Heterogeneous application development has introduced new challenges for experienced and novice developers alike. In particular, the need to understand how your programming language maps algorithms to each device.

This webinar focuses on how to gain that understanding for cross-architecture applications written in Data Parallel C++ (DPC++). Specifically, it showcases how Flow Graph Analyzer, a feature of Intel® Advisor, provides insights into efficiencies of DPC++ constructs that help you improve algorithm performance.

Join Intel® software specialists Anoop Madhusoodhanan Prabha and Kevin O’Leary to learn about:

  • The asynchronous task graph of your DPC++ algorithms and its similarities with other commonly used heterogeneous programming models
  • How to identify performance penalties using diagnostics reported on simple language use
  • How to determine scheduling inefficiencies—which kernels can be executed independently or if the kernels are being scheduled as intended
  • Flow Graph Analyzer reports and recommendations that can help improve the performance of data parallel algorithms

Includes demonstrations and code walk-throughs.

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Other Resources

  • Sign up for an Intel® DevCloud account—a free development sandbox with access to the latest Intel® hardware and oneAPI software.
  • Explore oneAPI, including developer opportunities and benefits.
  • Subscribe to the podcast—Code Together is an interview series that explores the challenges at the forefront of cross-architecture development. Each biweekly episode features industry VIPs who are blazing new trails through today’s data-centric world. Available wherever you get your podcasts.

Anoop Madhusoodhanan Prabha
Software engineer, Intel’s Software and Services Group, technical consulting engineer Intel® C and Intel® C++ Compilers support team

Anoop Madhusoodhanan joined Intel in 2009. Since then, he has worked on optimizing various customer applications by enabling multithreading, vectorization and other microarchitecture tunings. He has experience working with OpenMP*, Intel® Cilk™ Plus, Intel® Threading Building Blocks, and CUDA*. His interests are in processor and GPU architecture, heterogeneous computing, and high-performance computing. He has a master degree in electrical engineering from State University of New York at Buffalo. His email is anoop.madhusoodhanan.prabha@intel.com


Kevin O’Leary
Senior software developer and lead technical consulting engineer, Intel Corporation

Kevin O’Leary's expertise includes compilers, debuggers, and software performance tools. He’s currently responsible for performance optimization using Intel® Advisor and Intel® VTune™ Profiler, and was a key developer of the Intel® Parallel Studio XE development suite. Prior to joining Intel, Kevin spent many years as a debugger engineer for IBM Rational Software*.

Kevin holds a bachelor degree in computer science from University of Massachusetts and a master degree in computer science from Oregon Health and Science University.



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