HDDL Device

Introducing the HDDL Plugin

The OpenVINO Runtime HDDL plugin was developed for inference with neural networks on Intel® Vision Accelerator Design with Intel® Movidius™ VPUs. It is designed for use cases that require large throughput for deep learning inference, up to dozens of times more than the MYRIAD Plugin.

Configuring the HDDL Plugin

To configure your Intel® Vision Accelerator Design With Intel® Movidius™ on supported operating systems, refer to the Additional Configurations for VPU in Installation Guide.

Note

The HDDL and Myriad plugins may cause conflicts when used at the same time. To ensure proper operation in such a case, the number of booted devices needs to be limited in the ‘hddl_autoboot.config’ file. Otherwise, the HDDL plugin will boot all available Intel® Movidius™ Myriad™ X devices.

Supported networks

To see the list of supported networks for the HDDL plugin, refer to the list on the MYRIAD Plugin page.

Supported Configuration Parameters

For information on VPU common configuration parameters, see the VPU Plugins. When specifying key values as raw strings (when using the Python API), omit the KEY_ prefix.

In addition to common parameters for both VPU plugins, the HDDL plugin accepts the following options:

Parameter Name

Parameter Values

Default

Description

KEY_PERF_COUNT

YES / NO

NO

Enables performance counter option.

KEY_VPU_HDDL_GRAPH_TAG

string

empty string

Allows executing network on specified count of devices.

KEY_VPU_HDDL_STREAM_ID

string

empty string

Allows executing inference on a specified device.

KEY_VPU_HDDL_DEVICE_TAG

string

empty string

Allows allocating/deallocating networks on specified devices.

KEY_VPU_HDDL_BIND_DEVICE

YES / NO

NO

Enables the network to be bound to a device. Refer to the ‘vpu_plugin_config.hpp’ file.

KEY_VPU_HDDL_RUNTIME_PRIORITY

signed int

0

Specifies the runtime priority of a device among all devices running the same network. Refer to the vpu_plugin_config.hpp file.