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<!doctype html><html lang="en"><meta charset="utf-8"><title>Publish a reproducible placement study</title><h1>Publish a reproducible placement study</h1><p>15-minute session: read for 3 minutes, trace for 3, experiment for 7, and complete the check for 2. Spend longer whenever you need.</p><p>Build a report for at least two workload sizes. Include source revision, device topology, memory type and placement, affinity, input seed, correctness tolerance, repetitions, raw samples, and end-to-end cost. Distinguish measured results, simulations, and untested candidates. Explain why the winning policy may change on another machine. Submit code and raw evidence on Forge, never confidential machine credentials.</p><p><strong>Practice and evidence:</strong> Predict the example or draw its state transitions. Change one assumption, test the boundary, and record the actual result. Explain what this small model does not establish about a production system.</p><h3>Practice and evidence</h3><p>Keep three notes: your prediction, the actual result, and why they match or differ. The completion check grades understanding; the practice task builds skill.</p><p><a href="https://git.agilaos.com/matt/open_agx">Language reference: git.agilaos.com</a></p><p><a href="https://docs.nvidia.com/cuda/cuda-c-best-practices-guide/">Language reference: docs.nvidia.com</a></p></html> |