LARK Bringing Distributed High Throughput Computing to the Network Todd Tannenbaum U of Wisconsin-Madison Garhan Attebury

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Presentation transcript:

LARK Bringing Distributed High Throughput Computing to the Network Todd Tannenbaum U of Wisconsin-Madison Garhan Attebury U of Nebraska-Lincoln

What is Lark? NSF-funded project to take first steps at bridging DHTC and the network layer Collaboration between UNL and UW-Madison Develop software for network interaction by leveraging recent advances in SDN and the Linux Kernel Integrate these advances into HTCondor Some Lark Goals… 2

One example application… At UW-Madison, we want network traffic to pass thru border firewalls. But… thousands of HTCondor jobs running on large campus compute clusters can overwhelm firewalls. Policy: Would like network traffic for trusted compute jobs that need to move a lot of data to bypass firewalls 3

Demonstration Goal: Demonstrate HTCondor programming a unique network path per job How: 1.HTCondor creates a per-job network device 2.Locks the user’s application to this device 3.Communicates with Cisco ONE controller to define a path based on metadata associated with the job 4

Todd bravely (foolishly?) gambles with Murphy’s Law by performing a brief live demonstration 5

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Besides SDN integration, what are the other Lark goals and activities? 11 Networking accounting Network policies DYNES integration perfSONAR integration IPv6 and network testbed

Network accounting Traditionally CPU hours are primary metric for academic clusters Networking not always free (EC2, non I2) More data, bigger data Interface per job allows detailed and accurate network network accounting 12

Network policies A few options… – My job requires no inbound connectivity (NAT) – My job needs full connectivity / public IP (Bridge) – My job requires port X for ObscureLicenseServer™ – My job is part of a special workflow (VLANs) Security policies 13

DYNES integration DYNES (Dynamic Network System) allocates, schedules, and prioritizes channels to provide bandwidth reservation to data flows API interface allows scheduler to reserve ‘dedicated’ path for workflows 14 “Bridging DHTC and the network layer”

perfSONAR integration perfSONAR publishes what it measures Collect statistical information (bandwidth, availability, etc…) into ClassAds Example: Using information from perfSONAR, Condor can determine expected bandwidth to a remote site and limit a workflow to match 15

IPv6 and Network Testbed Condor has (some) IPv6 support already, needs thorough testing Testbeds at both UW and UNL 16

Project status Per job namespaces: – IPv4 (NAT + bridging) – OpenFlow rules perfSONAR: – pS metrics in ClassAds DYNES: – work in progress IPv6: – basics work in condor, still some work 17

(lark demo diagram) 18