concept:batching
Batching
Batching in the context of production machine-learning systems.
Lessons
Formal explanations, examples, simulations, and checkpoints.
Serving & inference systems
Package model, preprocessing, schema, and runtime
The deployable artifact is the complete raw-input-to-output program, not the weights alone.
Serving & inference systemsFeatures, batching, caching, and backpressure
Fast serving comes from bounded, version-aware work; graceful overload is a feature, not an afterthought.
Serving & inference systemsCapacity, load testing, autoscaling, and tails
Design capacity around the tail and the delay of the scaling loop, not around average throughput.
Courses & assignments
Dependency-authoritative learning units.
Casebook
Reported facts and course reconstructions.
Pinterest · Serving & cost
GPU-accelerated inference at Pinterest
Accelerators pay off only when the entire request path feeds them efficiently.
Pinterest · Serving & costRay batch inference: coordinating data and model work
Batch inference is a bounded dataflow whose correctness includes exactly-once publication.