diff --git a/1.0/ArmnnDriverImpl.cpp b/1.0/ArmnnDriverImpl.cpp
new file mode 100644
index 0000000..5429ebe
--- /dev/null
+++ b/1.0/ArmnnDriverImpl.cpp
@@ -0,0 +1,277 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// See LICENSE file in the project root for full license information.
+//
+
+#include "ArmnnDriverImpl.hpp"
+#include "ModelToINetworkConverter.hpp"
+#include "ArmnnPreparedModel.hpp"
+#include "SystemPropertiesUtils.hpp"
+
+#if defined(ARMNN_ANDROID_P)
+// The headers of the ML framework have changed between Android O and Android P.
+// The validation functions have been moved into their own header, ValidateHal.h.
+#include <ValidateHal.h>
+#endif
+
+#include <log/log.h>
+
+using namespace std;
+using namespace android;
+using namespace android::nn;
+using namespace android::hardware;
+
+namespace
+{
+
+const char *g_Float32PerformanceExecTimeName = "ArmNN.float32Performance.execTime";
+const char *g_Float32PerformancePowerUsageName = "ArmNN.float32Performance.powerUsage";
+const char *g_Quantized8PerformanceExecTimeName = "ArmNN.quantized8Performance.execTime";
+const char *g_Quantized8PerformancePowerUsageName = "ArmNN.quantized8Performance.powerUsage";
+
+void NotifyCallbackAndCheck(const sp<IPreparedModelCallback>& callback,
+                            ErrorStatus errorStatus,
+                            const sp<IPreparedModel>& preparedModelPtr)
+{
+    Return<void> returned = callback->notify(errorStatus, preparedModelPtr);
+    // This check is required, if the callback fails and it isn't checked it will bring down the service
+    if (!returned.isOk())
+    {
+        ALOGE("V1_0::ArmnnDriverImpl::prepareModel: hidl callback failed to return properly: %s ",
+            returned.description().c_str());
+    }
+}
+
+Return<ErrorStatus> FailPrepareModel(ErrorStatus error,
+                                     const string& message,
+                                     const sp<IPreparedModelCallback>& callback)
+{
+    ALOGW("V1_0::ArmnnDriverImpl::prepareModel: %s", message.c_str());
+    NotifyCallbackAndCheck(callback, error, nullptr);
+    return error;
+}
+
+} // namespace
+
+namespace armnn_driver
+{
+namespace V1_0
+{
+
+Return<void> ArmnnDriverImpl::getCapabilities(
+        const armnn::IRuntimePtr& runtime,
+        neuralnetworks::V1_0::IDevice::getCapabilities_cb cb)
+{
+    ALOGV("V1_0::ArmnnDriverImpl::getCapabilities()");
+
+    neuralnetworks::V1_0::Capabilities capabilities;
+    if (runtime)
+    {
+        capabilities.float32Performance.execTime =
+            ParseSystemProperty(g_Float32PerformanceExecTimeName, .1f);
+
+        capabilities.float32Performance.powerUsage =
+            ParseSystemProperty(g_Float32PerformancePowerUsageName, .1f);
+
+        capabilities.quantized8Performance.execTime =
+            ParseSystemProperty(g_Quantized8PerformanceExecTimeName, .1f);
+
+        capabilities.quantized8Performance.powerUsage =
+            ParseSystemProperty(g_Quantized8PerformancePowerUsageName, .1f);
+
+        cb(ErrorStatus::NONE, capabilities);
+    }
+    else
+    {
+        capabilities.float32Performance.execTime = 0;
+        capabilities.float32Performance.powerUsage = 0;
+        capabilities.quantized8Performance.execTime = 0;
+        capabilities.quantized8Performance.powerUsage = 0;
+
+        cb(ErrorStatus::DEVICE_UNAVAILABLE, capabilities);
+    }
+
+    return Void();
+}
+
+Return<void> ArmnnDriverImpl::getSupportedOperations(
+        const armnn::IRuntimePtr& runtime,
+        const DriverOptions& options,
+        const neuralnetworks::V1_0::Model& model,
+        neuralnetworks::V1_0::IDevice::getSupportedOperations_cb cb)
+{
+    ALOGV("V1_0::ArmnnDriverImpl::getSupportedOperations()");
+
+    vector<bool> result;
+
+    if (!runtime)
+    {
+        cb(ErrorStatus::DEVICE_UNAVAILABLE, result);
+        return Void();
+    }
+
+    // Run general model validation, if this doesn't pass we shouldn't analyse the model anyway
+    if (!android::nn::validateModel(model))
+    {
+        cb(ErrorStatus::INVALID_ARGUMENT, result);
+        return Void();
+    }
+
+    // Attempt to convert the model to an ArmNN input network (INetwork).
+    ModelToINetworkConverter modelConverter(options.GetComputeDevice(), model,
+        options.GetForcedUnsupportedOperations());
+
+    if (modelConverter.GetConversionResult() != ConversionResult::Success
+        && modelConverter.GetConversionResult() != ConversionResult::UnsupportedFeature)
+    {
+        cb(ErrorStatus::GENERAL_FAILURE, result);
+        return Void();
+    }
+
+    // Check each operation if it was converted successfully and copy the flags
+    // into the result (vector<bool>) that we need to return to Android
+    result.reserve(model.operations.size());
+    for (uint32_t operationIdx = 0; operationIdx < model.operations.size(); operationIdx++)
+    {
+        bool operationSupported = modelConverter.IsOperationSupported(operationIdx);
+        result.push_back(operationSupported);
+    }
+
+    cb(ErrorStatus::NONE, result);
+    return Void();
+}
+
+Return<ErrorStatus> ArmnnDriverImpl::prepareModel(
+        const armnn::IRuntimePtr& runtime,
+        const armnn::IGpuAccTunedParametersPtr& clTunedParameters,
+        const DriverOptions& options,
+        const neuralnetworks::V1_0::Model& model,
+        const sp<IPreparedModelCallback>& cb,
+        bool  float32ToFloat16)
+{
+    ALOGV("V1_0::ArmnnDriverImpl::prepareModel()");
+
+    if (cb.get() == nullptr)
+    {
+        ALOGW("V1_0::ArmnnDriverImpl::prepareModel: Invalid callback passed to prepareModel");
+        return ErrorStatus::INVALID_ARGUMENT;
+    }
+
+    if (!runtime)
+    {
+        return FailPrepareModel(ErrorStatus::DEVICE_UNAVAILABLE,
+                                "V1_0::ArmnnDriverImpl::prepareModel: Device unavailable", cb);
+    }
+
+    if (!android::nn::validateModel(model))
+    {
+        return FailPrepareModel(ErrorStatus::INVALID_ARGUMENT,
+                                "V1_0::ArmnnDriverImpl::prepareModel: Invalid model passed as input", cb);
+    }
+
+    // Deliberately ignore any unsupported operations requested by the options -
+    // at this point we're being asked to prepare a model that we've already declared support for
+    // and the operation indices may be different to those in getSupportedOperations anyway.
+    set<unsigned int> unsupportedOperations;
+    ModelToINetworkConverter modelConverter(options.GetComputeDevice(), model,
+        unsupportedOperations);
+
+    if (modelConverter.GetConversionResult() != ConversionResult::Success)
+    {
+        FailPrepareModel(ErrorStatus::GENERAL_FAILURE, "ModelToINetworkConverter failed", cb);
+        return ErrorStatus::NONE;
+    }
+
+    // optimize the network
+    armnn::IOptimizedNetworkPtr optNet(nullptr, nullptr);
+    armnn::OptimizerOptions OptOptions;
+    OptOptions.m_ReduceFp32ToFp16 = float32ToFloat16;
+
+    try
+    {
+        optNet = armnn::Optimize(*modelConverter.GetINetwork(),
+                                 {options.GetComputeDevice()},
+                                 runtime->GetDeviceSpec(),
+                                 OptOptions);
+    }
+    catch (armnn::Exception &e)
+    {
+        stringstream message;
+        message << "armnn::Exception (" << e.what() << ") caught from optimize.";
+        FailPrepareModel(ErrorStatus::GENERAL_FAILURE, message.str(), cb);
+        return ErrorStatus::NONE;
+    }
+
+    // Check that the optimized network is valid.
+    if (!optNet)
+    {
+        FailPrepareModel(ErrorStatus::GENERAL_FAILURE,
+                         "V1_0::ArmnnDriverImpl::prepareModel: Invalid optimized network", cb);
+        return ErrorStatus::NONE;
+    }
+
+    // Export the optimized network graph to a dot file if an output dump directory
+    // has been specified in the drivers' arguments.
+    ExportNetworkGraphToDotFile(*optNet,
+                                options.GetRequestInputsAndOutputsDumpDir(),
+                                model);
+
+    // load it into the runtime
+    armnn::NetworkId netId = 0;
+    try
+    {
+        if (runtime->LoadNetwork(netId, move(optNet)) != armnn::Status::Success)
+        {
+            return FailPrepareModel(ErrorStatus::GENERAL_FAILURE,
+                "V1_0::ArmnnDriverImpl::prepareModel: Network could not be loaded", cb);
+        }
+    }
+    catch (armnn::Exception& e)
+    {
+        stringstream message;
+        message << "armnn::Exception (" << e.what()<< ") caught from LoadNetwork.";
+        FailPrepareModel(ErrorStatus::GENERAL_FAILURE, message.str(), cb);
+        return ErrorStatus::NONE;
+    }
+
+    unique_ptr<ArmnnPreparedModel> preparedModel(new ArmnnPreparedModel(
+        netId,
+        runtime.get(),
+        model,
+        options.GetRequestInputsAndOutputsDumpDir(),
+        options.IsGpuProfilingEnabled()
+    ));
+
+    // Run a single 'dummy' inference of the model. This means that CL kernels will get compiled (and tuned if
+    // this is enabled) before the first 'real' inference which removes the overhead of the first inference.
+    preparedModel->ExecuteWithDummyInputs();
+
+    if (clTunedParameters &&
+        options.GetClTunedParametersMode() == armnn::IGpuAccTunedParameters::Mode::UpdateTunedParameters)
+    {
+        // Now that we've done one inference the CL kernel parameters will have been tuned, so save the updated file.
+        try
+        {
+            clTunedParameters->Save(options.GetClTunedParametersFile().c_str());
+        }
+        catch (const armnn::Exception& error)
+        {
+            ALOGE("V1_0::ArmnnDriverImpl: Failed to save CL tuned parameters file '%s': %s",
+                options.GetClTunedParametersFile().c_str(), error.what());
+        }
+    }
+
+    NotifyCallbackAndCheck(cb, ErrorStatus::NONE, preparedModel.release());
+
+    return ErrorStatus::NONE;
+}
+
+Return<DeviceStatus> ArmnnDriverImpl::getStatus()
+{
+    ALOGV("V1_0::ArmnnDriverImpl::getStatus()");
+
+    return DeviceStatus::AVAILABLE;
+}
+
+} // armnn_driver::namespace V1_0
+} // namespace armnn_driver