wehub-resource-sync
24 lines
1.1 KiB
Markdown
24 lines
1.1 KiB
Markdown
# Serving patterns
|
|
|
|
Architecture documentation for distributed LLM serving patterns.
|
|
|
|
```{toctree}
|
|
:hidden:
|
|
:maxdepth: 1
|
|
|
|
Data parallel attention <data-parallel>
|
|
Prefill-decode disaggregation <prefill-decode>
|
|
```
|
|
|
|
## Overview
|
|
|
|
Ray Serve LLM supports several serving patterns that can be combined for complex deployment scenarios:
|
|
|
|
- {doc}`Data parallel attention <data-parallel>`: scale throughput by running multiple coordinated engine replicas that process requests in parallel, replicating attention while sharding requests across the replicas.
|
|
- {doc}`Prefill-decode disaggregation <prefill-decode>`: optimize resource utilization by separating prompt processing from token generation.
|
|
|
|
These patterns are composable and can be mixed to meet specific requirements for throughput, latency, and cost optimization.
|
|
|
|
These pages describe how each pattern works. For step-by-step configuration, see the matching how-to guides: {doc}`Data parallel attention <../../user-guides/data-parallel-attention>` and {doc}`Prefill/decode disaggregation <../../user-guides/prefill-decode>`.
|
|
|