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4 changes: 2 additions & 2 deletions .github/workflows/unifiedcache_test.yml
Original file line number Diff line number Diff line change
Expand Up @@ -43,10 +43,10 @@ jobs:
--entrypoint /bin/bash \
vllm/vllm-openai:v0.9.2 \
-c "
set -euo pipefail
pip install -v -e . --no-build-isolation
cd \$(pip show vllm | grep Location | awk '{print \$2}') &&
git apply /workspace/unified-cache-management/ucm/integration/vllm/patch/0.9.2/vllm-adapt.patch &&
git apply /workspace/unified-cache-management/ucm/integration/vllm/patch/0.9.2/vllm-adapt-sparse.patch
git apply /workspace/unified-cache-management/ucm/integration/vllm/patch/0.9.2/vllm-adapt.patch
cd /workspace/unified-cache-management
python3 -m unittest discover -s test
"
27 changes: 21 additions & 6 deletions docs/source/user-guide/prefix-cache/dram_store.md
Original file line number Diff line number Diff line change
Expand Up @@ -4,12 +4,27 @@ This document provides a usage example and configuration guide for the **DRAM Co

## Performance

Combining UCM with vLLM delivers 3–10× improvements in latency and GPU efficiency, especially for long-context LLM tasks.

<p align="center">
<img alt="UCM" src="../../images/dram_perform.png" width="90%">
</p>

### Overview
The following are the multi-concurrency performance test results of UCM in the Prefix Cache scenario under a CUDA environment, showing the performance improvements of UCM on two different models.
During the tests, HBM cache was disabled, and KV Cache was retrieved and matched only from DRAM.

In the QwQ-32B model, the test used one H20 server with two GPUs.

Here, Full Compute refers to pure VLLM inference, while DRAM80% indicates that after UCM pooling, the DRAM hit rate of the KV cache is 80%.

The following table shows the results on the QwQ-32B model:
| **QwQ-32B** | | | | |
| ---------------: | -------------: | ------------------: | -------------: | :----------- |
| **Input length** | **Concurrent** | **Full Compute(s)** | **DRAM80%(s)** | **Speedup** |
| 4 000 | 1 | 1.0269 | 0.3102 | **+230.9 %** |
| 8 000 | 1 | 2.0902 | 0.5718 | **+265.5 %** |
| 16 000 | 1 | 4.4852 | 1.1914 | **+276.4 %** |
| 4 000 | 2 | 1.5383 | 0.4209 | **+265.4 %** |
| 8 000 | 2 | 3.1323 | 0.8231 | **+280.5 %** |
| 16 000 | 2 | 6.7984 | 1.7420 | **+290.2 %** |
| 4 000 | 4 | 2.8173 | 0.9444 | **+198.2 %** |
| 8 000 | 4 | 5.2643 | 1.8290 | **+187.8 %** |
| 16 000 | 4 | 11.3651 | 3.6706 | **+209.6 %** |
## Features

The DRAM connector supports the following functionalities:
Expand Down