{"resourceId":"uw-tillicum-gpu-supercomputer-first-year-usage-20261102","versions":[{"version":"external-3e0b6b977c0fe359bf762e5839c5567e473d67691a8eba9fa8ec953de4b882b8","resource":{"id":"uw-tillicum-gpu-supercomputer-first-year-usage-20261102","title":"UW's Tillicum Supercomputer Marks First Anniversary","organization":"University of Washington Information Technology (UWIT)","sector":"University research computing (shared GPU supercomputer)","geography":"United States (Washington)","publishedAt":"2 November 2026 (UWIT news)","publicationDate":"2026-11-02","eventDate":null,"sourceName":"UW Information Technology","sourceLabel":"UWIT news, \"UW's Tillicum Supercomputer Marks First Anniversary,\" 2 Nov 2026","sourceUrl":"https://it.uw.edu/tillicum-supercomputer-marks-first-anniversary/","evidenceClass":"vendor-claim","outcomeClass":"emerging","topics":["infrastructure","operating-model","accessibility-workforce"],"finding":"UW reports that Tillicum, a $10 million UWIT GPU investment, supported 336,606 jobs and 1,018,768 GPU hours in its first year for 940 users from 159 research groups, 64 departments, 17 colleges and schools, and all three campuses. Students can access it through Student Technology Fee-funded credits. UW says shared GPUs reduce the need for groups to buy their own hardware.","sledRelevance":"Directly relevant to public research universities deciding whether to centralize GPU investment: a first-year usage baseline from a peer institution. Adoption breadth is shown; research outcomes and cost per GPU hour are not.","evidence":"Institutional self-report of usage counts and rankings (No. 7 U.S. higher ed on Green500, 10th on TOP500 per the post). No utilization rate, queue times, cost recovery, or research outcomes reported. Partner-sponsored events (Dell, NVIDIA) noted. Classified as a self-reported institutional claim.","architectureImplications":"Centrally funded shared GPU cluster serving multiple campuses, with student access through fee-funded credits and cloud providers participating in a symposium, suggesting hybrid on-prem/cloud discussion.","governanceImplications":"Allocation across 159 groups and student access implies governance for fair share and credits; not described in the post.","securityPrivacyImplications":"Shared clusters require tenant separation and data classification policies; not described.","caveats":"Self-reported; no denominator for capacity, so utilization cannot be computed; rankings not independently checked here; partner-sponsored events.","streamIds":["research"],"roles":{"sales":"Infrastructure framing: a peer public university can show broad first-year uptake of a central GPU investment, which supports conversations about consolidating departmental GPU purchases. A bounded engagement could assess demand and governance for a shared cluster. Interpretation: the post shows usage breadth only, so it cannot support claims of cost savings, research acceleration, or ROI.","engineering":"Fit is a central GPU cluster serving many departments plus student credits. Integration concerns are scheduler fair-share, identity across campuses, storage, and cloud bursting. Prerequisites include demand data and a funding model. Constraints: the source gives no utilization, queue, or cost figures. A proof of value should collect GPU-hour demand, queue wait and utilization from the institution's own departments before sizing.","delivery":"Delivery work is standing up or expanding a shared GPU service: allocation policy, onboarding, student credit program, and usage reporting. Ownership sits with central IT research computing. Governance checkpoints include fair-share policy and data classification for sensitive research. Acceptance criteria are proposals such as published utilization and wait-time reporting; risks include oversubscription and unclear cost recovery."},"roleDetails":{"sales":{"customerProblem":"Departments buy and run their own GPUs, leaving capacity fragmented and access uneven for smaller groups and students.","stakeholders":["CIO","Research computing director","Vice President for Research","Faculty governance","Student technology fee committee"],"discoveryQuestions":["How many departments buy GPUs independently today?","What utilization and wait-time data exist?","How would student access be funded?","What cost-recovery model is acceptable?"],"valueHypothesis":"A central shared cluster may broaden access across departments, as UW reports, though cost effects remain unmeasured.","potentialEngagement":"A demand and governance assessment for a shared GPU service, using UW's published counts as a reference point.","unsupportedClaims":["Cost savings from consolidation","Research productivity gains","Utilization levels"]},"engineering":{"fit":"Fits universities with scattered departmental GPU demand.","architectureIntegration":"Central cluster, scheduler fair-share, campus identity, research storage, optional cloud burst.","prerequisites":["Demand survey","Funding/cost-recovery model","Data classification policy"],"constraints":["No utilization or queue data in source","Rankings self-reported","Hardware pricing volatility"],"security":"Tenant separation, controlled-data enclaves where needed, and access reviews for student accounts.","proofOfValue":["Measure own GPU demand and wait times","Pilot shared allocation with several departments","Track utilization monthly"]},"delivery":{"work":"Design allocation policy and onboarding; Launch usage reporting and student credits","dependencies":["Central IT funding","Data center power/cooling","Scheduler and identity integration"],"ownership":"Central IT research computing.","skillsAdoption":"User training and office hours for new GPU users across disciplines.","governanceCheckpoints":["Fair-share policy approval","Data classification review","Annual usage and outcome review"],"acceptanceCriteria":["Proposed: utilization and queue-wait published quarterly","Proposed: number of departments served tracked","Proposed: student credit uptake reported"],"risks":["Oversubscription","Unfunded refresh cycle","Equity gaps between groups"]}},"retrievedAt":"2026-11-03T22:06:03-06:00","enrichedAt":"2026-11-03T22:07:06-06:00","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Student access through fee-funded credits and cross-campus users suggests broader workforce development, though outcomes are not reported.","procurementImplications":"Centralized purchasing can replace scattered departmental buys; post does not provide price or contract details.","operatingModelImplications":"Central IT-run shared service model with student credit program.","sourceVerification":{"openedUrl":"https://it.uw.edu/tillicum-supercomputer-marks-first-anniversary/","referenceExcerpt":"In its first year, Tillicum supported 336,606 computing jobs and delivered 1,018,768 GPU hours","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}