Results for “partitioning”

Split a large pull request into multiple smaller PRs to reduce the number of required CODEOWNERS reviewer groups.

Diagnoses Qdrant capacity needs and guides horizontal scaling decisions, including node count, shard count, replication factor, and resharding trade-offs.

Optimizes Qdrant query performance for large limits across multiple shards by using Poisson-distributed subsampling to reduce inter-shard data transfer.

Diagnose and optimize slow-loading, high-memory, or low-FPS USD scenes using a structured workflow with profiling, validation, and mutation phases.

Load sharded datasets (npy, Parquet, HDF5, raw binary) into distributed cuPyNumeric arrays using manual partitioning and Legate task launches.