STATUS Conditional alternative draft — not submitted; proceed only if managed Classroom fits the approved CPU/GPU strategy. PROJECT TITLE UArizona INFO 521 and LIS 671 CPU Classroom Pilot — [APPROVED TERM / YEAR] OPPORTUNITY / RESOURCE Explore ACCESS / CloudBank Classroom INTENDED USE Classroom / Training INSTITUTION University of Arizona · College of Information Science PI Greg Chism (proposed PI; confirm ACCESS profile, affiliation and eligibility before submission) CO-PIS [APPROVED COURSE LEAD(S), IF CO-PIs] PROJECT DATES [PROJECT START: SIX WEEKS BEFORE COURSE] through [PROJECT END: TWO WEEKS AFTER FINAL COURSE DATE] COURSE TITLES INFO 521: Introduction to Machine Learning — proposed pilot candidate; LIS 671: Digital Curation and Digital Preservation — proposed pilot candidate ENROLLMENT 80 planned students: 40 data science and 40 MLIS; confirm actual enrollments STAFF ACCOUNTS Up to six instructional/technical staff accounts; confirm role mapping and whether these count against provider limits KEYWORDS classroom computing; data science; library and information science; metadata; reproducibility; CPU notebooks FIELD OF SCIENCE Select the closest available education/information-science field(s) in the live form; CloudBank gives Science and Engineering Education as an example. SUPPORTING GRANT No supporting research grant is asserted by this draft. Add a grant only if the PI confirms that the pilot falls within that award’s authorized scope. MESA/IDSS funding is not assumed to fund instruction or local operations. PUBLIC OVERVIEW The University of Arizona College of Information Science requests CloudBank Classroom access through ACCESS for a two-course pilot in [TERM / YEAR]: INFO 521: Introduction to Machine Learning (proposed) and LIS 671: Digital Curation and Digital Preservation (proposed). Approximately 80 students would use browser-based CPU workspaces for reproducible data analysis, small-model evaluation, metadata normalization, collection queries and portable research outputs. The pilot aims to reduce software setup barriers and improve continuity of access across different student devices. We will evaluate workspace access, assignment reproducibility, export/recovery and staff effort using aggregate results. Both courses will retain an equivalent small-data CPU fallback, with institution-supported oversight, data handling and end-of-term exports. PLANNED WORK SUMMARY We propose one 15-week teaching pilot preceded by six weeks of configuration/canary testing and followed by a two-week export/close period, subject to provider and ACCESS approval. The proposed INFO 521 component will use Python notebooks to clean synthetic tabular data, visualize patterns and validate small CPU models. The proposed LIS 671 component will normalize synthetic collection records, document metadata crosswalks, query an embedded SQLite catalog and export structured records with provenance. No GPU, external managed database or paid student account is necessary for required coursework. We request persistent individual CPU workspaces for 80 students plus up to six course/technical staff accounts, institutional authentication, approved assignment distribution and a reproducible Python environment. The preferred student configuration is 2 vCPU, 6 GB RAM and an initial 5 GB home, or a provider-approved equivalent shown by rehearsal to run the assignments. Initial shared course data are modeled at 20 GB per course. Expand only after the canary demonstrates a justified need and the provider approves it. The college will designate course leads, primary/backup operators and support TAs, and will seek written operating commitments before classroom use; this draft does not claim those appointments or funds already exist. A ten-volunteer canary will precede provider-approved concurrency testing, account isolation, assignment execution, saved-file restart/export, grading-receipt reconciliation, accessibility review and a restore to a different environment. We will maintain CPU/small-data alternatives and independently restorable copies in institution-approved destinations. Rosters and grades will remain in approved institutional/LMS systems. The educational project will have explicit closure/export dates; continuation requires a confirmed provider/ACCESS process rather than assumed extension. Please confirm that the managed Classroom resource, rather than a general CloudBank commercial-cloud award, is appropriate; specify its accounting and credit/resource request amount. We can split the two courses into separate educational projects if ACCESS or the provider requires it. CURRENT ROUTE DECISION: ACCESS is intended to cover CPU and GPU for the classroom. Campus AWS is for CPU component testing only; free GPU benchmarks precede piloting. This older CPU-only managed-Classroom concept is conditional and cannot replace the CPU/GPU plan without explicit confirmation of GPU coverage or an approved split implementation. OPERATING CONSTRAINT: Greg has four hours/week total for allocation, component testing, operations and grant preparation. There is zero cash budget. TA and course-lead effort is separate (course leads need no salary). Necessary paid support/storage/hosting awaits confirmed eligible EduCloud grant funding; no award or finance role is assumed. RESOURCE JUSTIFICATION / AMOUNT Planning workload: 80 students × 8 active workspace-hours/week × 15 weeks = 9,600 student workspace-hours; 2 vCPU each implies 19,200 CPU core-hours of active demand. A 25% usage allowance gives 12,000 workspace-hours / 24,000 CPU core-hours before provider orchestration/idle billing and staff use. These are workload descriptions, not CloudBank SUs or ACCESS credit conversion. Request an initial 5 GB home per student plus 20 GB shared data per course: 80 × 5 + 2 × 20 = 440 GB before staff homes and provider overhead. Core tabular/catalog inputs are bounded below 250 MB each; the home/shared allowance covers notebooks, multiple assignment copies, outputs and approved small projects. Measure usage in the canary and grow only for justified semester needs with provider approval. The earlier 20 GB-home / 2 TB Jetstream2 assessment is a larger planning scenario, not a minimum CloudBank requirement. This conditional managed-CPU concept excludes GPU. The intended ACCESS allocation includes GPU separately; this concept is usable only if the CPU/GPU implementation and coverage are explicitly confirmed. Numeric CloudBank credit/resource amount remains to be supplied from the provider’s actual managed-Classroom accounting; do not enter the Jetstream2 VM model as CloudBank credits. SOFTWARE AND ASSIGNMENTS Python/JupyterLab with approved pandas, scikit-learn, matplotlib, CSV/JSON/XML parsing and SQLite; optional R/RStudio and MARC parsing packages only if needed and supported. Request version pinning and notebook distribution (for example, nbgitpuller) where the provider supports them. Confirm the actual grading extensions, assignment export and permissions; no LMS integration is presumed. OTHER AVAILABLE RESOURCES Campus UITS/AWS: Greg confirms access via requests, restricted in this plan to CPU component testing; exact limits/charges/dates need confirmation. Free Kaggle and Colab GPU resources: staff pre-pilot benchmarks only, subject to actual account eligibility, quotas and hardware availability. ACCESS provides the intended CPU and GPU classroom allocation. CloudBank is conditional through ACCESS. CyVerse/MESA, NRP and OSPool remain optional separate components; MESA funding is not automatically an instructional allocation or operations budget. REQUIRED COMPLETION / ATTACHMENTS - Final approved syllabus PDF for the data science course — missing. - Final approved syllabus PDF for the MLIS course — missing. - PI CV/résumé PDF and co-PI CVs if applicable — missing. - Confirm INFO 521 and LIS 671 selection/offering, instructor consent, course sections, enrollment, class dates and project preparation/export dates — missing. - Provider-confirmed resource configuration, accounting/request amount and one-versus-two-project structure — missing. - Named operator/backup, course leads, data/support approvals and budget/workload commitments — pending. REVIEW AND SUBMISSION STEPS 1. Designated eligible PI checks/creates their own ACCESS profile with matching institutional affiliation/email. No account has been created by this draft. 2. In the allocations portal, choose Explore ACCESS, Classroom / Training and CloudBank Classroom; confirm the current form and any course-specific project separation. 3. Paste the reviewed title, public overview, keywords, summary and provider-confirmed configuration/amount; supply the actual course dates/enrollment. 4. Attach the final approved syllabus PDFs and required CV/résumé PDFs, using the current portal/provider guidance. This generated request PDF is supporting draft text, not a substitute for either syllabus. 5. The human PI reviews scope, eligibility, disclosures, attachments and contact details before submitting. This site has no submission action. PROVIDER QUESTIONS (NOT SENT) - Can this general ACCESS Classroom route host two courses/80 students plus six staff, or do you require separate projects? What student CPU/RAM/home storage and shared storage can you provide? - What units/credits should we request for the described workload, and what orchestration, idle use, storage and support are included? Are any uncovered charges possible? - Can you pin the requested environment and support assignment distribution, grading permissions and complete student/instructor exports? - What actual institutional login/roster roles, support windows, accessibility documentation, concurrency and maintenance arrangements apply? - Can we automate or schedule independent file exports to approved destinations without shared credentials? What is the session/persistence behavior? - Which project start/end, canary, export, deletion and next-term process applies? Please reconcile the one-year renewal description with ACCESS education-period/extension policy.