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<!doctype html><html lang="en"><meta charset="utf-8"><title>Select a backend from evidence</title><h1>Select a backend from evidence</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>Filter candidates by capability, correctness, memory capacity, and constraints before comparing speed. Match representative workload sizes and include transfers. Preserve a fallback when a device is absent. The table below contains invented demonstration results, explicitly marked as such; replace them with real measurements only after validation. Do not fit a policy to one lucky run.</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><pre><code class="language-python">candidates=[{"name":"CPU demo","correct":True,"ms":8},{"name":"GPU demo","correct":True,"ms":11},{"name":"Broken demo","correct":False,"ms":1}]
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valid=[c for c in candidates if c["correct"]]
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print("Hypothetical winner:",min(valid,key=lambda c:c["ms"])["name"])
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</code></pre><p><strong>Expected result:</strong> <code>Hypothetical winner: CPU demo</code></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> |