Cornserve introduces a task abstraction and record-and-replay runtime for Any-to-Any multimodal models, achieving up to 3.81x higher throughput and 5.79x lower tail latency through component disaggregation and direct tensor forwarding.
Efficient memory management for large language model serving with PagedAttention
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Cornserve: A Distributed Serving System for Any-to-Any Multimodal Models
Cornserve introduces a task abstraction and record-and-replay runtime for Any-to-Any multimodal models, achieving up to 3.81x higher throughput and 5.79x lower tail latency through component disaggregation and direct tensor forwarding.