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- Interrupt the thread before waiting on join - Provide a method for looping threads to exit on demand - CHECK if start and stop succeed instead of returning an error
- Makes sure each solver accesses a different subset of the data - Sequential reading of DB for performance - Prefetches a configurable amount of data to host memory - Distributes data to solvers in round-robin way for determinism
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Merged with revisions in #2903, thanks. |
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Part of #2351, but switched to a round-robin way of distributing data to solvers, instead of the shared queue that was not deterministic. Combined with random seeds initialization on threads in #2367, it should make parallel training reproducible.
The data reader sits between a database and each solver's prefetch thread. It makes sure each solver processes a different subset of the database. It also prefetches data, but to host memory, and the amount is configurable. Solvers prefetch threads instead only prefetch a fixed small amount of data, since it is stored in GPU memory.