Cycles: Add support for P2P memory distribution (e.g. via NVLink)

This change modifies the multi-device implementation to support memory distribution
across devices, to reduce the overall memory footprint of large scenes and allow scenes to
fit entirely into combined GPU memory that previously had to fall back to host memory.

Reviewed By: brecht

Differential Revision: https://developer.blender.org/D7426

1 files changed, 20 insertions, 7 deletions

diff --git a/intern/cycles/blender/addon/properties.py b/intern/cycles/blender/addon/properties.py
index da18ac7c693..1635afab210 100644
--- a/intern/cycles/blender/addon/properties.py
+++ b/intern/cycles/blender/addon/properties.py
@@ -1535,6 +1535,12 @@ class CyclesPreferences(bpy.types.AddonPreferences):
 
     devices: bpy.props.CollectionProperty(type=CyclesDeviceSettings)
 
+    peer_memory: BoolProperty(
+        name="Distribute memory across devices",
+        description="Make more room for large scenes to fit by distributing memory across interconnected devices (e.g. via NVLink) rather than duplicating it",
+        default=False,
+    )
+
     def find_existing_device_entry(self, device):
         for device_entry in self.devices:
             if device_entry.id == device[2] and device_entry.type == device[1]:
@@ -1632,14 +1638,21 @@ class CyclesPreferences(bpy.types.AddonPreferences):
         row = layout.row()
         row.prop(self, "compute_device_type", expand=True)
 
-        devices = self.get_devices_for_type(self.compute_device_type)
+        if self.compute_device_type == 'NONE':
+            return
         row = layout.row()
-        if self.compute_device_type == 'CUDA':
-            self._draw_devices(row, 'CUDA', devices)
-        elif self.compute_device_type == 'OPTIX':
-            self._draw_devices(row, 'OPTIX', devices)
-        elif self.compute_device_type == 'OPENCL':
-            self._draw_devices(row, 'OPENCL', devices)
+        devices = self.get_devices_for_type(self.compute_device_type)
+        self._draw_devices(row, self.compute_device_type, devices)
+
+        import _cycles
+        has_peer_memory = 0
+        for device in _cycles.available_devices(self.compute_device_type):
+            if device[3] and self.find_existing_device_entry(device).use:
+                has_peer_memory += 1
+        if has_peer_memory > 1:
+            row = layout.row()
+            row.use_property_split = True
+            row.prop(self, "peer_memory")
 
     def draw(self, context):
         self.draw_impl(self.layout, context)