Unverified Commit 95d680b8 authored by Thien Tran's avatar Thien Tran Committed by GitHub
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[Bugfix][IPEX] Add `VLLM_CPU_MOE_PREPACK` to allow disabling MoE prepack when...


[Bugfix][IPEX] Add `VLLM_CPU_MOE_PREPACK` to allow disabling MoE prepack when CPU does not support it (#14681)
Signed-off-by: default avatarThien Tran <gau.nernst@yahoo.com.sg>
parent fb4c7f8e
......@@ -195,6 +195,7 @@ vLLM CPU backend supports the following vLLM features:
- `VLLM_CPU_KVCACHE_SPACE`: specify the KV Cache size (e.g, `VLLM_CPU_KVCACHE_SPACE=40` means 40 GB space for KV cache), larger setting will allow vLLM running more requests in parallel. This parameter should be set based on the hardware configuration and memory management pattern of users.
- `VLLM_CPU_OMP_THREADS_BIND`: specify the CPU cores dedicated to the OpenMP threads. For example, `VLLM_CPU_OMP_THREADS_BIND=0-31` means there will be 32 OpenMP threads bound on 0-31 CPU cores. `VLLM_CPU_OMP_THREADS_BIND=0-31|32-63` means there will be 2 tensor parallel processes, 32 OpenMP threads of rank0 are bound on 0-31 CPU cores, and the OpenMP threads of rank1 are bound on 32-63 CPU cores.
- `VLLM_CPU_MOE_PREPACK`: whether to use prepack for MoE layer. This will be passed to `ipex.llm.modules.GatedMLPMOE`. Default is `1` (True). On unsupported CPUs, you might need to set this to `0` (False).
## Performance tips
......
......@@ -40,6 +40,7 @@ if TYPE_CHECKING:
VLLM_PP_LAYER_PARTITION: Optional[str] = None
VLLM_CPU_KVCACHE_SPACE: int = 0
VLLM_CPU_OMP_THREADS_BIND: str = ""
VLLM_CPU_MOE_PREPACK: bool = True
VLLM_OPENVINO_DEVICE: str = "CPU"
VLLM_OPENVINO_KVCACHE_SPACE: int = 0
VLLM_OPENVINO_CPU_KV_CACHE_PRECISION: Optional[str] = None
......@@ -349,6 +350,12 @@ environment_variables: dict[str, Callable[[], Any]] = {
"VLLM_CPU_OMP_THREADS_BIND":
lambda: os.getenv("VLLM_CPU_OMP_THREADS_BIND", "all"),
# (CPU backend only) whether to use prepack for MoE layer. This will be
# passed to ipex.llm.modules.GatedMLPMOE. On unsupported CPUs, you might
# need to set this to "0" (False).
"VLLM_CPU_MOE_PREPACK":
lambda: bool(int(os.getenv("VLLM_CPU_MOE_PREPACK", "1"))),
# OpenVINO device selection
# default is CPU
"VLLM_OPENVINO_DEVICE":
......
......@@ -7,6 +7,7 @@ from typing import Callable, List, Optional, Tuple
import torch
from torch.nn.parameter import UninitializedParameter
from vllm import envs
from vllm.config import get_current_vllm_config
from vllm.distributed import (get_dp_group, get_tensor_model_parallel_rank,
get_tensor_model_parallel_world_size,
......@@ -104,7 +105,7 @@ class UnquantizedFusedMoEMethod(FusedMoEMethodBase, CustomOp):
layer.ipex_fusion = ipex.llm.modules.GatedMLPMOE(
layer.w13_weight,
layer.w2_weight,
use_prepack=True,
use_prepack=envs.VLLM_CPU_MOE_PREPACK,
)
else:
raise NotImplementedError("CPU MOE only supports x86 arch.")
......
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