Oom
Oom in the context of production machine-learning systems.
Lessons
Formal explanations, examples, simulations, and checkpoints.
What the GPU actually executes
Use what the gpu actually executes to move the gpu training production brief toward a defensible release.
GPU-aware trainingKeep it fed: loaders and async copies
Use keep it fed: loaders and async copies to move the gpu training production brief toward a defensible release.
GPU-aware trainingMixed precision without NaNs
Use mixed precision without nans to move the gpu training production brief toward a defensible release.
GPU-aware trainingActivations, accumulation, and checkpointing
Use activations, accumulation, and checkpointing to move the gpu training production brief toward a defensible release.
GPU-aware trainingProfile from timeline to cost per sample
Use profile from timeline to cost per sample to move the gpu training production brief toward a defensible release.
Courses & assignments
Dependency-authoritative learning units.
Casebook
Reported facts and course reconstructions.