arXiv (All)
open access
Koala: Non-disruptive Reconfiguration for Long-running Stateful Dataflows
Stateful dataflow systems must decide where state lives relative to the tasks that process it. For long-running applications that require frequent reconfiguration due to changes in resource allocation, partitioning, or task placement, this design choice presents a core trade-off between adaptability
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Koala: Non-disruptive Reconfiguration for Long-running Stateful Dataflows#1406430
- Optimizing Allreduce Operations for Modern Heterogeneous Architectures with Multiple Processes per GPU#670369
- Optimizing Allreduce Operations for Modern Heterogeneous Architectures with Multiple Processes per GPU#668304
- Trillion-Parameter MoE in a Box: Decoupling Memory Provisioning with High-Bandwidth Flash#1109618
- Supporting workflow reproducibility by linking bioinformatics tools across papers and executable code#1039140
Record · ID 1413180
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive