of the next great challenges,
including (1) understanding the needs of formerly non-traditional
research communities that comprise half the user community and whose
non-MPI workflows consume more than a third of the computing cycles;
(2) putting usage data in the hands of end users interested in records
of their own job-level activity to facilitate, for example,
reproducible research. Among the emerging needs: tracking individual
Python packages and similar usage within other frameworks like R and
MATLAB.
XALT (xalt.readthedocs.org) is a battle-tested tool focused on
job-level usage data; it enjoys a well-documented history of helping
administrators, support staff, and decision makers manage and improve
their operations. The small but growing list of centers that run XALT
includes NCSA, UK NCC, KAUST, NICS, the University of Utah, and
TACC. Version 2.0 is now ready to begin tracking non-MPI
workflows. Join us a far-ranging discussion that will begin with an
overview of new XALT capabilities before it ventures into broader
strategic and technical issues related to job-level activity
tracking.
at the level of each individual job. We’re interested in what users
are actually doing: everything from which applications, libraries, and
individual functions are in demand, to preventing the problems that
get in the way of successful computational research. Moreover, we want
to do this for every single job running on our systems. And this year
we’re especially interested in some of the next great challenges,
including (1) understanding the needs of formerly non-traditional
research communities that comprise half the user community and whose
non-MPI workflows consume more than a third of the computing cycles;
(2) putting usage data in the hands of end users interested in records
of their own job-level activity to facilitate, for example,
reproducible research. Among the emerging needs: tracking individual
Python packages and similar usage within other frameworks like R and
MATLAB.
XALT (xalt.readthedocs.org) is a battle-tested tool focused on
job-level usage data; it enjoys a well-documented history of helping
administrators, support staff, and decision makers manage and improve
their operations. The small but growing list of centers that run XALT
includes NCSA, UK NCC, KAUST, NICS, the University of Utah, and
TACC. Version 2.0 is now ready to begin tracking non-MPI
workflows. Join us a far-ranging discussion that will begin with an
overview of new XALT capabilities before it ventures into broader
strategic and technical issues related to job-level activity
tracking.
BoF Organizer/Speaker
