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A Distributed Campus Computing Model for MIT
By Paul AcostaPaul Acosta, Max Goncharov, Yutaro Iiyama, Bo Jayatilaka, Christoph Paus
The Virtual Computing Center
● Conceptually simple
– Users logon to virtual computing
center
– Setup their task
– Launch the task
– System distributes task to resources
as requested
– Work with the output
Campus
Resource A
Resource C
Resource B
Resource D
Virtual Center
The WorldThe World
Introduction Campus ComputingIntroduction Campus Computing
● Description of generic campus situation (ex. MIT)
– Large variety of research areas: engineering, maths, sciences, social
sciences ….
– Most need large computing at times and have some computing
resources
● some resources shared but not widely, usage not 100% for all of them
● no accurate inventory of all existing resources
– Most resources use some linux variant of similar versions
● Some Issues
– Researches have peak demands that exceed their resources
– Often though the resources are not fully used
– Account management is work intensive
Introduction Campus ComputingIntroduction Campus Computing ….continued….continued
The Virtual Computing CenterThe Virtual Computing Center
ConclusionConclusion
● The Virtual Computing Center
– Viable, pragmatic solution for generic campus computing
– Covers most use cases, but not all
– Allows maximal flexibility: all resources can be separately registered
and used, but also controlled by the owners
– Specific fully funtional prototype implemented using the Open Science
Grid (OSG) to connect to the 'outside world': HTCondor, bosco,
glideInWMS pilots
● What next?
– Some investment needed to establish infrastructure and support
– Users need to re-learn a little but win big
– Resource owners need to be convinced and have to adjust
– Need to find all resources on campus and connect them
● Why not have one big computing center?
– Could work, but it does/did not: ownership, funding, different
interests, management ….
– Existing resources would need to be moved
– Difficult to change Status Quo
● Requirements for a new model
– Minimally expensive: money and human resources
– Technically feasible and attractive for most research efforts
– Use all existing computing resources
– Leave computing resource owners maximal control
– Reach beyond campus as needed/wanted
● Pretending to be a big computing center
– Create a common login pool, big enough for tests
– Connect this pool to each campus computing resource
– Also connect to external resources: ex. OSG
● Resource Owner's/Administrator's perspective
– Access to the resources are granted through service accounts
– Service account submits in local flavor to the batch system and can
be managed: privileges/priorities etc.
– Typical service accounts:
● for resource owners (get full access
● for visitors from MIT (opportunistic access)
● for visitors from off-campus (opportunistic access, pre-emption), etc.
Prototype – Campus Computing
● Three campus resources connected (6 prototype users)
– T2 at Bates, T3 in B24, and EAPS at the Green Center in Holyoke
– Also seamlessly integrated the Open Science Grid (OSG) access
Prototype – OSG Impact
● Uses of the virtual computing center (Campus + OSG)
– About 1 million CPU hours per week for 31 weeks
– 19 M computing hours for cosmic particle simulations (AMS)
– 12 M computing hours for Dark Matter simulations in pp collisions (CMS)
Implementation Details
● How are jobs running?
– FrontEnd submits glideIn
pilots through BOSCO to the
various resources submit
nodes (local flavor)
– On subMIT user jobs get
submitted to a HTCondor
collector
– Physical workers are
matched at subMIT and pull
down their work
– subMIT becomes a huge
virtual resource, real work
is done at the physical
worker
– At completion output is
shipped as specified
EAPSEAPS
(Slurm)(Slurm)
HPRCFHPRCF
(HTCondor)(HTCondor)
CMS Tier3CMS Tier3
(HTCondor)(HTCondor)
Virtual HTCondor pool Collector
ssh
Physical Worker Node
Submit Node
HTCondor worker process
Campus
FrontEnd
subMIT

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Campus Computing Model

  • 1. A Distributed Campus Computing Model for MIT By Paul AcostaPaul Acosta, Max Goncharov, Yutaro Iiyama, Bo Jayatilaka, Christoph Paus The Virtual Computing Center ● Conceptually simple – Users logon to virtual computing center – Setup their task – Launch the task – System distributes task to resources as requested – Work with the output Campus Resource A Resource C Resource B Resource D Virtual Center The WorldThe World Introduction Campus ComputingIntroduction Campus Computing ● Description of generic campus situation (ex. MIT) – Large variety of research areas: engineering, maths, sciences, social sciences …. – Most need large computing at times and have some computing resources ● some resources shared but not widely, usage not 100% for all of them ● no accurate inventory of all existing resources – Most resources use some linux variant of similar versions ● Some Issues – Researches have peak demands that exceed their resources – Often though the resources are not fully used – Account management is work intensive Introduction Campus ComputingIntroduction Campus Computing ….continued….continued The Virtual Computing CenterThe Virtual Computing Center ConclusionConclusion ● The Virtual Computing Center – Viable, pragmatic solution for generic campus computing – Covers most use cases, but not all – Allows maximal flexibility: all resources can be separately registered and used, but also controlled by the owners – Specific fully funtional prototype implemented using the Open Science Grid (OSG) to connect to the 'outside world': HTCondor, bosco, glideInWMS pilots ● What next? – Some investment needed to establish infrastructure and support – Users need to re-learn a little but win big – Resource owners need to be convinced and have to adjust – Need to find all resources on campus and connect them ● Why not have one big computing center? – Could work, but it does/did not: ownership, funding, different interests, management …. – Existing resources would need to be moved – Difficult to change Status Quo ● Requirements for a new model – Minimally expensive: money and human resources – Technically feasible and attractive for most research efforts – Use all existing computing resources – Leave computing resource owners maximal control – Reach beyond campus as needed/wanted ● Pretending to be a big computing center – Create a common login pool, big enough for tests – Connect this pool to each campus computing resource – Also connect to external resources: ex. OSG ● Resource Owner's/Administrator's perspective – Access to the resources are granted through service accounts – Service account submits in local flavor to the batch system and can be managed: privileges/priorities etc. – Typical service accounts: ● for resource owners (get full access ● for visitors from MIT (opportunistic access) ● for visitors from off-campus (opportunistic access, pre-emption), etc. Prototype – Campus Computing ● Three campus resources connected (6 prototype users) – T2 at Bates, T3 in B24, and EAPS at the Green Center in Holyoke – Also seamlessly integrated the Open Science Grid (OSG) access Prototype – OSG Impact ● Uses of the virtual computing center (Campus + OSG) – About 1 million CPU hours per week for 31 weeks – 19 M computing hours for cosmic particle simulations (AMS) – 12 M computing hours for Dark Matter simulations in pp collisions (CMS) Implementation Details ● How are jobs running? – FrontEnd submits glideIn pilots through BOSCO to the various resources submit nodes (local flavor) – On subMIT user jobs get submitted to a HTCondor collector – Physical workers are matched at subMIT and pull down their work – subMIT becomes a huge virtual resource, real work is done at the physical worker – At completion output is shipped as specified EAPSEAPS (Slurm)(Slurm) HPRCFHPRCF (HTCondor)(HTCondor) CMS Tier3CMS Tier3 (HTCondor)(HTCondor) Virtual HTCondor pool Collector ssh Physical Worker Node Submit Node HTCondor worker process Campus FrontEnd subMIT