Intel® DevCloud for the Edge is a computing resource to develop, test, and run your workloads across a range of Intel® CPUs, GPUs, and Movidius™ Myriad™ Vision Processing Units (VPUs). Running the DL Workbench in the DevCloud helps you optimize your model and analyze its performance on various Intel® hardware configurations. DevCloud is available for enterprise developers, independent developers, students, and faculty members.
When running the DL Workbench in the DevCloud, you can use the following DL Workbench features:
|Single and group inference||Yes|
(HDDL plugin is not supported)
|Winograd algorithmic tuning||No|
|Model output visualization||Yes|
|Visualization of runtime and Intermediate Representation (IR) graph||Yes|
|Connecting to your remote machine**||No|
|Downloading models from the Intel Open Model Zoo||Yes|
|Deployment package creation||Yes|
|JupyterLab* learning environment||No|
** In the DevCloud, you are connecting only to remote machines that are available in it. You cannot work with your local workstation or connect to other machines in your local network.
- Profiling and calibration on DevCloud machines take more time than on a local machine due to the exchange of models, datasets, the job script, and performance data.
- Inference results may insignificantly vary for identical environment configurations. This happens because the same environment in the DevCloud does not mean the same physical machine.
Watch this video to learn how to start DL Workbench in the Intel® DevCloud for the Edge:
Click this link to open the DL Workbench. Make sure your browser does not block pop-up windows as it prevents the tab from opening:
You have started the DL Workbench in the DevCloud. A DL Workbench session in the DevCloud is limited to four hours. Remaining session time is indicated in the upper-right corner of the interface:
After four hours, the Docker container with the DL Workbench stops, but your data is autosaved in the DevCloud. To continue working with the DL Workbench, restart the session.