diff --git a/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Conversions.h b/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Conversions.h
index 78433a7..477b311 100644
--- a/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Conversions.h
+++ b/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Conversions.h
@@ -112,11 +112,15 @@
 GeneralResult<Request> convert(const aidl_hal::Request& request);
 GeneralResult<Timing> convert(const aidl_hal::Timing& timing);
 GeneralResult<SharedHandle> convert(const ndk::ScopedFileDescriptor& handle);
+GeneralResult<BufferDesc> convert(const aidl_hal::BufferDesc& bufferDesc);
 
 GeneralResult<std::vector<Extension>> convert(const std::vector<aidl_hal::Extension>& extension);
 GeneralResult<std::vector<SharedMemory>> convert(const std::vector<aidl_hal::Memory>& memories);
 GeneralResult<std::vector<OutputShape>> convert(
         const std::vector<aidl_hal::OutputShape>& outputShapes);
+GeneralResult<std::vector<SharedHandle>> convert(
+        const std::vector<ndk::ScopedFileDescriptor>& handles);
+GeneralResult<std::vector<BufferRole>> convert(const std::vector<aidl_hal::BufferRole>& roles);
 
 GeneralResult<std::vector<uint32_t>> toUnsigned(const std::vector<int32_t>& vec);
 
@@ -129,6 +133,7 @@
 nn::GeneralResult<std::vector<uint8_t>> unvalidatedConvert(const nn::CacheToken& cacheToken);
 nn::GeneralResult<BufferDesc> unvalidatedConvert(const nn::BufferDesc& bufferDesc);
 nn::GeneralResult<BufferRole> unvalidatedConvert(const nn::BufferRole& bufferRole);
+nn::GeneralResult<DeviceType> unvalidatedConvert(const nn::DeviceType& deviceType);
 nn::GeneralResult<bool> unvalidatedConvert(const nn::MeasureTiming& measureTiming);
 nn::GeneralResult<Memory> unvalidatedConvert(const nn::SharedMemory& memory);
 nn::GeneralResult<OutputShape> unvalidatedConvert(const nn::OutputShape& outputShape);
@@ -154,14 +159,16 @@
 nn::GeneralResult<RequestArgument> unvalidatedConvert(const nn::Request::Argument& requestArgument);
 nn::GeneralResult<RequestMemoryPool> unvalidatedConvert(const nn::Request::MemoryPool& memoryPool);
 nn::GeneralResult<Timing> unvalidatedConvert(const nn::Timing& timing);
-nn::GeneralResult<int64_t> unvalidatedConvert(const nn::Duration& duration);
 nn::GeneralResult<int64_t> unvalidatedConvert(const nn::OptionalDuration& optionalDuration);
 nn::GeneralResult<int64_t> unvalidatedConvert(const nn::OptionalTimePoint& optionalTimePoint);
 nn::GeneralResult<ndk::ScopedFileDescriptor> unvalidatedConvert(const nn::SyncFence& syncFence);
 nn::GeneralResult<ndk::ScopedFileDescriptor> unvalidatedConvert(const nn::SharedHandle& handle);
+nn::GeneralResult<Capabilities> unvalidatedConvert(const nn::Capabilities& capabilities);
+nn::GeneralResult<Extension> unvalidatedConvert(const nn::Extension& extension);
 
 nn::GeneralResult<std::vector<uint8_t>> convert(const nn::CacheToken& cacheToken);
 nn::GeneralResult<BufferDesc> convert(const nn::BufferDesc& bufferDesc);
+nn::GeneralResult<DeviceType> convert(const nn::DeviceType& deviceType);
 nn::GeneralResult<bool> convert(const nn::MeasureTiming& measureTiming);
 nn::GeneralResult<Memory> convert(const nn::SharedMemory& memory);
 nn::GeneralResult<ErrorStatus> convert(const nn::ErrorStatus& errorStatus);
@@ -172,6 +179,8 @@
 nn::GeneralResult<Timing> convert(const nn::Timing& timing);
 nn::GeneralResult<int64_t> convert(const nn::OptionalDuration& optionalDuration);
 nn::GeneralResult<int64_t> convert(const nn::OptionalTimePoint& optionalTimePoint);
+nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities);
+nn::GeneralResult<Extension> convert(const nn::Extension& extension);
 
 nn::GeneralResult<std::vector<BufferRole>> convert(const std::vector<nn::BufferRole>& bufferRoles);
 nn::GeneralResult<std::vector<OutputShape>> convert(
@@ -180,6 +189,7 @@
         const std::vector<nn::SharedHandle>& handles);
 nn::GeneralResult<std::vector<ndk::ScopedFileDescriptor>> convert(
         const std::vector<nn::SyncFence>& syncFences);
+nn::GeneralResult<std::vector<Extension>> convert(const std::vector<nn::Extension>& extensions);
 
 nn::GeneralResult<std::vector<int32_t>> toSigned(const std::vector<uint32_t>& vec);
 
diff --git a/neuralnetworks/aidl/utils/src/Conversions.cpp b/neuralnetworks/aidl/utils/src/Conversions.cpp
index 45628c8..113d2da 100644
--- a/neuralnetworks/aidl/utils/src/Conversions.cpp
+++ b/neuralnetworks/aidl/utils/src/Conversions.cpp
@@ -551,6 +551,10 @@
     return validatedConvert(handle);
 }
 
+GeneralResult<BufferDesc> convert(const aidl_hal::BufferDesc& bufferDesc) {
+    return validatedConvert(bufferDesc);
+}
+
 GeneralResult<std::vector<Extension>> convert(const std::vector<aidl_hal::Extension>& extension) {
     return validatedConvert(extension);
 }
@@ -564,6 +568,15 @@
     return validatedConvert(outputShapes);
 }
 
+GeneralResult<std::vector<SharedHandle>> convert(
+        const std::vector<ndk::ScopedFileDescriptor>& handles) {
+    return validatedConvert(handles);
+}
+
+GeneralResult<std::vector<BufferRole>> convert(const std::vector<aidl_hal::BufferRole>& roles) {
+    return validatedConvert(roles);
+}
+
 GeneralResult<std::vector<uint32_t>> toUnsigned(const std::vector<int32_t>& vec) {
     if (!std::all_of(vec.begin(), vec.end(), [](int32_t v) { return v >= 0; })) {
         return NN_ERROR() << "Negative value passed to conversion from signed to unsigned";
@@ -576,42 +589,7 @@
 namespace aidl::android::hardware::neuralnetworks::utils {
 namespace {
 
-template <typename Input>
-using UnvalidatedConvertOutput =
-        std::decay_t<decltype(unvalidatedConvert(std::declval<Input>()).value())>;
-
-template <typename Type>
-nn::GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> unvalidatedConvertVec(
-        const std::vector<Type>& arguments) {
-    std::vector<UnvalidatedConvertOutput<Type>> halObject;
-    halObject.reserve(arguments.size());
-    for (const auto& argument : arguments) {
-        halObject.push_back(NN_TRY(unvalidatedConvert(argument)));
-    }
-    return halObject;
-}
-
-template <typename Type>
-nn::GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> unvalidatedConvert(
-        const std::vector<Type>& arguments) {
-    return unvalidatedConvertVec(arguments);
-}
-
-template <typename Type>
-nn::GeneralResult<UnvalidatedConvertOutput<Type>> validatedConvert(const Type& canonical) {
-    NN_TRY(compliantVersion(canonical));
-    return utils::unvalidatedConvert(canonical);
-}
-
-template <typename Type>
-nn::GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> validatedConvert(
-        const std::vector<Type>& arguments) {
-    std::vector<UnvalidatedConvertOutput<Type>> halObject(arguments.size());
-    for (size_t i = 0; i < arguments.size(); ++i) {
-        halObject[i] = NN_TRY(validatedConvert(arguments[i]));
-    }
-    return halObject;
-}
+using utils::unvalidatedConvert;
 
 // Helper template for std::visit
 template <class... Ts>
@@ -721,6 +699,74 @@
             operator nn::GeneralResult<Memory>();
 }
 
+nn::GeneralResult<PerformanceInfo> unvalidatedConvert(
+        const nn::Capabilities::PerformanceInfo& info) {
+    return PerformanceInfo{.execTime = info.execTime, .powerUsage = info.powerUsage};
+}
+
+nn::GeneralResult<OperandPerformance> unvalidatedConvert(
+        const nn::Capabilities::OperandPerformance& operandPerformance) {
+    return OperandPerformance{.type = NN_TRY(unvalidatedConvert(operandPerformance.type)),
+                              .info = NN_TRY(unvalidatedConvert(operandPerformance.info))};
+}
+
+nn::GeneralResult<std::vector<OperandPerformance>> unvalidatedConvert(
+        const nn::Capabilities::OperandPerformanceTable& table) {
+    std::vector<OperandPerformance> operandPerformances;
+    operandPerformances.reserve(table.asVector().size());
+    for (const auto& operandPerformance : table.asVector()) {
+        operandPerformances.push_back(NN_TRY(unvalidatedConvert(operandPerformance)));
+    }
+    return operandPerformances;
+}
+
+nn::GeneralResult<ExtensionOperandTypeInformation> unvalidatedConvert(
+        const nn::Extension::OperandTypeInformation& info) {
+    return ExtensionOperandTypeInformation{.type = info.type,
+                                           .isTensor = info.isTensor,
+                                           .byteSize = static_cast<int32_t>(info.byteSize)};
+}
+
+nn::GeneralResult<int64_t> unvalidatedConvert(const nn::Duration& duration) {
+    if (duration < nn::Duration::zero()) {
+        return NN_ERROR() << "Unable to convert invalid (negative) duration";
+    }
+    constexpr std::chrono::nanoseconds::rep kIntMax = std::numeric_limits<int64_t>::max();
+    const auto count = duration.count();
+    return static_cast<int64_t>(std::min(count, kIntMax));
+}
+
+template <typename Input>
+using UnvalidatedConvertOutput =
+        std::decay_t<decltype(unvalidatedConvert(std::declval<Input>()).value())>;
+
+template <typename Type>
+nn::GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> unvalidatedConvert(
+        const std::vector<Type>& arguments) {
+    std::vector<UnvalidatedConvertOutput<Type>> halObject;
+    halObject.reserve(arguments.size());
+    for (const auto& argument : arguments) {
+        halObject.push_back(NN_TRY(unvalidatedConvert(argument)));
+    }
+    return halObject;
+}
+
+template <typename Type>
+nn::GeneralResult<UnvalidatedConvertOutput<Type>> validatedConvert(const Type& canonical) {
+    NN_TRY(compliantVersion(canonical));
+    return utils::unvalidatedConvert(canonical);
+}
+
+template <typename Type>
+nn::GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> validatedConvert(
+        const std::vector<Type>& arguments) {
+    std::vector<UnvalidatedConvertOutput<Type>> halObject(arguments.size());
+    for (size_t i = 0; i < arguments.size(); ++i) {
+        halObject[i] = NN_TRY(validatedConvert(arguments[i]));
+    }
+    return halObject;
+}
+
 }  // namespace
 
 nn::GeneralResult<std::vector<uint8_t>> unvalidatedConvert(const nn::CacheToken& cacheToken) {
@@ -743,6 +789,19 @@
     };
 }
 
+nn::GeneralResult<DeviceType> unvalidatedConvert(const nn::DeviceType& deviceType) {
+    switch (deviceType) {
+        case nn::DeviceType::UNKNOWN:
+            break;
+        case nn::DeviceType::OTHER:
+        case nn::DeviceType::CPU:
+        case nn::DeviceType::GPU:
+        case nn::DeviceType::ACCELERATOR:
+            return static_cast<DeviceType>(deviceType);
+    }
+    return NN_ERROR() << "Invalid DeviceType " << deviceType;
+}
+
 nn::GeneralResult<bool> unvalidatedConvert(const nn::MeasureTiming& measureTiming) {
     return measureTiming == nn::MeasureTiming::YES;
 }
@@ -956,15 +1015,6 @@
     };
 }
 
-nn::GeneralResult<int64_t> unvalidatedConvert(const nn::Duration& duration) {
-    if (duration < nn::Duration::zero()) {
-        return NN_ERROR() << "Unable to convert invalid (negative) duration";
-    }
-    constexpr std::chrono::nanoseconds::rep kIntMax = std::numeric_limits<int64_t>::max();
-    const auto count = duration.count();
-    return static_cast<int64_t>(std::min(count, kIntMax));
-}
-
 nn::GeneralResult<int64_t> unvalidatedConvert(const nn::OptionalDuration& optionalDuration) {
     if (!optionalDuration.has_value()) {
         return kNoTiming;
@@ -989,6 +1039,23 @@
     return ndk::ScopedFileDescriptor(duplicatedFd.release());
 }
 
+nn::GeneralResult<Capabilities> unvalidatedConvert(const nn::Capabilities& capabilities) {
+    return Capabilities{
+            .relaxedFloat32toFloat16PerformanceTensor = NN_TRY(
+                    unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor)),
+            .relaxedFloat32toFloat16PerformanceScalar = NN_TRY(
+                    unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar)),
+            .operandPerformance = NN_TRY(unvalidatedConvert(capabilities.operandPerformance)),
+            .ifPerformance = NN_TRY(unvalidatedConvert(capabilities.ifPerformance)),
+            .whilePerformance = NN_TRY(unvalidatedConvert(capabilities.whilePerformance)),
+    };
+}
+
+nn::GeneralResult<Extension> unvalidatedConvert(const nn::Extension& extension) {
+    return Extension{.name = extension.name,
+                     .operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes))};
+}
+
 nn::GeneralResult<std::vector<uint8_t>> convert(const nn::CacheToken& cacheToken) {
     return validatedConvert(cacheToken);
 }
@@ -997,6 +1064,10 @@
     return validatedConvert(bufferDesc);
 }
 
+nn::GeneralResult<DeviceType> convert(const nn::DeviceType& deviceType) {
+    return validatedConvert(deviceType);
+}
+
 nn::GeneralResult<bool> convert(const nn::MeasureTiming& measureTiming) {
     return validatedConvert(measureTiming);
 }
@@ -1037,6 +1108,14 @@
     return validatedConvert(outputShapes);
 }
 
+nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities) {
+    return validatedConvert(capabilities);
+}
+
+nn::GeneralResult<Extension> convert(const nn::Extension& extension) {
+    return validatedConvert(extension);
+}
+
 nn::GeneralResult<std::vector<BufferRole>> convert(const std::vector<nn::BufferRole>& bufferRoles) {
     return validatedConvert(bufferRoles);
 }
@@ -1056,6 +1135,10 @@
     return validatedConvert(syncFences);
 }
 
+nn::GeneralResult<std::vector<Extension>> convert(const std::vector<nn::Extension>& extensions) {
+    return validatedConvert(extensions);
+}
+
 nn::GeneralResult<std::vector<int32_t>> toSigned(const std::vector<uint32_t>& vec) {
     if (!std::all_of(vec.begin(), vec.end(),
                      [](uint32_t v) { return v <= std::numeric_limits<int32_t>::max(); })) {
diff --git a/neuralnetworks/utils/adapter/aidl/Android.bp b/neuralnetworks/utils/adapter/aidl/Android.bp
new file mode 100644
index 0000000..8269a3d
--- /dev/null
+++ b/neuralnetworks/utils/adapter/aidl/Android.bp
@@ -0,0 +1,42 @@
+//
+// 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 {
+    // See: http://go/android-license-faq
+    // A large-scale-change added 'default_applicable_licenses' to import
+    // all of the 'license_kinds' from "hardware_interfaces_license"
+    // to get the below license kinds:
+    //   SPDX-license-identifier-Apache-2.0
+    default_applicable_licenses: ["hardware_interfaces_license"],
+}
+
+cc_library_static {
+    name: "neuralnetworks_utils_hal_adapter_aidl",
+    defaults: [
+        "neuralnetworks_use_latest_utils_hal_aidl",
+        "neuralnetworks_utils_defaults",
+    ],
+    srcs: ["src/*"],
+    local_include_dirs: ["include/nnapi/hal/aidl/"],
+    export_include_dirs: ["include"],
+    static_libs: [
+        "neuralnetworks_types",
+        "neuralnetworks_utils_hal_common",
+    ],
+    shared_libs: [
+        "libbinder_ndk",
+    ],
+}
diff --git a/neuralnetworks/utils/adapter/include/nnapi/hal/Adapter.h b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Adapter.h
similarity index 63%
copy from neuralnetworks/utils/adapter/include/nnapi/hal/Adapter.h
copy to neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Adapter.h
index da00a09..4c0b328 100644
--- a/neuralnetworks/utils/adapter/include/nnapi/hal/Adapter.h
+++ b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Adapter.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (C) 2020 The Android Open Source Project
+ * 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.
@@ -14,20 +14,20 @@
  * limitations under the License.
  */
 
-#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_ADAPTER_H
-#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_ADAPTER_H
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_ADAPTER_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_ADAPTER_H
 
-#include <android/hardware/neuralnetworks/1.3/IDevice.h>
+#include <aidl/android/hardware/neuralnetworks/BnDevice.h>
 #include <nnapi/IDevice.h>
 #include <nnapi/Types.h>
-#include <sys/types.h>
+
 #include <functional>
 #include <memory>
 
-// See hardware/interfaces/neuralnetworks/utils/README.md for more information on HIDL interface
-// lifetimes across processes and for protecting asynchronous calls across HIDL.
+// See hardware/interfaces/neuralnetworks/utils/README.md for more information on AIDL interface
+// lifetimes across processes and for protecting asynchronous calls across AIDL.
 
-namespace android::hardware::neuralnetworks::adapter {
+namespace aidl::android::hardware::neuralnetworks::adapter {
 
 /**
  * A self-contained unit of work to be executed.
@@ -37,25 +37,26 @@
 /**
  * A type-erased executor which executes a task asynchronously.
  *
- * This executor is also provided with an Application ID (Android User ID) and an optional deadline
- * for when the caller expects is the upper bound for the amount of time to complete the task.
+ * This executor is also provided an optional deadline for when the caller expects is the upper
+ * bound for the amount of time to complete the task. If needed, the Executor can retrieve the
+ * Application ID (Android User ID) by calling AIBinder_getCallingUid in android/binder_ibinder.h.
  */
-using Executor = std::function<void(Task, uid_t, nn::OptionalTimePoint)>;
+using Executor = std::function<void(Task, ::android::nn::OptionalTimePoint)>;
 
 /**
- * Adapt an NNAPI canonical interface object to a HIDL NN HAL interface object.
+ * Adapt an NNAPI canonical interface object to a AIDL NN HAL interface object.
  *
  * The IPreparedModel object created from IDevice::prepareModel or IDevice::preparedModelFromCache
  * must return "const nn::Model*" from IPreparedModel::getUnderlyingResource().
  *
  * @param device NNAPI canonical IDevice interface object to be adapted.
  * @param executor Type-erased executor to handle executing tasks asynchronously.
- * @return HIDL NN HAL IDevice interface object.
+ * @return AIDL NN HAL IDevice interface object.
  */
-sp<V1_3::IDevice> adapt(nn::SharedDevice device, Executor executor);
+std::shared_ptr<BnDevice> adapt(::android::nn::SharedDevice device, Executor executor);
 
 /**
- * Adapt an NNAPI canonical interface object to a HIDL NN HAL interface object.
+ * Adapt an NNAPI canonical interface object to a AIDL NN HAL interface object.
  *
  * The IPreparedModel object created from IDevice::prepareModel or IDevice::preparedModelFromCache
  * must return "const nn::Model*" from IPreparedModel::getUnderlyingResource().
@@ -63,10 +64,10 @@
  * This function uses a default executor, which will execute tasks from a detached thread.
  *
  * @param device NNAPI canonical IDevice interface object to be adapted.
- * @return HIDL NN HAL IDevice interface object.
+ * @return AIDL NN HAL IDevice interface object.
  */
-sp<V1_3::IDevice> adapt(nn::SharedDevice device);
+std::shared_ptr<BnDevice> adapt(::android::nn::SharedDevice device);
 
-}  // namespace android::hardware::neuralnetworks::adapter
+}  // namespace aidl::android::hardware::neuralnetworks::adapter
 
-#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_ADAPTER_H
+#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_ADAPTER_H
diff --git a/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Buffer.h b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Buffer.h
new file mode 100644
index 0000000..701e43e
--- /dev/null
+++ b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Buffer.h
@@ -0,0 +1,47 @@
+/*
+ * 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_BUFFER_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_BUFFER_H
+
+#include <aidl/android/hardware/neuralnetworks/BnBuffer.h>
+#include <aidl/android/hardware/neuralnetworks/Memory.h>
+#include <android/binder_auto_utils.h>
+#include <nnapi/IBuffer.h>
+
+#include <memory>
+#include <vector>
+
+// See hardware/interfaces/neuralnetworks/utils/README.md for more information on AIDL interface
+// lifetimes across processes and for protecting asynchronous calls across AIDL.
+
+namespace aidl::android::hardware::neuralnetworks::adapter {
+
+// Class that adapts nn::IBuffer to BnBuffer.
+class Buffer : public BnBuffer {
+  public:
+    explicit Buffer(::android::nn::SharedBuffer buffer);
+
+    ndk::ScopedAStatus copyFrom(const Memory& src, const std::vector<int32_t>& dimensions) override;
+    ndk::ScopedAStatus copyTo(const Memory& dst) override;
+
+  private:
+    const ::android::nn::SharedBuffer kBuffer;
+};
+
+}  // namespace aidl::android::hardware::neuralnetworks::adapter
+
+#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_BUFFER_H
diff --git a/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Burst.h b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Burst.h
new file mode 100644
index 0000000..f2687c4
--- /dev/null
+++ b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Burst.h
@@ -0,0 +1,72 @@
+/*
+ * 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_BURST_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_BURST_H
+
+#include <aidl/android/hardware/neuralnetworks/BnBurst.h>
+#include <aidl/android/hardware/neuralnetworks/ExecutionResult.h>
+#include <aidl/android/hardware/neuralnetworks/Request.h>
+#include <android-base/thread_annotations.h>
+#include <android/binder_auto_utils.h>
+#include <nnapi/IBurst.h>
+#include <nnapi/Types.h>
+
+#include <memory>
+#include <mutex>
+#include <unordered_map>
+#include <vector>
+
+// See hardware/interfaces/neuralnetworks/utils/README.md for more information on AIDL interface
+// lifetimes across processes and for protecting asynchronous calls across AIDL.
+
+namespace aidl::android::hardware::neuralnetworks::adapter {
+
+// Class that adapts nn::Burst to BnBurst.
+class Burst : public BnBurst {
+  public:
+    // Precondition: burst != nullptr
+    explicit Burst(::android::nn::SharedBurst burst);
+
+    ndk::ScopedAStatus executeSynchronously(const Request& request,
+                                            const std::vector<int64_t>& memoryIdentifierTokens,
+                                            bool measureTiming, int64_t deadlineNs,
+                                            int64_t loopTimeoutDurationNs,
+                                            ExecutionResult* executionResult) override;
+    ndk::ScopedAStatus releaseMemoryResource(int64_t memoryIdentifierToken) override;
+
+    class ThreadSafeMemoryCache {
+      public:
+        using Value =
+                std::pair<::android::nn::SharedMemory, ::android::nn::IBurst::OptionalCacheHold>;
+
+        Value add(int64_t token, const ::android::nn::SharedMemory& memory,
+                  const ::android::nn::IBurst& burst) const;
+        void remove(int64_t token) const;
+
+      private:
+        mutable std::mutex mMutex;
+        mutable std::unordered_map<int64_t, Value> mCache GUARDED_BY(mMutex);
+    };
+
+  private:
+    const ::android::nn::SharedBurst kBurst;
+    const ThreadSafeMemoryCache kMemoryCache;
+};
+
+}  // namespace aidl::android::hardware::neuralnetworks::adapter
+
+#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_BURST_H
diff --git a/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Device.h b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Device.h
new file mode 100644
index 0000000..aa29d63
--- /dev/null
+++ b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Device.h
@@ -0,0 +1,83 @@
+/*
+ * 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_DEVICE_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_DEVICE_H
+
+#include "nnapi/hal/aidl/Adapter.h"
+
+#include <aidl/android/hardware/neuralnetworks/BnDevice.h>
+#include <aidl/android/hardware/neuralnetworks/BufferDesc.h>
+#include <aidl/android/hardware/neuralnetworks/BufferRole.h>
+#include <aidl/android/hardware/neuralnetworks/Capabilities.h>
+#include <aidl/android/hardware/neuralnetworks/DeviceBuffer.h>
+#include <aidl/android/hardware/neuralnetworks/DeviceType.h>
+#include <aidl/android/hardware/neuralnetworks/ExecutionPreference.h>
+#include <aidl/android/hardware/neuralnetworks/Extension.h>
+#include <aidl/android/hardware/neuralnetworks/IPreparedModelCallback.h>
+#include <aidl/android/hardware/neuralnetworks/IPreparedModelParcel.h>
+#include <aidl/android/hardware/neuralnetworks/Model.h>
+#include <aidl/android/hardware/neuralnetworks/NumberOfCacheFiles.h>
+#include <aidl/android/hardware/neuralnetworks/Priority.h>
+#include <android/binder_auto_utils.h>
+#include <nnapi/IDevice.h>
+
+#include <memory>
+#include <string>
+#include <vector>
+
+// See hardware/interfaces/neuralnetworks/utils/README.md for more information on AIDL interface
+// lifetimes across processes and for protecting asynchronous calls across AIDL.
+
+namespace aidl::android::hardware::neuralnetworks::adapter {
+
+// Class that adapts nn::IDevice to BnDevice.
+class Device : public BnDevice {
+  public:
+    Device(::android::nn::SharedDevice device, Executor executor);
+
+    ndk::ScopedAStatus allocate(const BufferDesc& desc,
+                                const std::vector<IPreparedModelParcel>& preparedModels,
+                                const std::vector<BufferRole>& inputRoles,
+                                const std::vector<BufferRole>& outputRoles,
+                                DeviceBuffer* buffer) override;
+    ndk::ScopedAStatus getCapabilities(Capabilities* capabilities) override;
+    ndk::ScopedAStatus getNumberOfCacheFilesNeeded(NumberOfCacheFiles* numberOfCacheFiles) override;
+    ndk::ScopedAStatus getSupportedExtensions(std::vector<Extension>* extensions) override;
+    ndk::ScopedAStatus getSupportedOperations(const Model& model,
+                                              std::vector<bool>* supported) override;
+    ndk::ScopedAStatus getType(DeviceType* deviceType) override;
+    ndk::ScopedAStatus getVersionString(std::string* version) override;
+    ndk::ScopedAStatus prepareModel(
+            const Model& model, ExecutionPreference preference, Priority priority,
+            int64_t deadlineNs, const std::vector<ndk::ScopedFileDescriptor>& modelCache,
+            const std::vector<ndk::ScopedFileDescriptor>& dataCache,
+            const std::vector<uint8_t>& token,
+            const std::shared_ptr<IPreparedModelCallback>& callback) override;
+    ndk::ScopedAStatus prepareModelFromCache(
+            int64_t deadlineNs, const std::vector<ndk::ScopedFileDescriptor>& modelCache,
+            const std::vector<ndk::ScopedFileDescriptor>& dataCache,
+            const std::vector<uint8_t>& token,
+            const std::shared_ptr<IPreparedModelCallback>& callback) override;
+
+  protected:
+    const ::android::nn::SharedDevice kDevice;
+    const Executor kExecutor;
+};
+
+}  // namespace aidl::android::hardware::neuralnetworks::adapter
+
+#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_DEVICE_H
diff --git a/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/PreparedModel.h b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/PreparedModel.h
new file mode 100644
index 0000000..93e0427
--- /dev/null
+++ b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/PreparedModel.h
@@ -0,0 +1,62 @@
+/*
+ * 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_PREPARED_MDOEL_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_PREPARED_MDOEL_H
+
+#include "nnapi/hal/aidl/Adapter.h"
+
+#include <aidl/android/hardware/neuralnetworks/BnPreparedModel.h>
+#include <aidl/android/hardware/neuralnetworks/ExecutionResult.h>
+#include <aidl/android/hardware/neuralnetworks/FencedExecutionResult.h>
+#include <aidl/android/hardware/neuralnetworks/IBurst.h>
+#include <aidl/android/hardware/neuralnetworks/Request.h>
+#include <android/binder_auto_utils.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Types.h>
+
+#include <memory>
+#include <vector>
+
+// See hardware/interfaces/neuralnetworks/utils/README.md for more information on AIDL interface
+// lifetimes across processes and for protecting asynchronous calls across AIDL.
+
+namespace aidl::android::hardware::neuralnetworks::adapter {
+
+// Class that adapts nn::IPreparedModel to BnPreparedModel.
+class PreparedModel : public BnPreparedModel {
+  public:
+    explicit PreparedModel(::android::nn::SharedPreparedModel preparedModel);
+
+    ndk::ScopedAStatus executeSynchronously(const Request& request, bool measureTiming,
+                                            int64_t deadlineNs, int64_t loopTimeoutDurationNs,
+                                            ExecutionResult* executionResult) override;
+    ndk::ScopedAStatus executeFenced(const Request& request,
+                                     const std::vector<ndk::ScopedFileDescriptor>& waitFor,
+                                     bool measureTiming, int64_t deadlineNs,
+                                     int64_t loopTimeoutDurationNs, int64_t durationNs,
+                                     FencedExecutionResult* executionResult) override;
+    ndk::ScopedAStatus configureExecutionBurst(std::shared_ptr<IBurst>* burst) override;
+
+    ::android::nn::SharedPreparedModel getUnderlyingPreparedModel() const;
+
+  protected:
+    const ::android::nn::SharedPreparedModel kPreparedModel;
+};
+
+}  // namespace aidl::android::hardware::neuralnetworks::adapter
+
+#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_PREPARED_MDOEL_H
diff --git a/neuralnetworks/utils/adapter/aidl/src/Adapter.cpp b/neuralnetworks/utils/adapter/aidl/src/Adapter.cpp
new file mode 100644
index 0000000..d0b56e8
--- /dev/null
+++ b/neuralnetworks/utils/adapter/aidl/src/Adapter.cpp
@@ -0,0 +1,46 @@
+/*
+ * 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.
+ */
+
+#include "Adapter.h"
+
+#include "Device.h"
+
+#include <aidl/android/hardware/neuralnetworks/BnDevice.h>
+#include <android/binder_interface_utils.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/Types.h>
+
+#include <functional>
+#include <memory>
+#include <thread>
+
+// See hardware/interfaces/neuralnetworks/utils/README.md for more information on AIDL interface
+// lifetimes across processes and for protecting asynchronous calls across AIDL.
+
+namespace aidl::android::hardware::neuralnetworks::adapter {
+
+std::shared_ptr<BnDevice> adapt(::android::nn::SharedDevice device, Executor executor) {
+    return ndk::SharedRefBase::make<Device>(std::move(device), std::move(executor));
+}
+
+std::shared_ptr<BnDevice> adapt(::android::nn::SharedDevice device) {
+    Executor defaultExecutor = [](Task task, ::android::nn::OptionalTimePoint /*deadline*/) {
+        std::thread(std::move(task)).detach();
+    };
+    return adapt(std::move(device), std::move(defaultExecutor));
+}
+
+}  // namespace aidl::android::hardware::neuralnetworks::adapter
diff --git a/neuralnetworks/utils/adapter/aidl/src/Buffer.cpp b/neuralnetworks/utils/adapter/aidl/src/Buffer.cpp
new file mode 100644
index 0000000..c15ab65
--- /dev/null
+++ b/neuralnetworks/utils/adapter/aidl/src/Buffer.cpp
@@ -0,0 +1,88 @@
+/*
+ * 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.
+ */
+
+#include "Buffer.h"
+
+#include <aidl/android/hardware/neuralnetworks/BnBuffer.h>
+#include <aidl/android/hardware/neuralnetworks/Memory.h>
+#include <android-base/logging.h>
+#include <android/binder_auto_utils.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/aidl/Conversions.h>
+
+namespace aidl::android::hardware::neuralnetworks::adapter {
+namespace {
+
+template <typename Type>
+auto convertInput(const Type& object) -> decltype(nn::convert(std::declval<Type>())) {
+    auto result = nn::convert(object);
+    if (!result.has_value()) {
+        result.error().code = nn::ErrorStatus::INVALID_ARGUMENT;
+    }
+    return result;
+}
+
+nn::GeneralResult<std::vector<uint32_t>> inputToUnsigned(const std::vector<int32_t>& dims) {
+    auto result = nn::toUnsigned(dims);
+    if (!result.has_value()) {
+        result.error().code = nn::ErrorStatus::INVALID_ARGUMENT;
+    }
+    return result;
+}
+
+nn::GeneralResult<void> copyTo(const nn::IBuffer& buffer, const Memory& dst) {
+    const auto nnDst = NN_TRY(convertInput(dst));
+    return buffer.copyTo(nnDst);
+}
+
+nn::GeneralResult<void> copyFrom(const nn::IBuffer& buffer, const Memory& src,
+                                 const std::vector<int32_t>& dimensions) {
+    const auto nnSrc = NN_TRY(convertInput(src));
+    const auto nnDims = NN_TRY(inputToUnsigned(dimensions));
+    return buffer.copyFrom(nnSrc, nnDims);
+}
+
+}  // namespace
+
+Buffer::Buffer(nn::SharedBuffer buffer) : kBuffer(std::move(buffer)) {
+    CHECK(kBuffer != nullptr);
+}
+
+ndk::ScopedAStatus Buffer::copyTo(const Memory& dst) {
+    const auto result = adapter::copyTo(*kBuffer, dst);
+    if (!result.has_value()) {
+        const auto& [message, code] = result.error();
+        const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE);
+        return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage(
+                static_cast<int32_t>(aidlCode), message.c_str());
+    }
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Buffer::copyFrom(const Memory& src, const std::vector<int32_t>& dimensions) {
+    const auto result = adapter::copyFrom(*kBuffer, src, dimensions);
+    if (!result.has_value()) {
+        const auto& [message, code] = result.error();
+        const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE);
+        return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage(
+                static_cast<int32_t>(aidlCode), message.c_str());
+    }
+    return ndk::ScopedAStatus::ok();
+}
+
+}  // namespace aidl::android::hardware::neuralnetworks::adapter
diff --git a/neuralnetworks/utils/adapter/aidl/src/Burst.cpp b/neuralnetworks/utils/adapter/aidl/src/Burst.cpp
new file mode 100644
index 0000000..4fabb20
--- /dev/null
+++ b/neuralnetworks/utils/adapter/aidl/src/Burst.cpp
@@ -0,0 +1,179 @@
+/*
+ * 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.
+ */
+
+#include "Burst.h"
+
+#include <android-base/logging.h>
+#include <android-base/thread_annotations.h>
+#include <android/binder_auto_utils.h>
+#include <nnapi/IBurst.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/Validation.h>
+#include <nnapi/hal/aidl/Conversions.h>
+#include <nnapi/hal/aidl/Utils.h>
+
+#include <algorithm>
+#include <chrono>
+#include <memory>
+#include <mutex>
+#include <unordered_map>
+#include <utility>
+#include <variant>
+
+namespace aidl::android::hardware::neuralnetworks::adapter {
+namespace {
+
+using Value = Burst::ThreadSafeMemoryCache::Value;
+
+template <typename Type>
+auto convertInput(const Type& object) -> decltype(nn::convert(std::declval<Type>())) {
+    auto result = nn::convert(object);
+    if (!result.has_value()) {
+        result.error().code = nn::ErrorStatus::INVALID_ARGUMENT;
+    }
+    return result;
+}
+
+nn::Duration makeDuration(int64_t durationNs) {
+    return nn::Duration(std::chrono::nanoseconds(durationNs));
+}
+
+nn::GeneralResult<nn::OptionalDuration> makeOptionalDuration(int64_t durationNs) {
+    if (durationNs < -1) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid duration " << durationNs;
+    }
+    return durationNs < 0 ? nn::OptionalDuration{} : makeDuration(durationNs);
+}
+
+nn::GeneralResult<nn::OptionalTimePoint> makeOptionalTimePoint(int64_t durationNs) {
+    if (durationNs < -1) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid time point " << durationNs;
+    }
+    return durationNs < 0 ? nn::OptionalTimePoint{} : nn::TimePoint(makeDuration(durationNs));
+}
+
+std::vector<nn::IBurst::OptionalCacheHold> ensureAllMemoriesAreCached(
+        nn::Request* request, const std::vector<int64_t>& memoryIdentifierTokens,
+        const nn::IBurst& burst, const Burst::ThreadSafeMemoryCache& cache) {
+    std::vector<nn::IBurst::OptionalCacheHold> holds;
+    holds.reserve(memoryIdentifierTokens.size());
+
+    for (size_t i = 0; i < memoryIdentifierTokens.size(); ++i) {
+        const auto& pool = request->pools[i];
+        const auto token = memoryIdentifierTokens[i];
+        constexpr int64_t kNoToken = -1;
+        if (token == kNoToken || !std::holds_alternative<nn::SharedMemory>(pool)) {
+            continue;
+        }
+
+        const auto& memory = std::get<nn::SharedMemory>(pool);
+        auto [storedMemory, hold] = cache.add(token, memory, burst);
+
+        request->pools[i] = std::move(storedMemory);
+        holds.push_back(std::move(hold));
+    }
+
+    return holds;
+}
+
+nn::ExecutionResult<ExecutionResult> executeSynchronously(
+        const nn::IBurst& burst, const Burst::ThreadSafeMemoryCache& cache, const Request& request,
+        const std::vector<int64_t>& memoryIdentifierTokens, bool measureTiming, int64_t deadlineNs,
+        int64_t loopTimeoutDurationNs) {
+    if (request.pools.size() != memoryIdentifierTokens.size()) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+               << "request.pools.size() != memoryIdentifierTokens.size()";
+    }
+    if (!std::all_of(memoryIdentifierTokens.begin(), memoryIdentifierTokens.end(),
+                     [](int64_t token) { return token >= -1; })) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid memoryIdentifierTokens";
+    }
+
+    auto nnRequest = NN_TRY(convertInput(request));
+    const auto nnMeasureTiming = measureTiming ? nn::MeasureTiming::YES : nn::MeasureTiming::NO;
+    const auto nnDeadline = NN_TRY(makeOptionalTimePoint(deadlineNs));
+    const auto nnLoopTimeoutDuration = NN_TRY(makeOptionalDuration(loopTimeoutDurationNs));
+
+    const auto hold = ensureAllMemoriesAreCached(&nnRequest, memoryIdentifierTokens, burst, cache);
+
+    const auto result =
+            burst.execute(nnRequest, nnMeasureTiming, nnDeadline, nnLoopTimeoutDuration);
+
+    if (!result.ok() && result.error().code == nn::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE) {
+        const auto& [message, code, outputShapes] = result.error();
+        return ExecutionResult{.outputSufficientSize = false,
+                               .outputShapes = utils::convert(outputShapes).value(),
+                               .timing = {.timeInDriverNs = -1, .timeOnDeviceNs = -1}};
+    }
+
+    const auto& [outputShapes, timing] = NN_TRY(result);
+    return ExecutionResult{.outputSufficientSize = true,
+                           .outputShapes = utils::convert(outputShapes).value(),
+                           .timing = utils::convert(timing).value()};
+}
+
+}  // namespace
+
+Value Burst::ThreadSafeMemoryCache::add(int64_t token, const nn::SharedMemory& memory,
+                                        const nn::IBurst& burst) const {
+    std::lock_guard guard(mMutex);
+    if (const auto it = mCache.find(token); it != mCache.end()) {
+        return it->second;
+    }
+    auto hold = burst.cacheMemory(memory);
+    auto [it, _] = mCache.emplace(token, std::make_pair(memory, std::move(hold)));
+    return it->second;
+}
+
+void Burst::ThreadSafeMemoryCache::remove(int64_t token) const {
+    std::lock_guard guard(mMutex);
+    mCache.erase(token);
+}
+
+Burst::Burst(nn::SharedBurst burst) : kBurst(std::move(burst)) {
+    CHECK(kBurst != nullptr);
+}
+
+ndk::ScopedAStatus Burst::executeSynchronously(const Request& request,
+                                               const std::vector<int64_t>& memoryIdentifierTokens,
+                                               bool measureTiming, int64_t deadlineNs,
+                                               int64_t loopTimeoutDurationNs,
+                                               ExecutionResult* executionResult) {
+    auto result =
+            adapter::executeSynchronously(*kBurst, kMemoryCache, request, memoryIdentifierTokens,
+                                          measureTiming, deadlineNs, loopTimeoutDurationNs);
+    if (!result.has_value()) {
+        auto [message, code, _] = std::move(result).error();
+        const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE);
+        return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage(
+                static_cast<int32_t>(aidlCode), message.c_str());
+    }
+    *executionResult = std::move(result).value();
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Burst::releaseMemoryResource(int64_t memoryIdentifierToken) {
+    if (memoryIdentifierToken < -1) {
+        return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage(
+                static_cast<int32_t>(ErrorStatus::INVALID_ARGUMENT),
+                "Invalid memoryIdentifierToken");
+    }
+    kMemoryCache.remove(memoryIdentifierToken);
+    return ndk::ScopedAStatus::ok();
+}
+
+}  // namespace aidl::android::hardware::neuralnetworks::adapter
diff --git a/neuralnetworks/utils/adapter/aidl/src/Device.cpp b/neuralnetworks/utils/adapter/aidl/src/Device.cpp
new file mode 100644
index 0000000..763be7f
--- /dev/null
+++ b/neuralnetworks/utils/adapter/aidl/src/Device.cpp
@@ -0,0 +1,304 @@
+/*
+ * 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.
+ */
+
+#include "Device.h"
+
+#include "Adapter.h"
+#include "Buffer.h"
+#include "PreparedModel.h"
+
+#include <aidl/android/hardware/neuralnetworks/BnDevice.h>
+#include <aidl/android/hardware/neuralnetworks/BufferDesc.h>
+#include <aidl/android/hardware/neuralnetworks/BufferRole.h>
+#include <aidl/android/hardware/neuralnetworks/DeviceBuffer.h>
+#include <aidl/android/hardware/neuralnetworks/DeviceType.h>
+#include <aidl/android/hardware/neuralnetworks/ErrorStatus.h>
+#include <aidl/android/hardware/neuralnetworks/ExecutionPreference.h>
+#include <aidl/android/hardware/neuralnetworks/Extension.h>
+#include <aidl/android/hardware/neuralnetworks/IPreparedModelCallback.h>
+#include <aidl/android/hardware/neuralnetworks/IPreparedModelParcel.h>
+#include <aidl/android/hardware/neuralnetworks/Model.h>
+#include <aidl/android/hardware/neuralnetworks/NumberOfCacheFiles.h>
+#include <aidl/android/hardware/neuralnetworks/Priority.h>
+#include <android-base/logging.h>
+#include <android/binder_auto_utils.h>
+#include <android/binder_interface_utils.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/Result.h>
+#include <nnapi/TypeUtils.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/aidl/Conversions.h>
+
+#include <chrono>
+#include <memory>
+#include <string>
+#include <vector>
+
+namespace aidl::android::hardware::neuralnetworks::adapter {
+namespace {
+
+template <typename Type>
+auto convertInput(const Type& object) -> decltype(nn::convert(std::declval<Type>())) {
+    auto result = nn::convert(object);
+    if (!result.has_value()) {
+        result.error().code = nn::ErrorStatus::INVALID_ARGUMENT;
+    }
+    return result;
+}
+
+nn::Duration makeDuration(int64_t durationNs) {
+    return nn::Duration(std::chrono::nanoseconds(durationNs));
+}
+
+nn::GeneralResult<nn::OptionalTimePoint> makeOptionalTimePoint(int64_t durationNs) {
+    if (durationNs < -1) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid time point " << durationNs;
+    }
+    return durationNs < 0 ? nn::OptionalTimePoint{} : nn::TimePoint(makeDuration(durationNs));
+}
+
+nn::GeneralResult<nn::CacheToken> convertCacheToken(const std::vector<uint8_t>& token) {
+    nn::CacheToken nnToken;
+    if (token.size() != nnToken.size()) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid token";
+    }
+    std::copy(token.begin(), token.end(), nnToken.begin());
+    return nnToken;
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> downcast(const IPreparedModelParcel& preparedModel) {
+    if (preparedModel.preparedModel == nullptr) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "preparedModel is nullptr";
+    }
+    if (preparedModel.preparedModel->isRemote()) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Cannot convert remote models";
+    }
+
+    // This static_cast is safe because adapter::PreparedModel is the only class that implements
+    // the IPreparedModel interface in the adapter service code.
+    const auto* casted = static_cast<const PreparedModel*>(preparedModel.preparedModel.get());
+    return casted->getUnderlyingPreparedModel();
+}
+
+nn::GeneralResult<std::vector<nn::SharedPreparedModel>> downcastAll(
+        const std::vector<IPreparedModelParcel>& preparedModels) {
+    std::vector<nn::SharedPreparedModel> canonical;
+    canonical.reserve(preparedModels.size());
+    for (const auto& preparedModel : preparedModels) {
+        canonical.push_back(NN_TRY(downcast(preparedModel)));
+    }
+    return canonical;
+}
+
+nn::GeneralResult<DeviceBuffer> allocate(const nn::IDevice& device, const BufferDesc& desc,
+                                         const std::vector<IPreparedModelParcel>& preparedModels,
+                                         const std::vector<BufferRole>& inputRoles,
+                                         const std::vector<BufferRole>& outputRoles) {
+    auto nnDesc = NN_TRY(convertInput(desc));
+    auto nnPreparedModels = NN_TRY(downcastAll(preparedModels));
+    auto nnInputRoles = NN_TRY(convertInput(inputRoles));
+    auto nnOutputRoles = NN_TRY(convertInput(outputRoles));
+
+    auto buffer = NN_TRY(device.allocate(nnDesc, nnPreparedModels, nnInputRoles, nnOutputRoles));
+    CHECK(buffer != nullptr);
+
+    const nn::Request::MemoryDomainToken token = buffer->getToken();
+    auto aidlBuffer = ndk::SharedRefBase::make<Buffer>(std::move(buffer));
+    return DeviceBuffer{.buffer = std::move(aidlBuffer), .token = static_cast<int32_t>(token)};
+}
+
+nn::GeneralResult<std::vector<bool>> getSupportedOperations(const nn::IDevice& device,
+                                                            const Model& model) {
+    const auto nnModel = NN_TRY(convertInput(model));
+    return device.getSupportedOperations(nnModel);
+}
+
+using PrepareModelResult = nn::GeneralResult<nn::SharedPreparedModel>;
+
+std::shared_ptr<PreparedModel> adaptPreparedModel(nn::SharedPreparedModel preparedModel) {
+    if (preparedModel == nullptr) {
+        return nullptr;
+    }
+    return ndk::SharedRefBase::make<PreparedModel>(std::move(preparedModel));
+}
+
+void notify(IPreparedModelCallback* callback, PrepareModelResult result) {
+    if (!result.has_value()) {
+        const auto& [message, status] = result.error();
+        LOG(ERROR) << message;
+        const auto aidlCode = utils::convert(status).value_or(ErrorStatus::GENERAL_FAILURE);
+        callback->notify(aidlCode, nullptr);
+    } else {
+        auto preparedModel = std::move(result).value();
+        auto aidlPreparedModel = adaptPreparedModel(std::move(preparedModel));
+        callback->notify(ErrorStatus::NONE, std::move(aidlPreparedModel));
+    }
+}
+
+nn::GeneralResult<void> prepareModel(const nn::SharedDevice& device, const Executor& executor,
+                                     const Model& model, ExecutionPreference preference,
+                                     Priority priority, int64_t deadlineNs,
+                                     const std::vector<ndk::ScopedFileDescriptor>& modelCache,
+                                     const std::vector<ndk::ScopedFileDescriptor>& dataCache,
+                                     const std::vector<uint8_t>& token,
+                                     const std::shared_ptr<IPreparedModelCallback>& callback) {
+    if (callback.get() == nullptr) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid callback";
+    }
+
+    auto nnModel = NN_TRY(convertInput(model));
+    const auto nnPreference = NN_TRY(convertInput(preference));
+    const auto nnPriority = NN_TRY(convertInput(priority));
+    const auto nnDeadline = NN_TRY(makeOptionalTimePoint(deadlineNs));
+    auto nnModelCache = NN_TRY(convertInput(modelCache));
+    auto nnDataCache = NN_TRY(convertInput(dataCache));
+    const auto nnToken = NN_TRY(convertCacheToken(token));
+
+    Task task = [device, nnModel = std::move(nnModel), nnPreference, nnPriority, nnDeadline,
+                 nnModelCache = std::move(nnModelCache), nnDataCache = std::move(nnDataCache),
+                 nnToken, callback] {
+        auto result = device->prepareModel(nnModel, nnPreference, nnPriority, nnDeadline,
+                                           nnModelCache, nnDataCache, nnToken);
+        notify(callback.get(), std::move(result));
+    };
+    executor(std::move(task), nnDeadline);
+
+    return {};
+}
+
+nn::GeneralResult<void> prepareModelFromCache(
+        const nn::SharedDevice& device, const Executor& executor, int64_t deadlineNs,
+        const std::vector<ndk::ScopedFileDescriptor>& modelCache,
+        const std::vector<ndk::ScopedFileDescriptor>& dataCache, const std::vector<uint8_t>& token,
+        const std::shared_ptr<IPreparedModelCallback>& callback) {
+    if (callback.get() == nullptr) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid callback";
+    }
+
+    const auto nnDeadline = NN_TRY(makeOptionalTimePoint(deadlineNs));
+    auto nnModelCache = NN_TRY(convertInput(modelCache));
+    auto nnDataCache = NN_TRY(convertInput(dataCache));
+    const auto nnToken = NN_TRY(convertCacheToken(token));
+
+    auto task = [device, nnDeadline, nnModelCache = std::move(nnModelCache),
+                 nnDataCache = std::move(nnDataCache), nnToken, callback] {
+        auto result = device->prepareModelFromCache(nnDeadline, nnModelCache, nnDataCache, nnToken);
+        notify(callback.get(), std::move(result));
+    };
+    executor(std::move(task), nnDeadline);
+
+    return {};
+}
+
+}  // namespace
+
+Device::Device(::android::nn::SharedDevice device, Executor executor)
+    : kDevice(std::move(device)), kExecutor(std::move(executor)) {
+    CHECK(kDevice != nullptr);
+    CHECK(kExecutor != nullptr);
+}
+
+ndk::ScopedAStatus Device::allocate(const BufferDesc& desc,
+                                    const std::vector<IPreparedModelParcel>& preparedModels,
+                                    const std::vector<BufferRole>& inputRoles,
+                                    const std::vector<BufferRole>& outputRoles,
+                                    DeviceBuffer* buffer) {
+    auto result = adapter::allocate(*kDevice, desc, preparedModels, inputRoles, outputRoles);
+    if (!result.has_value()) {
+        const auto& [message, code] = result.error();
+        const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE);
+        return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage(
+                static_cast<int32_t>(aidlCode), message.c_str());
+    }
+    *buffer = std::move(result).value();
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Device::getCapabilities(Capabilities* capabilities) {
+    *capabilities = utils::convert(kDevice->getCapabilities()).value();
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Device::getNumberOfCacheFilesNeeded(NumberOfCacheFiles* numberOfCacheFiles) {
+    const auto [numModelCache, numDataCache] = kDevice->getNumberOfCacheFilesNeeded();
+    *numberOfCacheFiles = NumberOfCacheFiles{.numModelCache = static_cast<int32_t>(numModelCache),
+                                             .numDataCache = static_cast<int32_t>(numDataCache)};
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Device::getSupportedExtensions(std::vector<Extension>* extensions) {
+    *extensions = utils::convert(kDevice->getSupportedExtensions()).value();
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Device::getSupportedOperations(const Model& model,
+                                                  std::vector<bool>* supported) {
+    auto result = adapter::getSupportedOperations(*kDevice, model);
+    if (!result.has_value()) {
+        const auto& [message, code] = result.error();
+        const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE);
+        return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage(
+                static_cast<int32_t>(aidlCode), message.c_str());
+    }
+    *supported = std::move(result).value();
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Device::getType(DeviceType* deviceType) {
+    *deviceType = utils::convert(kDevice->getType()).value();
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Device::getVersionString(std::string* version) {
+    *version = kDevice->getVersionString();
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Device::prepareModel(const Model& model, ExecutionPreference preference,
+                                        Priority priority, int64_t deadlineNs,
+                                        const std::vector<ndk::ScopedFileDescriptor>& modelCache,
+                                        const std::vector<ndk::ScopedFileDescriptor>& dataCache,
+                                        const std::vector<uint8_t>& token,
+                                        const std::shared_ptr<IPreparedModelCallback>& callback) {
+    const auto result = adapter::prepareModel(kDevice, kExecutor, model, preference, priority,
+                                              deadlineNs, modelCache, dataCache, token, callback);
+    if (!result.has_value()) {
+        const auto& [message, code] = result.error();
+        const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE);
+        callback->notify(aidlCode, nullptr);
+        return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage(
+                static_cast<int32_t>(aidlCode), message.c_str());
+    }
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Device::prepareModelFromCache(
+        int64_t deadlineNs, const std::vector<ndk::ScopedFileDescriptor>& modelCache,
+        const std::vector<ndk::ScopedFileDescriptor>& dataCache, const std::vector<uint8_t>& token,
+        const std::shared_ptr<IPreparedModelCallback>& callback) {
+    const auto result = adapter::prepareModelFromCache(kDevice, kExecutor, deadlineNs, modelCache,
+                                                       dataCache, token, callback);
+    if (!result.has_value()) {
+        const auto& [message, code] = result.error();
+        const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE);
+        callback->notify(aidlCode, nullptr);
+        return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage(
+                static_cast<int32_t>(aidlCode), message.c_str());
+    }
+    return ndk::ScopedAStatus::ok();
+}
+
+}  // namespace aidl::android::hardware::neuralnetworks::adapter
diff --git a/neuralnetworks/utils/adapter/aidl/src/PreparedModel.cpp b/neuralnetworks/utils/adapter/aidl/src/PreparedModel.cpp
new file mode 100644
index 0000000..71ed1a8
--- /dev/null
+++ b/neuralnetworks/utils/adapter/aidl/src/PreparedModel.cpp
@@ -0,0 +1,225 @@
+/*
+ * 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.
+ */
+
+#include "PreparedModel.h"
+
+#include "Burst.h"
+
+#include <aidl/android/hardware/neuralnetworks/BnFencedExecutionCallback.h>
+#include <aidl/android/hardware/neuralnetworks/BnPreparedModel.h>
+#include <aidl/android/hardware/neuralnetworks/ExecutionResult.h>
+#include <aidl/android/hardware/neuralnetworks/FencedExecutionResult.h>
+#include <aidl/android/hardware/neuralnetworks/IBurst.h>
+#include <aidl/android/hardware/neuralnetworks/Request.h>
+#include <android-base/logging.h>
+#include <android/binder_auto_utils.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/SharedMemory.h>
+#include <nnapi/Types.h>
+#include <nnapi/Validation.h>
+#include <nnapi/hal/aidl/Conversions.h>
+#include <nnapi/hal/aidl/Utils.h>
+
+#include <memory>
+#include <utility>
+#include <vector>
+
+namespace aidl::android::hardware::neuralnetworks::adapter {
+namespace {
+
+class FencedExecutionCallback : public BnFencedExecutionCallback {
+  public:
+    FencedExecutionCallback(nn::ExecuteFencedInfoCallback callback)
+        : kCallback(std::move(callback)) {}
+
+    ndk::ScopedAStatus getExecutionInfo(Timing* timingLaunched, Timing* timingFenced,
+                                        ErrorStatus* errorStatus) override {
+        const auto result = kCallback();
+        if (result.ok()) {
+            const auto& [nnTimingLaunched, nnTimingFenced] = result.value();
+            *timingLaunched = utils::convert(nnTimingLaunched).value();
+            *timingFenced = utils::convert(nnTimingFenced).value();
+            *errorStatus = ErrorStatus::NONE;
+        } else {
+            constexpr auto kNoTiming = Timing{.timeOnDeviceNs = -1, .timeInDriverNs = -1};
+            const auto& [message, code] = result.error();
+            LOG(ERROR) << "getExecutionInfo failed with " << code << ": " << message;
+            const auto aidlStatus = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE);
+            *timingLaunched = kNoTiming;
+            *timingFenced = kNoTiming;
+            *errorStatus = aidlStatus;
+        }
+        return ndk::ScopedAStatus::ok();
+    }
+
+  private:
+    const nn::ExecuteFencedInfoCallback kCallback;
+};
+
+template <typename Type>
+auto convertInput(const Type& object) -> decltype(nn::convert(std::declval<Type>())) {
+    auto result = nn::convert(object);
+    if (!result.has_value()) {
+        result.error().code = nn::ErrorStatus::INVALID_ARGUMENT;
+    }
+    return result;
+}
+
+nn::GeneralResult<std::vector<nn::SyncFence>> convertSyncFences(
+        const std::vector<ndk::ScopedFileDescriptor>& waitFor) {
+    auto handles = NN_TRY(convertInput(waitFor));
+
+    constexpr auto valid = [](const nn::SharedHandle& handle) {
+        return handle != nullptr && handle->ok();
+    };
+    if (!std::all_of(handles.begin(), handles.end(), valid)) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid sync fence";
+    }
+
+    std::vector<nn::SyncFence> syncFences;
+    syncFences.reserve(waitFor.size());
+    for (auto& handle : handles) {
+        syncFences.push_back(nn::SyncFence::create(std::move(handle)).value());
+    }
+    return syncFences;
+}
+
+nn::Duration makeDuration(int64_t durationNs) {
+    return nn::Duration(std::chrono::nanoseconds(durationNs));
+}
+
+nn::GeneralResult<nn::OptionalDuration> makeOptionalDuration(int64_t durationNs) {
+    if (durationNs < -1) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid duration " << durationNs;
+    }
+    return durationNs < 0 ? nn::OptionalDuration{} : makeDuration(durationNs);
+}
+
+nn::GeneralResult<nn::OptionalTimePoint> makeOptionalTimePoint(int64_t durationNs) {
+    if (durationNs < -1) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid time point " << durationNs;
+    }
+    return durationNs < 0 ? nn::OptionalTimePoint{} : nn::TimePoint(makeDuration(durationNs));
+}
+
+nn::ExecutionResult<ExecutionResult> executeSynchronously(const nn::IPreparedModel& preparedModel,
+                                                          const Request& request,
+                                                          bool measureTiming, int64_t deadlineNs,
+                                                          int64_t loopTimeoutDurationNs) {
+    const auto nnRequest = NN_TRY(convertInput(request));
+    const auto nnMeasureTiming = measureTiming ? nn::MeasureTiming::YES : nn::MeasureTiming::NO;
+    const auto nnDeadline = NN_TRY(makeOptionalTimePoint(deadlineNs));
+    const auto nnLoopTimeoutDuration = NN_TRY(makeOptionalDuration(loopTimeoutDurationNs));
+
+    const auto result =
+            preparedModel.execute(nnRequest, nnMeasureTiming, nnDeadline, nnLoopTimeoutDuration);
+
+    if (!result.ok() && result.error().code == nn::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE) {
+        const auto& [message, code, outputShapes] = result.error();
+        LOG(ERROR) << "executeSynchronously failed with " << code << ": " << message;
+        return ExecutionResult{.outputSufficientSize = false,
+                               .outputShapes = utils::convert(outputShapes).value(),
+                               .timing = {.timeInDriverNs = -1, .timeOnDeviceNs = -1}};
+    }
+
+    const auto& [outputShapes, timing] = NN_TRY(result);
+    return ExecutionResult{.outputSufficientSize = true,
+                           .outputShapes = utils::convert(outputShapes).value(),
+                           .timing = utils::convert(timing).value()};
+}
+
+nn::GeneralResult<FencedExecutionResult> executeFenced(
+        const nn::IPreparedModel& preparedModel, const Request& request,
+        const std::vector<ndk::ScopedFileDescriptor>& waitFor, bool measureTiming,
+        int64_t deadlineNs, int64_t loopTimeoutDurationNs, int64_t durationNs) {
+    const auto nnRequest = NN_TRY(convertInput(request));
+    const auto nnWaitFor = NN_TRY(convertSyncFences(waitFor));
+    const auto nnMeasureTiming = measureTiming ? nn::MeasureTiming::YES : nn::MeasureTiming::NO;
+    const auto nnDeadline = NN_TRY(makeOptionalTimePoint(deadlineNs));
+    const auto nnLoopTimeoutDuration = NN_TRY(makeOptionalDuration(loopTimeoutDurationNs));
+    const auto nnDuration = NN_TRY(makeOptionalDuration(durationNs));
+
+    auto [syncFence, executeFencedInfoCallback] = NN_TRY(preparedModel.executeFenced(
+            nnRequest, nnWaitFor, nnMeasureTiming, nnDeadline, nnLoopTimeoutDuration, nnDuration));
+
+    ndk::ScopedFileDescriptor fileDescriptor;
+    if (syncFence.hasFd()) {
+        auto uniqueFd = NN_TRY(nn::dupFd(syncFence.getFd()));
+        fileDescriptor = ndk::ScopedFileDescriptor(uniqueFd.release());
+    }
+
+    return FencedExecutionResult{.callback = ndk::SharedRefBase::make<FencedExecutionCallback>(
+                                         std::move(executeFencedInfoCallback)),
+                                 .syncFence = std::move(fileDescriptor)};
+}
+
+}  // namespace
+
+PreparedModel::PreparedModel(nn::SharedPreparedModel preparedModel)
+    : kPreparedModel(std::move(preparedModel)) {
+    CHECK(kPreparedModel != nullptr);
+}
+
+ndk::ScopedAStatus PreparedModel::executeSynchronously(const Request& request, bool measureTiming,
+                                                       int64_t deadlineNs,
+                                                       int64_t loopTimeoutDurationNs,
+                                                       ExecutionResult* executionResult) {
+    auto result = adapter::executeSynchronously(*kPreparedModel, request, measureTiming, deadlineNs,
+                                                loopTimeoutDurationNs);
+    if (!result.has_value()) {
+        const auto& [message, code, _] = result.error();
+        const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE);
+        return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage(
+                static_cast<int32_t>(aidlCode), message.c_str());
+    }
+    *executionResult = std::move(result).value();
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus PreparedModel::executeFenced(
+        const Request& request, const std::vector<ndk::ScopedFileDescriptor>& waitFor,
+        bool measureTiming, int64_t deadlineNs, int64_t loopTimeoutDurationNs, int64_t durationNs,
+        FencedExecutionResult* executionResult) {
+    auto result = adapter::executeFenced(*kPreparedModel, request, waitFor, measureTiming,
+                                         deadlineNs, loopTimeoutDurationNs, durationNs);
+    if (!result.has_value()) {
+        const auto& [message, code] = result.error();
+        const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE);
+        return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage(
+                static_cast<int32_t>(aidlCode), message.c_str());
+    }
+    *executionResult = std::move(result).value();
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus PreparedModel::configureExecutionBurst(std::shared_ptr<IBurst>* burst) {
+    auto result = kPreparedModel->configureExecutionBurst();
+    if (!result.has_value()) {
+        const auto& [message, code] = result.error();
+        const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE);
+        return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage(
+                static_cast<int32_t>(aidlCode), message.c_str());
+    }
+    *burst = ndk::SharedRefBase::make<Burst>(std::move(result).value());
+    return ndk::ScopedAStatus::ok();
+}
+
+nn::SharedPreparedModel PreparedModel::getUnderlyingPreparedModel() const {
+    return kPreparedModel;
+}
+
+}  // namespace aidl::android::hardware::neuralnetworks::adapter
diff --git a/neuralnetworks/utils/adapter/Android.bp b/neuralnetworks/utils/adapter/hidl/Android.bp
similarity index 100%
rename from neuralnetworks/utils/adapter/Android.bp
rename to neuralnetworks/utils/adapter/hidl/Android.bp
diff --git a/neuralnetworks/utils/adapter/include/nnapi/hal/Adapter.h b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Adapter.h
similarity index 86%
rename from neuralnetworks/utils/adapter/include/nnapi/hal/Adapter.h
rename to neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Adapter.h
index da00a09..6fba4ab 100644
--- a/neuralnetworks/utils/adapter/include/nnapi/hal/Adapter.h
+++ b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Adapter.h
@@ -20,7 +20,6 @@
 #include <android/hardware/neuralnetworks/1.3/IDevice.h>
 #include <nnapi/IDevice.h>
 #include <nnapi/Types.h>
-#include <sys/types.h>
 #include <functional>
 #include <memory>
 
@@ -37,10 +36,12 @@
 /**
  * A type-erased executor which executes a task asynchronously.
  *
- * This executor is also provided with an Application ID (Android User ID) and an optional deadline
- * for when the caller expects is the upper bound for the amount of time to complete the task.
+ * This executor is also provided an optional deadline for when the caller expects is the upper
+ * bound for the amount of time to complete the task. If needed, the Executor can retrieve the
+ * Application ID (Android User ID) by calling IPCThreadState::self()->getCallingUid() in
+ * hwbinder/IPCThreadState.h.
  */
-using Executor = std::function<void(Task, uid_t, nn::OptionalTimePoint)>;
+using Executor = std::function<void(Task, nn::OptionalTimePoint)>;
 
 /**
  * Adapt an NNAPI canonical interface object to a HIDL NN HAL interface object.
diff --git a/neuralnetworks/utils/adapter/include/nnapi/hal/Buffer.h b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Buffer.h
similarity index 100%
rename from neuralnetworks/utils/adapter/include/nnapi/hal/Buffer.h
rename to neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Buffer.h
diff --git a/neuralnetworks/utils/adapter/include/nnapi/hal/Burst.h b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Burst.h
similarity index 100%
rename from neuralnetworks/utils/adapter/include/nnapi/hal/Burst.h
rename to neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Burst.h
diff --git a/neuralnetworks/utils/adapter/include/nnapi/hal/Device.h b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Device.h
similarity index 100%
rename from neuralnetworks/utils/adapter/include/nnapi/hal/Device.h
rename to neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Device.h
diff --git a/neuralnetworks/utils/adapter/include/nnapi/hal/PreparedModel.h b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/PreparedModel.h
similarity index 98%
rename from neuralnetworks/utils/adapter/include/nnapi/hal/PreparedModel.h
rename to neuralnetworks/utils/adapter/hidl/include/nnapi/hal/PreparedModel.h
index 65763b8..9482b0d 100644
--- a/neuralnetworks/utils/adapter/include/nnapi/hal/PreparedModel.h
+++ b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/PreparedModel.h
@@ -39,7 +39,7 @@
 // Class that adapts nn::IPreparedModel to V1_3::IPreparedModel.
 class PreparedModel final : public V1_3::IPreparedModel {
   public:
-    PreparedModel(nn::SharedPreparedModel preparedModel, Executor executor, uid_t userId);
+    PreparedModel(nn::SharedPreparedModel preparedModel, Executor executor);
 
     Return<V1_0::ErrorStatus> execute(const V1_0::Request& request,
                                       const sp<V1_0::IExecutionCallback>& callback) override;
@@ -71,7 +71,6 @@
   private:
     const nn::SharedPreparedModel kPreparedModel;
     const Executor kExecutor;
-    const uid_t kUserId;
 };
 
 }  // namespace android::hardware::neuralnetworks::adapter
diff --git a/neuralnetworks/utils/adapter/src/Adapter.cpp b/neuralnetworks/utils/adapter/hidl/src/Adapter.cpp
similarity index 92%
rename from neuralnetworks/utils/adapter/src/Adapter.cpp
rename to neuralnetworks/utils/adapter/hidl/src/Adapter.cpp
index d6f53f0..782e815 100644
--- a/neuralnetworks/utils/adapter/src/Adapter.cpp
+++ b/neuralnetworks/utils/adapter/hidl/src/Adapter.cpp
@@ -21,7 +21,6 @@
 #include <android/hardware/neuralnetworks/1.3/IDevice.h>
 #include <nnapi/IDevice.h>
 #include <nnapi/Types.h>
-#include <sys/types.h>
 
 #include <functional>
 #include <memory>
@@ -37,7 +36,7 @@
 }
 
 sp<V1_3::IDevice> adapt(nn::SharedDevice device) {
-    Executor defaultExecutor = [](Task task, uid_t /*uid*/, nn::OptionalTimePoint /*deadline*/) {
+    Executor defaultExecutor = [](Task task, nn::OptionalTimePoint /*deadline*/) {
         std::thread(std::move(task)).detach();
     };
     return adapt(std::move(device), std::move(defaultExecutor));
diff --git a/neuralnetworks/utils/adapter/src/Buffer.cpp b/neuralnetworks/utils/adapter/hidl/src/Buffer.cpp
similarity index 100%
rename from neuralnetworks/utils/adapter/src/Buffer.cpp
rename to neuralnetworks/utils/adapter/hidl/src/Buffer.cpp
diff --git a/neuralnetworks/utils/adapter/src/Burst.cpp b/neuralnetworks/utils/adapter/hidl/src/Burst.cpp
similarity index 100%
rename from neuralnetworks/utils/adapter/src/Burst.cpp
rename to neuralnetworks/utils/adapter/hidl/src/Burst.cpp
diff --git a/neuralnetworks/utils/adapter/src/Device.cpp b/neuralnetworks/utils/adapter/hidl/src/Device.cpp
similarity index 92%
rename from neuralnetworks/utils/adapter/src/Device.cpp
rename to neuralnetworks/utils/adapter/hidl/src/Device.cpp
index 96142c3..4993a80 100644
--- a/neuralnetworks/utils/adapter/src/Device.cpp
+++ b/neuralnetworks/utils/adapter/hidl/src/Device.cpp
@@ -28,7 +28,6 @@
 #include <android/hardware/neuralnetworks/1.3/IDevice.h>
 #include <android/hardware/neuralnetworks/1.3/IPreparedModelCallback.h>
 #include <android/hardware/neuralnetworks/1.3/types.h>
-#include <hwbinder/IPCThreadState.h>
 #include <nnapi/IBuffer.h>
 #include <nnapi/IDevice.h>
 #include <nnapi/IPreparedModel.h>
@@ -43,7 +42,6 @@
 #include <nnapi/hal/1.2/Utils.h>
 #include <nnapi/hal/1.3/Conversions.h>
 #include <nnapi/hal/1.3/Utils.h>
-#include <sys/types.h>
 
 #include <memory>
 
@@ -64,12 +62,11 @@
 
 using PrepareModelResult = nn::GeneralResult<nn::SharedPreparedModel>;
 
-sp<PreparedModel> adaptPreparedModel(nn::SharedPreparedModel preparedModel, Executor executor,
-                                     uid_t userId) {
+sp<PreparedModel> adaptPreparedModel(nn::SharedPreparedModel preparedModel, Executor executor) {
     if (preparedModel == nullptr) {
         return nullptr;
     }
-    return sp<PreparedModel>::make(std::move(preparedModel), std::move(executor), userId);
+    return sp<PreparedModel>::make(std::move(preparedModel), std::move(executor));
 }
 
 void notify(V1_0::IPreparedModelCallback* callback, nn::ErrorStatus status,
@@ -108,15 +105,14 @@
 }
 
 template <typename CallbackType>
-void notify(CallbackType* callback, PrepareModelResult result, Executor executor, uid_t userId) {
+void notify(CallbackType* callback, PrepareModelResult result, Executor executor) {
     if (!result.has_value()) {
         const auto [message, status] = std::move(result).error();
         LOG(ERROR) << message;
         notify(callback, status, nullptr);
     } else {
         auto preparedModel = std::move(result).value();
-        auto hidlPreparedModel =
-                adaptPreparedModel(std::move(preparedModel), std::move(executor), userId);
+        auto hidlPreparedModel = adaptPreparedModel(std::move(preparedModel), std::move(executor));
         notify(callback, nn::ErrorStatus::NONE, std::move(hidlPreparedModel));
     }
 }
@@ -137,13 +133,12 @@
 
     auto nnModel = NN_TRY(convertInput(model));
 
-    const uid_t userId = hardware::IPCThreadState::self()->getCallingUid();
-    Task task = [device, nnModel = std::move(nnModel), userId, executor, callback] {
+    Task task = [device, nnModel = std::move(nnModel), executor, callback] {
         auto result = device->prepareModel(nnModel, nn::ExecutionPreference::DEFAULT,
                                            nn::Priority::DEFAULT, {}, {}, {}, {});
-        notify(callback.get(), std::move(result), executor, userId);
+        notify(callback.get(), std::move(result), executor);
     };
-    executor(std::move(task), userId, {});
+    executor(std::move(task), {});
 
     return {};
 }
@@ -159,13 +154,12 @@
     auto nnModel = NN_TRY(convertInput(model));
     const auto nnPreference = NN_TRY(convertInput(preference));
 
-    const uid_t userId = hardware::IPCThreadState::self()->getCallingUid();
-    Task task = [device, nnModel = std::move(nnModel), nnPreference, userId, executor, callback] {
+    Task task = [device, nnModel = std::move(nnModel), nnPreference, executor, callback] {
         auto result =
                 device->prepareModel(nnModel, nnPreference, nn::Priority::DEFAULT, {}, {}, {}, {});
-        notify(callback.get(), std::move(result), executor, userId);
+        notify(callback.get(), std::move(result), executor);
     };
-    executor(std::move(task), userId, {});
+    executor(std::move(task), {});
 
     return {};
 }
@@ -187,15 +181,14 @@
     auto nnDataCache = NN_TRY(convertInput(dataCache));
     const auto nnToken = nn::CacheToken(token);
 
-    const uid_t userId = hardware::IPCThreadState::self()->getCallingUid();
     Task task = [device, nnModel = std::move(nnModel), nnPreference,
                  nnModelCache = std::move(nnModelCache), nnDataCache = std::move(nnDataCache),
-                 nnToken, userId, executor, callback] {
+                 nnToken, executor, callback] {
         auto result = device->prepareModel(nnModel, nnPreference, nn::Priority::DEFAULT, {},
                                            nnModelCache, nnDataCache, nnToken);
-        notify(callback.get(), std::move(result), executor, userId);
+        notify(callback.get(), std::move(result), executor);
     };
-    executor(std::move(task), userId, {});
+    executor(std::move(task), {});
 
     return {};
 }
@@ -218,15 +211,14 @@
     auto nnDataCache = NN_TRY(convertInput(dataCache));
     const auto nnToken = nn::CacheToken(token);
 
-    const uid_t userId = hardware::IPCThreadState::self()->getCallingUid();
     Task task = [device, nnModel = std::move(nnModel), nnPreference, nnPriority, nnDeadline,
                  nnModelCache = std::move(nnModelCache), nnDataCache = std::move(nnDataCache),
-                 nnToken, userId, executor, callback] {
+                 nnToken, executor, callback] {
         auto result = device->prepareModel(nnModel, nnPreference, nnPriority, nnDeadline,
                                            nnModelCache, nnDataCache, nnToken);
-        notify(callback.get(), std::move(result), executor, userId);
+        notify(callback.get(), std::move(result), executor);
     };
-    executor(std::move(task), userId, nnDeadline);
+    executor(std::move(task), nnDeadline);
 
     return {};
 }
@@ -245,13 +237,12 @@
     auto nnDataCache = NN_TRY(convertInput(dataCache));
     const auto nnToken = nn::CacheToken(token);
 
-    const uid_t userId = hardware::IPCThreadState::self()->getCallingUid();
     Task task = [device, nnModelCache = std::move(nnModelCache),
-                 nnDataCache = std::move(nnDataCache), nnToken, userId, executor, callback] {
+                 nnDataCache = std::move(nnDataCache), nnToken, executor, callback] {
         auto result = device->prepareModelFromCache({}, nnModelCache, nnDataCache, nnToken);
-        notify(callback.get(), std::move(result), executor, userId);
+        notify(callback.get(), std::move(result), executor);
     };
-    executor(std::move(task), userId, {});
+    executor(std::move(task), {});
 
     return {};
 }
@@ -270,13 +261,12 @@
     auto nnDataCache = NN_TRY(convertInput(dataCache));
     const auto nnToken = nn::CacheToken(token);
 
-    const uid_t userId = hardware::IPCThreadState::self()->getCallingUid();
     auto task = [device, nnDeadline, nnModelCache = std::move(nnModelCache),
-                 nnDataCache = std::move(nnDataCache), nnToken, userId, executor, callback] {
+                 nnDataCache = std::move(nnDataCache), nnToken, executor, callback] {
         auto result = device->prepareModelFromCache(nnDeadline, nnModelCache, nnDataCache, nnToken);
-        notify(callback.get(), std::move(result), executor, userId);
+        notify(callback.get(), std::move(result), executor);
     };
-    executor(std::move(task), userId, nnDeadline);
+    executor(std::move(task), nnDeadline);
 
     return {};
 }
diff --git a/neuralnetworks/utils/adapter/src/PreparedModel.cpp b/neuralnetworks/utils/adapter/hidl/src/PreparedModel.cpp
similarity index 96%
rename from neuralnetworks/utils/adapter/src/PreparedModel.cpp
rename to neuralnetworks/utils/adapter/hidl/src/PreparedModel.cpp
index a14e782..71060d5 100644
--- a/neuralnetworks/utils/adapter/src/PreparedModel.cpp
+++ b/neuralnetworks/utils/adapter/hidl/src/PreparedModel.cpp
@@ -28,7 +28,6 @@
 #include <android/hardware/neuralnetworks/1.3/IFencedExecutionCallback.h>
 #include <android/hardware/neuralnetworks/1.3/IPreparedModel.h>
 #include <android/hardware/neuralnetworks/1.3/types.h>
-#include <hwbinder/IPCThreadState.h>
 #include <nnapi/IPreparedModel.h>
 #include <nnapi/TypeUtils.h>
 #include <nnapi/Types.h>
@@ -37,7 +36,6 @@
 #include <nnapi/hal/1.2/Utils.h>
 #include <nnapi/hal/1.3/Conversions.h>
 #include <nnapi/hal/1.3/Utils.h>
-#include <sys/types.h>
 
 #include <memory>
 #include <thread>
@@ -145,7 +143,7 @@
     }
 }
 
-nn::GeneralResult<void> execute(const nn::SharedPreparedModel& preparedModel, uid_t userId,
+nn::GeneralResult<void> execute(const nn::SharedPreparedModel& preparedModel,
                                 const Executor& executor, const V1_0::Request& request,
                                 const sp<V1_0::IExecutionCallback>& callback) {
     if (callback.get() == nullptr) {
@@ -164,12 +162,12 @@
         auto result = preparedModel->execute(nnRequest, nn::MeasureTiming::NO, {}, {});
         notify(callback.get(), std::move(result));
     };
-    executor(std::move(task), userId, {});
+    executor(std::move(task), {});
 
     return {};
 }
 
-nn::GeneralResult<void> execute_1_2(const nn::SharedPreparedModel& preparedModel, uid_t userId,
+nn::GeneralResult<void> execute_1_2(const nn::SharedPreparedModel& preparedModel,
                                     const Executor& executor, const V1_0::Request& request,
                                     V1_2::MeasureTiming measure,
                                     const sp<V1_2::IExecutionCallback>& callback) {
@@ -190,12 +188,12 @@
         auto result = preparedModel->execute(nnRequest, nnMeasure, {}, {});
         notify(callback.get(), std::move(result));
     };
-    executor(std::move(task), userId, {});
+    executor(std::move(task), {});
 
     return {};
 }
 
-nn::GeneralResult<void> execute_1_3(const nn::SharedPreparedModel& preparedModel, uid_t userId,
+nn::GeneralResult<void> execute_1_3(const nn::SharedPreparedModel& preparedModel,
                                     const Executor& executor, const V1_3::Request& request,
                                     V1_2::MeasureTiming measure,
                                     const V1_3::OptionalTimePoint& deadline,
@@ -222,7 +220,7 @@
                 preparedModel->execute(nnRequest, nnMeasure, nnDeadline, nnLoopTimeoutDuration);
         notify(callback.get(), std::move(result));
     };
-    executor(std::move(task), userId, nnDeadline);
+    executor(std::move(task), nnDeadline);
 
     return {};
 }
@@ -305,8 +303,8 @@
 
 }  // namespace
 
-PreparedModel::PreparedModel(nn::SharedPreparedModel preparedModel, Executor executor, uid_t userId)
-    : kPreparedModel(std::move(preparedModel)), kExecutor(std::move(executor)), kUserId(userId) {
+PreparedModel::PreparedModel(nn::SharedPreparedModel preparedModel, Executor executor)
+    : kPreparedModel(std::move(preparedModel)), kExecutor(std::move(executor)) {
     CHECK(kPreparedModel != nullptr);
     CHECK(kExecutor != nullptr);
 }
@@ -317,7 +315,7 @@
 
 Return<V1_0::ErrorStatus> PreparedModel::execute(const V1_0::Request& request,
                                                  const sp<V1_0::IExecutionCallback>& callback) {
-    auto result = adapter::execute(kPreparedModel, kUserId, kExecutor, request, callback);
+    auto result = adapter::execute(kPreparedModel, kExecutor, request, callback);
     if (!result.has_value()) {
         auto [message, code] = std::move(result).error();
         LOG(ERROR) << "adapter::PreparedModel::execute failed with " << code << ": " << message;
@@ -330,8 +328,7 @@
 Return<V1_0::ErrorStatus> PreparedModel::execute_1_2(const V1_0::Request& request,
                                                      V1_2::MeasureTiming measure,
                                                      const sp<V1_2::IExecutionCallback>& callback) {
-    auto result =
-            adapter::execute_1_2(kPreparedModel, kUserId, kExecutor, request, measure, callback);
+    auto result = adapter::execute_1_2(kPreparedModel, kExecutor, request, measure, callback);
     if (!result.has_value()) {
         auto [message, code] = std::move(result).error();
         LOG(ERROR) << "adapter::PreparedModel::execute_1_2 failed with " << code << ": " << message;
@@ -346,8 +343,8 @@
         const V1_3::OptionalTimePoint& deadline,
         const V1_3::OptionalTimeoutDuration& loopTimeoutDuration,
         const sp<V1_3::IExecutionCallback>& callback) {
-    auto result = adapter::execute_1_3(kPreparedModel, kUserId, kExecutor, request, measure,
-                                       deadline, loopTimeoutDuration, callback);
+    auto result = adapter::execute_1_3(kPreparedModel, kExecutor, request, measure, deadline,
+                                       loopTimeoutDuration, callback);
     if (!result.has_value()) {
         auto [message, code] = std::move(result).error();
         LOG(ERROR) << "adapter::PreparedModel::execute_1_3 failed with " << code << ": " << message;