5 papers
EvoMem: Memory-Augmented Evolution for Code Optimization
Viktor Volkov, Valentin Khrulkov, Andrey V. Galichin +8
Successful mutation strategies in evolutionary code search may contain reusable knowledge that is useful beyond a single run, and in some cases may transfer across related tasks an…
CoRoVA: Compressed Representations for Vector-Augmented Code Completion
Daria Cherniuk, Nikita Sukhorukov, Danil Gusak +4
Retrieval-augmented generation has emerged as one of the most effective approaches for code completion enhancement, especially when repository-level context is important. However,…
Birch SGD: A Tree Graph Framework for Local and Asynchronous SGD Methods
Alexander Tyurin, Danil Sivtsov
We propose a new unifying framework, Birch SGD, for analyzing and designing distributed SGD methods. The central idea is to represent each method as a weighted directed tree, refer…
Cluster Topology-Driven Placement of Experts Reduces Network Traffic in MoE Inference
Danil Sivtsov, Aleksandr Katrutsa, Ivan Oseledets
Efficient deployment of a pre-trained LLM to a cluster with multiple servers is a critical step for providing fast responses to users' queries. The recent success of Mixture-of-Exp…
Diagonal Batching Unlocks Parallelism in Recurrent Memory Transformers for Long Contexts
Danil Sivtsov, Ivan Rodkin, Gleb Kuzmin +2
Transformer models struggle with long-context inference due to their quadratic time and linear memory complexity. Recurrent Memory Transformers (RMTs) offer a solution by reducing…