diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IBurst.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IBurst.aidl
new file mode 100644
index 0000000..634f39e
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IBurst.aidl
@@ -0,0 +1,39 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+///////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+interface IBurst {
+  android.hardware.neuralnetworks.ExecutionResult executeSynchronously(in android.hardware.neuralnetworks.Request request, in long[] memoryIdentifierTokens, in boolean measureTiming, in long deadline, in long loopTimeoutDuration);
+  void releaseMemoryResource(in long memoryIdentifierToken);
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IPreparedModel.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IPreparedModel.aidl
index 5c54355..52882cd 100644
--- a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IPreparedModel.aidl
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IPreparedModel.aidl
@@ -36,6 +36,7 @@
 interface IPreparedModel {
   android.hardware.neuralnetworks.ExecutionResult executeSynchronously(in android.hardware.neuralnetworks.Request request, in boolean measureTiming, in long deadline, in long loopTimeoutDuration);
   android.hardware.neuralnetworks.FencedExecutionResult executeFenced(in android.hardware.neuralnetworks.Request request, in ParcelFileDescriptor[] waitFor, in boolean measureTiming, in long deadline, in long loopTimeoutDuration, in long duration);
+  android.hardware.neuralnetworks.IBurst configureExecutionBurst();
   const long DEFAULT_LOOP_TIMEOUT_DURATION_NS = 2000000000;
   const long MAXIMUM_LOOP_TIMEOUT_DURATION_NS = 15000000000;
 }
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/IBurst.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/IBurst.aidl
new file mode 100644
index 0000000..85d2a03
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/IBurst.aidl
@@ -0,0 +1,120 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.ErrorStatus;
+import android.hardware.neuralnetworks.ExecutionResult;
+import android.hardware.neuralnetworks.Request;
+
+/**
+ * IBurst represents a burst execution object.
+ *
+ * Burst executions are a sequence of executions of the same prepared model that occur in rapid
+ * succession, such as frames of a camera capture or successive audio samples. A burst object is
+ * used to control a set of burst executions, and to preserve resources between executions, enabling
+ * executions to have lower overhead. Burst objects enable some optimizations:
+ * (1) A burst object is created before a sequence of executions, and freed when the sequence has
+ *     ended. Because of this, the lifetime of the burst object hints to a driver how long it should
+ *     remain in a high performance state.
+ * (2) A burst object can preserve resources between executions. For example, a driver can map a
+ *     memory object on the first execution and cache the mapping in the burst object for reuse in
+ *     subsequent executions. Any cached resource can be released when the burst object is destroyed
+ *     or when the NNAPI runtime notifies the burst object that the resource is no longer required.
+ * (3) A burst object may be used for at most one execution at a time. This enables any transient
+ *     execution resources such as intermediate tensors to be allocated once when the burst object
+ *     is created and freed when the burst object is destroyed.
+ */
+@VintfStability
+interface IBurst {
+    /**
+     * Performs a synchronous execution on a burst object.
+     *
+     * The execution is performed synchronously with respect to the caller. executeSynchronously
+     * must verify the inputs to the function are correct, and the usages of memory pools allocated
+     * by IDevice::allocate are valid. If there is an error, executeSynchronously must immediately
+     * return a service specific exception with the appropriate ErrorStatus value. If the inputs to
+     * the function are valid and there is no error, executeSynchronously must perform the
+     * execution, and must not return until the execution is complete.
+     *
+     * The caller must not change the content of any data object referenced by 'request' (described
+     * by the {@link DataLocation} of a {@link RequestArgument}) until executeSynchronously returns.
+     * executeSynchronously must not change the content of any of the data objects corresponding to
+     * 'request' inputs.
+     *
+     * If the burst object was configured from a prepared model wherein all tensor operands have
+     * fully specified dimensions, and the inputs to the function are valid, and at execution time
+     * every operation's input operands have legal values, then the execution should complete
+     * successfully: there must be no failure unless the device itself is in a bad state.
+     *
+     * executeSynchronously may be called with an optional deadline. If the execution is not able to
+     * be completed before the provided deadline, the execution may be aborted, and either
+     * {@link ErrorStatus::MISSED_DEADLINE_TRANSIENT} or {@link
+     * ErrorStatus::MISSED_DEADLINE_PERSISTENT} may be returned. The error due to an abort must be
+     * sent the same way as other errors, described above.
+     *
+     * Only a single execution on a given burst object may be active at any time.
+     *
+     * @param request The input and output information on which the prepared model is to be
+     *                executed.
+     * @param memoryIdentifierTokens A list of tokens where each token is a non-negative number
+     *                               that uniquely identifies a memory object. Each memory
+     *                               identifier token corresponds to an element of request.pools. A
+     *                               value of -1 indicates no identity.
+     * @param measure Specifies whether or not to measure duration of the execution. The duration
+     *                runs from the time the driver sees the call to the executeSynchronously
+     *                function to the time the driver returns from the function.
+     * @param deadline The time by which the execution is expected to complete. The time is measured
+     *                 in nanoseconds since epoch of the steady clock (as from
+     *                 std::chrono::steady_clock). If the execution cannot be finished by the
+     *                 deadline, the execution may be aborted. Passing -1 means the deadline is
+     *                 omitted. Other negative values are invalid.
+     * @param loopTimeoutDuration The maximum amount of time in nanoseconds that should be spent
+     *                            executing a {@link OperationType::WHILE} operation. If a loop
+     *                            condition model does not output false within this duration, the
+     *                            execution must be aborted. If -1 is provided, the maximum amount
+     *                            of time is {@link DEFAULT_LOOP_TIMEOUT_DURATION_NS}. Other
+     *                            negative values are invalid. When provided, the duration must not
+     *                            exceed {@link MAXIMUM_LOOP_TIMEOUT_DURATION_NS}.
+     * @return ExecutionResult parcelable, containing the status of the execution, output shapes and
+     *     timing information.
+     * @throws ServiceSpecificException with one of the following ErrorStatus values:
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if there is an unspecified error
+     *     - INVALID_ARGUMENT if one of the input arguments is invalid
+     *     - MISSED_DEADLINE_* if the execution is aborted because it cannot be completed by the
+     *       deadline
+     *     - RESOURCE_EXHAUSTED_* if the task was aborted by the driver
+     */
+    ExecutionResult executeSynchronously(in Request request, in long[] memoryIdentifierTokens,
+            in boolean measureTiming, in long deadline, in long loopTimeoutDuration);
+
+    /**
+     * releaseMemoryResource is used by the client to signal to the service that a memory buffer
+     * corresponding to a slot number is no longer needed by the client, and any cached resources
+     * associated with that memory object may be released.
+     *
+     * The identifier tokens are unique to the burst object.
+     *
+     * @param memoryIdentifierToken Value uniquely identifying a memory object that is no longer
+     *                              used.
+     * @throws ServiceSpecificException with one of the following ErrorStatus values:
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if there is an unspecified error
+     *     - INVALID_ARGUMENT if one of the input arguments is invalid
+     */
+    void releaseMemoryResource(in long memoryIdentifierToken);
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/IPreparedModel.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/IPreparedModel.aidl
index 0240e3c..2a9757b 100644
--- a/neuralnetworks/aidl/android/hardware/neuralnetworks/IPreparedModel.aidl
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/IPreparedModel.aidl
@@ -20,6 +20,7 @@
 import android.hardware.neuralnetworks.ErrorStatus;
 import android.hardware.neuralnetworks.ExecutionResult;
 import android.hardware.neuralnetworks.FencedExecutionResult;
+import android.hardware.neuralnetworks.IBurst;
 import android.hardware.neuralnetworks.Request;
 
 /**
@@ -166,4 +167,22 @@
     FencedExecutionResult executeFenced(in Request request, in ParcelFileDescriptor[] waitFor,
             in boolean measureTiming, in long deadline, in long loopTimeoutDuration,
             in long duration);
+
+    /**
+     * Configure a Burst object used to execute multiple inferences on a prepared model in rapid
+     * succession.
+     *
+     * If the prepared model was prepared from a model wherein all tensor operands have fully
+     * specified dimensions, and a valid serialized Request is sent to the Burst for execution, and
+     * at execution time every operation's input operands have legal values, then the execution
+     * should complete successfully (ErrorStatus::NONE): There must be no failure unless the device
+     * itself is in a bad state.
+     *
+     * @return burst Execution burst controller object.
+     * @throws ServiceSpecificException with one of the following ErrorStatus values:
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if there is an unspecified error
+     *     - RESOURCE_EXHAUSTED_* if the task was aborted by the driver
+     */
+    IBurst configureExecutionBurst();
 }