[Bugfix] torch.set_num_threads() in multiproc_gpu_executor (#6802)

[Bugfix] Use torch.set_num_threads() to configure parallelism in multiproc_gpu_executor (#6802)
Signed-off-by: Travis Johnson <tsjohnso@us.ibm.com>

vllm/executor/multiproc_gpu_executor.py

@@ -6,6 +6,8 @@ import weakref
 from functools import partial
 from typing import Any, List, Optional
 
+import torch
+
 from vllm.executor.distributed_gpu_executor import (  # yapf: disable
     DistributedGPUExecutor, DistributedGPUExecutorAsync)
 from vllm.executor.gpu_executor import create_worker
@@ -45,10 +47,23 @@ class MultiprocessingGPUExecutor(DistributedGPUExecutor):
         # Disable torch async compiling which won't work with daemonic processes
         os.environ["TORCHINDUCTOR_COMPILE_THREADS"] = "1"
 
-        # Set OMP_NUM_THREADS to 1 if it is not set explicitly, avoids CPU
-        # contention amongst the shards
-        if "OMP_NUM_THREADS" not in os.environ:
-            os.environ["OMP_NUM_THREADS"] = "1"
+        # Configure thread parallelism if OMP_NUM_THREADS isn't set
+        #
+        # Helps to avoid CPU contention. The default of spawning a thread per
+        # core combined with multiprocessing for each GPU can have a negative
+        # impact on performance. The contention is amplified when running in a
+        # container where CPU limits can cause throttling.
+        default_omp_num_threads = 1
+        if "OMP_NUM_THREADS" not in os.environ and (
+                current_parallelism :=
+                torch.get_num_threads()) > default_omp_num_threads:
+            logger.warning(
+                "Reducing Torch parallelism from %d threads to %d to avoid "
+                "unnecessary CPU contention. Set OMP_NUM_THREADS in the "
+                "external environment to tune this value as needed.",
+                current_parallelism, default_omp_num_threads)
+            os.environ["OMP_NUM_THREADS"] = str(default_omp_num_threads)
+            torch.set_num_threads(default_omp_num_threads)
 
         # workaround for https://github.com/vllm-project/vllm/issues/6103
         if world_size > 1: