TL;DR
A join optimizer for Souffl´e is developed that automatically computes high-quality join orders using a feedback-directed optimization strategy, surpassing the performance of un-tuned join orders by a geometric mean speedup.
Modern web applications are increasingly reliant on Object-Relational Mapper (ORM) frameworks to bridge the gap between high-level application logic and relational databases. However, in standard Create, Read, Update, and Delete (CRUD) architectures, the use of a unified data model often leads to significant performanc...
A novel code-generating engine with factorization that enables intra-query-parallelized query execution on factorized representations and generates code to overcome their CPU-unfriendly layout, offering a unified and scalable solution for modern workloads.
Torchy is presented, a tracing JIT compiler for PyTorch, one of the mainstream eager-mode frameworks, that achieves similar performance as data-flow frameworks, while providing the same semantics of straight-away execution.
This paper revisits the connection between Datalog and relational databases, advocating recursive SQL as a backend for Datalog evaluation, and presents a compilation framework that translates Datalog programs, particularly those in the Linear Datalog fragment, into equivalent recursive SQL queries.
Nowadays, modern applications do more than just store text -- they need to derive meaningful insights from it. To do that, they usually rely on wildcard queries with LIKE predicate to extract patterns. However, modern database management systems (DBMSs) handle these wildcard operations poorly, resorting to nested loops...
Training and serving large language models (LLMs) has become a core business for AI providers. To ensure a high-quality user experience while optimizing infrastructure costs, providers need to closely monitor the performance of LLM executions in production. However, existing performance profiling tools fall short in th...
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