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Methods · GPU operations

Your team's library.

Define capacity, take delivery of the configuration, monitor processing, and retain results: choose your stage, then walk away with a decision, a method, or a file to complete.

A first team folder?

Start with a clear scope.

  1. 01 Define the needExpected result and constraints
  2. 02 Compare the optionsBatches, memory, and commitment
  3. 03 Prepare the handoverCriteria, evidence, and decision
Takeaway · v1 files

Two dossiers, working documents.

Read the method, adapt the criteria, then keep your team's observations.

Receipt · checklist and example

Decide whether the configuration is ready

Ten checks, a blank checklist, a fictional example and a rejection checklist. The observations remain to be completed on your target.

Decision
Accept, hold or reject
Evidence
Criterion, observation and document
Owner
Checker and decision-maker to be named
Excerpt from the blank checklist · R02Accessible cardsCriterion: model and count agreed in the scopeObservation, unit and evidence: to be completed
Migration · procedure and exercise

Organize a verifiable recovery

Eight fictional batches, a log and a Python exercise. The published checks concern files and a single CPU worker; they do not measure any GPU.

Decision
Switch, wait, or return
Evidence
Accepted states and results
Owner
Recovery authority to designate
The batch registry · fields to completelot_id · version_entree · statutmachine_autorisee · responsable_validationcritere_acceptation · motif_reprise
01

Frame the capacity

Turn the team's requests into criteria and a schedule.

02

Prepare and receive

Match the accesses, the data and the target to the agreed need.

03

Operate and diagnose

Make the work observable and keep a clear action in the face of deviations.

04

Migrate and retain

Prepare the handover, verify the copies and close the files without losing the context.