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OpenPipe
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ART
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Price trainer-rank memory profiles by packed tokens, not sharing ratio
- #950
#950
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bradhilton
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Sep 24, 2026
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Price trainer-rank memory profiles by packed tokens, not sharing ratio
#950
bradhilton
merged 13 commits into
main
OpenPipe/ART:main
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dalinar/planner-sharing-ratio
OpenPipe/ART:dalinar/planner-sharing-ratio
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Price trainer-rank memory profiles by packed tokens, not sharing ratio
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Price logical-sized head copies and output gradients; drop stale callers
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Scope packed-token pricing to single-target training requests
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Tighten packed-pricing scope and charge head rows beyond profile sharing
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Charge retained head rows and keep packed pricing monotone
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Charge GDN branch states and keep packed pricing monotone at the floor
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Limit packed pricing to one-layer full recompute
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Detect one-layer recompute from exact config and training mode
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Read the decoder's own mode and recompute config when pricing
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Charge allocator blocks for shared rows; read the decoder's own mode
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Size the shared-row charge from a measured head peak
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Charge head and caller memory per logical row; clamp sharing to 8x
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Keep short-request batches on the calibrated profile
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