Query Engine
4 articles on Query Engine from Ayoob AI, the full code AI automation agency based in Newcastle upon Tyne.
Predicting GPU Hash Map Collisions with the Chao1 Estimator
GPU databases crash when GROUP BY cardinality is guessed wrong. The Chao1 estimator predicts it, used in our Newcastle-built analytics engine.
Executing SQL WHERE Clauses on the GPU with Dictionary Encoding
Filtering 10M customer records on a GPU in a browser, under 200ms. The technique powering our Newcastle AI data-query engines.
Sub-200ms Hospitality CRMs: Moving SQL Relational Operators to WebGPU
Server-side CRM queries add 150 to 400 ms per interaction. Our Adaptive WebGPU Data Query Engine runs relational operators on in-memory columnar data at the client, using dictionary encoding for GPU string processing and a 6-factor scoring function for per-operator dispatch.
GPU-Accelerated Relational Queries: Moving the Database to the Browser
Server round-trips add 50 to 300 ms per dashboard interaction. Our Adaptive WebGPU Data Query Engine compiles structured queries into execution plans where each operator is routed to one of three execution tiers (CPU main thread, Web Worker thread pool, or WebGPU compute pipeline) based on a 6-factor dispatch scoring function.
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