Introduction to JupyterLab and Notebooks

Use Jupyter notebooks to modify and run code as part of learning exercises.

To begin, open Introduction_to_Jupyter.ipnyb.

Introduction to DPC++

• Articulate how oneAPI can help to solve the challenges of programming in a heterogeneous world.
• Use oneAPI solutions to enable your workflows.
• Understand the DPC++ language and programming model.
• Become familiar with using Jupyter notebooks for training throughout the course.

DPC++ Program Structure

• Articulate the SYCL fundamental classes.
• Use device selection to offload kernel workloads.
• Decide when to use basic parallel kernels and ND Range Kernels.
• Create a host accessor.
• Build a sample DPC++ application through hands-on lab exercises.

DPC++ Unified Shared Memory

• Use new DPC++ features like Unified Shared Memory (USM) to simplify programming.
• Understand implicit and explicit ways of moving memory using USM.
• Solve data dependency between kernel tasks in an optimal way.

DPC++ Sub-Groups

• Understand advantages of using Sub-groups in DPC++
• Take advantage of Sub-group collectives in ND-Range kernel implementation
• Use Sub-group Shuffle operations to avoid explicit memory operations

Demonstration of Intel® Advisor

• See how Offload Advisor¹ identifies and ranks parallelization opportunities for offload.
• Run Offload Advisor using command line syntax.
• Use performance models and analyze generated reports.

¹Offload Advisor is a feature of Intel Advisor⁽ᴮᵉᵗᵃ⁾ installed as part of the Intel oneAPI Base Toolkit.

Intel® VTune™ Profiler on Intel® DevCloud

• Profile a DPC++ application using Intel® VTune™ Profiler⁽ᴮᵉᵗᵃ⁾ on Intel® DevCloud.
• Understand the basics of command line options in Intel VTune Profiler to collect data and generate reports.