Autodetect the number of GPUs when starting Ray. (#1293)

* autodetect

* Wed Dec  6 12:46:52 PST 2017

* Wed Dec  6 12:47:54 PST 2017

* Move GPU autodetection into services.py.

* Fix capitalization of Nvidia.

* Update documentation.

python/ray/services.py

@@ -279,6 +279,20 @@ def wait_for_redis_to_start(redis_ip_address, redis_port, num_retries=5):
                         "configured properly.")
 
 
+def _autodetect_num_gpus():
+    """Attempt to detect the number of GPUs on this machine.
+
+    TODO(rkn): This currently assumes Nvidia GPUs and Linux.
+
+    Returns:
+        The number of GPUs if any were detected, otherwise 0.
+    """
+    proc_gpus_path = "/proc/driver/nvidia/gpus"
+    if os.path.isdir(proc_gpus_path):
+        return len(os.listdir(proc_gpus_path))
+    return 0
+
+
 def _compute_version_info():
     """Compute the versions of Python, cloudpickle, pyarrow, and Ray.
 
@@ -679,6 +693,9 @@ def start_local_scheduler(redis_address,
         # By default, use the number of hardware execution threads for the
         # number of cores.
         resources["CPU"] = psutil.cpu_count()
+    if "GPU" not in resources:
+        # Try to automatically detect the number of GPUs.
+        resources["GPU"] = _autodetect_num_gpus()
     print("Starting local scheduler with the following resources: {}."
           .format(resources))
     local_scheduler_name, p = ray.local_scheduler.start_local_scheduler(

python/ray/worker.py

@@ -1224,7 +1224,9 @@ def _init(address_info=None,
         num_cpus (int): Number of cpus the user wishes all local schedulers to
             be configured with.
         num_gpus (int): Number of gpus the user wishes all local schedulers to
-            be configured with.
+            be configured with. If unspecified, Ray will attempt to autodetect
+            the number of GPUs available on the node (note that autodetection
+            currently only works for Nvidia GPUs).
         resources: A dictionary mapping resource names to the quantity of that
             resource available.
         num_redis_shards: The number of Redis shards to start in addition to