diff --git a/tensorflow/compiler/xla/pjrt/pjrt_client.cc b/tensorflow/compiler/xla/pjrt/pjrt_client.cc
index 868ba991b71..a5fdd00fb05 100644
--- a/tensorflow/compiler/xla/pjrt/pjrt_client.cc
+++ b/tensorflow/compiler/xla/pjrt/pjrt_client.cc
@@ -334,10 +334,14 @@ void RecordUsage(PjRtBuffer::ScopedHold device_buffer,
 //
 // It is safe to delete the returned PjRtBuffer without further
 // synchronization if an error occurs before the buffer is used.
+//
+// The caller may optionally provide a definition event to be recorded in
+// the buffer.
 StatusOr<std::unique_ptr<PjRtBuffer>> AllocateDestinationBuffer(
     const Shape& on_host_shape, PjRtDevice* device,
     LocalDeviceState* local_device, se::Stream* copy_stream,
-    bool is_uninitialized_create, PjRtClient* client) {
+    bool is_uninitialized_create, PjRtClient* client,
+    std::shared_ptr<BufferSequencingEvent> definition_event = nullptr) {
   if (on_host_shape.IsTuple() && on_host_shape.tuple_shapes_size() == 0) {
     return InvalidArgument("Can't make a buffer from an empty tuple");
   }
@@ -377,10 +381,18 @@ StatusOr<std::unique_ptr<PjRtBuffer>> AllocateDestinationBuffer(
       definition_events.back()->SetSequencingEvent(
           std::move(event), local_device->compute_stream());
     }
+    // if the caller provided a definition event then we record that.
+    if (definition_event) {
+      definition_events.emplace_back(definition_event);
+    }
   } else {
     // We have at least one definition event, for the copy completing to
     // the device buffers.
-    definition_events.emplace_back(std::make_shared<BufferSequencingEvent>());
+    if (definition_event) {
+      definition_events.emplace_back(definition_event);
+    } else {
+      definition_events.emplace_back(std::make_shared<BufferSequencingEvent>());
+    }
   }
   se::Stream* tuple_table_stream = local_device->host_to_device_stream();
   if (on_device_shape.IsTuple()) {
@@ -698,6 +710,12 @@ StatusOr<std::unique_ptr<PjRtBuffer>> PjRtClient::BufferFromHostBuffer(
 
 StatusOr<std::unique_ptr<PjRtBuffer>> PjRtClient::CreateUninitializedBuffer(
     const Shape& shape, PjRtDevice* device) {
+  return CreateUninitializedBuffer(shape, device, nullptr);
+}
+
+StatusOr<std::unique_ptr<PjRtBuffer>> PjRtClient::CreateUninitializedBuffer(
+    const Shape& shape, PjRtDevice* device,
+    std::shared_ptr<BufferSequencingEvent> definition_event) {
   tensorflow::profiler::TraceMe traceme(
       "PjRtClient::CreateUninitializedBuffer");
   VLOG(2) << "PjRtClient::CreateUninitializedBuffer: shape: "
@@ -711,7 +729,8 @@ StatusOr<std::unique_ptr<PjRtBuffer>> PjRtClient::CreateUninitializedBuffer(
 
   return AllocateDestinationBuffer(compact_shape, device, local_device,
                                    /*copy_stream=*/nullptr,
-                                   /*is_uninitialized_create=*/true, this);
+                                   /*is_uninitialized_create=*/true, this,
+                                   definition_event);
 }
 
 StatusOr<std::unique_ptr<PjRtBuffer>> PjRtClient::BufferFromHostLiteral(
@@ -788,14 +807,15 @@ void PjRtClient::MakeCrossHostReceiveBuffers(
     return;
   }
   LocalDeviceState* local_device = local_device_or.ConsumeValueOrDie();
-
+  std::shared_ptr<BufferSequencingEvent> definition_event =
+      std::make_shared<BufferSequencingEvent>();
   std::vector<std::unique_ptr<PjRtBuffer>> buffers;
   buffers.reserve(shapes.size());
   for (const auto& shape : shapes) {
-    StatusOr<std::unique_ptr<PjRtBuffer>> buffer_or =
-        AllocateDestinationBuffer(shape, device, local_device,
-                                  /*copy_stream=*/nullptr,
-                                  /*is_uninitialized_create=*/false, this);
+    StatusOr<std::unique_ptr<PjRtBuffer>> buffer_or = AllocateDestinationBuffer(
+        shape, device, local_device,
+        /*copy_stream=*/nullptr,
+        /*is_uninitialized_create=*/false, this, definition_event);
     if (!buffer_or.ok()) {
       notifier(buffer_or.status());
       return;
@@ -803,7 +823,8 @@ void PjRtClient::MakeCrossHostReceiveBuffers(
     buffers.push_back(buffer_or.ConsumeValueOrDie());
   }
 
-  EnqueueCrossHostReceive(std::move(buffers), std::move(notifier));
+  EnqueueCrossHostReceive(std::move(buffers), std::move(definition_event),
+                          std::move(notifier));
 }
 
 // Transfer the given literal to the infeed queue of the given local device.
diff --git a/tensorflow/compiler/xla/pjrt/pjrt_client.h b/tensorflow/compiler/xla/pjrt/pjrt_client.h
index 38d2610ff93..ec695e05c44 100644
--- a/tensorflow/compiler/xla/pjrt/pjrt_client.h
+++ b/tensorflow/compiler/xla/pjrt/pjrt_client.h
@@ -248,8 +248,17 @@ class PjRtClient {
   virtual StatusOr<std::unique_ptr<PjRtExecutable>> Compile(
       const XlaComputation& computation, CompileOptions options);
 
+  // Creates a buffer on the device without initializing or copying any data.
+  // An optional `definition_event` may be speficied that can be used to
+  // ensure the buffer isn't referenced until some external mechanism has
+  // initialized the data.
+  // NOTE: The sequencing mechanism is not guaranteed to be supported by all
+  // future backends and so callers should avoid wherever possible.
   virtual StatusOr<std::unique_ptr<PjRtBuffer>> CreateUninitializedBuffer(
       const Shape& shape, PjRtDevice* device);
+  virtual StatusOr<std::unique_ptr<PjRtBuffer>> CreateUninitializedBuffer(
+      const Shape& shape, PjRtDevice* device,
+      std::shared_ptr<BufferSequencingEvent> definition_event);
 
   // Describes the semantics the caller to BufferFromHostBuffer expects from the
   // runtime, in a total order from most restrictive to least restrictive.
@@ -316,6 +325,7 @@ class PjRtClient {
   friend class PjRtBuffer;
   virtual void EnqueueCrossHostReceive(
       std::vector<std::unique_ptr<PjRtBuffer>>&& buffers,
+      std::shared_ptr<BufferSequencingEvent> definition_event,
       PjRtCrossHostRecvNotifier&& notifier) const {
     notifier(Unimplemented("Cross host receives not implemented."));
   }