In this episode of Code Together, we talk to Alice Chan, Vice President and General Manager of Compiler Engineering at Intel, and Hal Finkel, Lead for Compiler Technology and Programming Languages at Argonne National Lab, about how the industry is uniting to address the need for programming portability and performance across diverse architectures, particularly important with the rise of data-intensive workloads like artificial intelligence and machine learning. We discuss the important shift to modern C++ programming models, and how the cross-industry oneAPI initiative, and DPC++, bring much-needed portable performance to today’s developers.

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Tags: Alice Chan, Argonne National Lab, artificial intelligence, C++, Compiler Engineering, Compiler Technology, cross-architecture, CUDA, developers, DPC++, GPU, Hal Finkel, hardware abstraction, heterogeneous, Khronos, machine learning, oneAPI, Programming Languages, programming portability, SYCL
 
Posted in: Artificial Intelligence, Audio Podcast, Code Together, Intel