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"Open Source Heterogeneous Programming for Python* Developers"

Watch how to offload Python data and workloads to any SYCL device, such as GPUs, with little code effort.

The session includes technical demos that showcase the Data Parallel Extensions for Python language* in action, including the speedups at every step ultimately enabling you to offload Python data and workloads to any SYCL device, such as GPUs, with little code effort.

Watch this session to learn how to: 

• Use the extensions for open source heterogeneous computing and compilation.
• Write SYCL kernels in Python.
• Use a just-in-time (JIT) compilation in Python on any SYCL device for near-native performance
• Achieve data interoperability and scale via powerful drop-in replacements for NumPy and Numba*.

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