[Bug] 随着时间运行，lmdeploy进程占用cpu提高且不释放

### Checklist

- [X] 1. I have searched related issues but cannot get the expected help.
- [X] 2. The bug has not been fixed in the latest version.
- [X] 3. Please note that if the bug-related issue you submitted lacks corresponding environment info and a minimal reproducible demo, it will be challenging for us to reproduce and resolve the issue, reducing the likelihood of receiving feedback.

### Describe the bug

版本：0.6.0
命令：
```
lmdeploy serve api_server Qwen1.5-110B-Chat-AWQ --server-port 9001 --session-len 16000 --enable-prefix-caching --max-batch-size 25 --tp 4 --quant-policy 8
```
每次重启隔一段时间过后，cpu会直接拉满，即使是在空闲时间内也没有释放
硬件环境：5c + 6g + A800 * 4

除了在0.6.0版本中有类似的问题以外，目前还发现0.6.2.post1也有同样的问题(其他版本暂未测试)
另外请教一下，这种问题应该如何排查？

### Reproduction

lmdeploy serve api_server Qwen1.5-110B-Chat-AWQ --server-port 9001 --session-len 16000 --enable-prefix-caching --max-batch-size 25 --tp 4 --quant-policy 8

### Environment

```Shell
sys.platform: linux
Python: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0]
CUDA available: True
MUSA available: False
numpy_random_seed: 2147483648
GPU 0,1,2,3: NVIDIA A800-SXM4-80GB
CUDA_HOME: /usr/local/cuda
NVCC: Not Available
GCC: x86_64-linux-gnu-gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
PyTorch: 2.1.2+cu121
PyTorch compiling details: PyTorch built with:
- GCC 9.3
- C++ Version: 201703
- Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v3.1.1 (Git Hash 64f6bcbcbab628e96f33a62c3e975f8535a7bde4)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- LAPACK is enabled (usually provided by MKL)
- NNPACK is enabled
- CPU capability usage: AVX512
- CUDA Runtime 12.1
- NVCC architecture flags: -gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90
- CuDNN 8.9.2
- Magma 2.6.1
- Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=12.1, CUDNN_VERSION=8.9.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=old-style-cast -Wno-invalid-partial-specialization -Wno-unused-private-field -Wno-aligned-allocation-unavailable -Wno-missing-braces -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_DISABLE_GPU_ASSERTS=ON, TORCH_VERSION=2.1.2, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF,

TorchVision: 0.16.2+cu121
LMDeploy: 0.6.0+unknown
transformers: 4.39.3
gradio: Not Found
fastapi: 0.110.1
pydantic: 2.6.4
triton: 2.1.0
NVIDIA Topology:
GPU0 GPU1 GPU2 GPU3 NIC0 NIC1 NIC2 NIC3 NIC4 NIC5 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X NV8 NV8 NV8 SYS SYS SYS SYS PXB NODE 32-63,96-127 1 N/A
GPU1 NV8 X NV8 NV8 SYS SYS SYS SYS PXB NODE 32-63,96-127 1 N/A
GPU2 NV8 NV8 X NV8 SYS SYS SYS SYS NODE PXB 32-63,96-127 1 N/A
GPU3 NV8 NV8 NV8 X SYS SYS SYS SYS NODE PXB 32-63,96-127 1 N/A
NIC0 SYS SYS SYS SYS X NODE NODE NODE SYS SYS
NIC1 SYS SYS SYS SYS NODE X PIX PIX SYS SYS
NIC2 SYS SYS SYS SYS NODE PIX X PIX SYS SYS
NIC3 SYS SYS SYS SYS NODE PIX PIX X SYS SYS
NIC4 PXB PXB NODE NODE SYS SYS SYS SYS X NODE
NIC5 NODE NODE PXB PXB SYS SYS SYS SYS NODE X

Legend:

X = Self
SYS = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
PHB = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
PXB = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
PIX = Connection traversing at most a single PCIe bridge
NV# = Connection traversing a bonded set of # NVLinks

NIC Legend:

NIC0: mlx5_0
NIC1: mlx5_1
NIC2: mlx5_2
NIC3: mlx5_3
NIC4: mlx5_4
NIC5: mlx5_5
```

### Error traceback

_No response_