Fix DDP master address for dynamic task scheduling

The fundamental issue was that MASTER_ADDR was hardcoded to
airflow-worker-gpu-0, but rank 0 might run on any worker due to
Celery's dynamic task scheduling.

Now rank 0 dynamically stores its FQDN as the master address,
and all other ranks connect to it.

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
2026-04-15 12:23:15 +03:00
parent ef78f2a7b8
commit 48abe40c15

View File

@@ -76,11 +76,39 @@ def run_training_node_func(rank, world_size):
else:
raise RuntimeError(f"[{rank}] Timeout waiting for all workers to be ready!")
# STEP 2.5: Rank 0 stores its address, others wait for it
print(f"[{rank}] Determining master address...")
my_fqdn = socket.getfqdn()
print(f"[{rank}] My FQDN: {my_fqdn}")
if rank == 0:
# Rank 0 stores its address as the master
sync_state = json.loads(Variable.get('ddp_sync_state', default_var='{}'))
sync_state['master_addr'] = my_fqdn
Variable.set('ddp_sync_state', json.dumps(sync_state))
print(f"[{rank}] I am the master. Stored my address: {my_fqdn}")
else:
# Other ranks wait for rank 0 to store its address
max_wait = 60
start_wait = time.time()
while time.time() - start_wait < max_wait:
sync_state = json.loads(Variable.get('ddp_sync_state', default_var='{}'))
if 'master_addr' in sync_state:
master_addr = sync_state['master_addr']
print(f"[{rank}] Master address retrieved: {master_addr}")
break
print(f"[{rank}] Waiting for master address...")
time.sleep(1)
else:
raise RuntimeError(f"[{rank}] Timeout waiting for master address!")
# Small delay to ensure all workers see the ready state
time.sleep(3)
# STEP 3: Configure distributed environment
os.environ['MASTER_ADDR'] = MASTER_ADDR
# Use dynamic master address from rank 0
actual_master_addr = my_fqdn if rank == 0 else sync_state.get('master_addr', MASTER_ADDR)
os.environ['MASTER_ADDR'] = actual_master_addr
os.environ['MASTER_PORT'] = MASTER_PORT
os.environ['WORLD_SIZE'] = str(world_size)
os.environ['RANK'] = str(rank)