High-Performance GPU Acceleration—Part 2: Offload Performance

Developers who deploy applications across CPUs to GPUs are often challenged to find the best methods for analyzing and optimizing offload performance.

In Part 2 of this webinar series, technical consulting engineer Kevin O’Leary focuses on tuning software for optimal performance once hardware is available. He uses Intel® VTune™ Profiler, a performance analyzer that takes the guesswork out of cross-architecture improvements. (Part 1 of this series focuses on designing software for efficient offload even before hardware is available.)

Using a sample application written in Data Parallel C++ (DPC++), Kevin demonstrates how Intel VTune Profiler can:

• Profile DPC++, OpenMP* offload, and code running on host and GPU processors
• Collect the right data and turn it into rich, interpretable analysis
• Identify the hot spots in your compute kernels, including which are key areas for optimization
• Show how the GPU resources are being used and locate hardware bottlenecks

• Get Intel VTune Profiler as part of the Intel® oneAPI Base Toolkit—a foundational set of tools and libraries for developing high-performance, data-centric applications across diverse architectures.
• Get the stand-alone version of Intel VTune Profiler.

• Sign up for an Intel® Developer Cloud account—a free development sandbox with access to the latest Intel hardware and oneAPI software.
• Explore oneAPI including developer opportunities and benefits.
• Subscribe to Code Together—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.