High-Performance GPU Acceleration—Part 1: Code Design

Heterogeneous computing comes with the challenge of designing code that can work in multiprocessor and multiaccelerator environments. Developers need to be equipped with the right set of metrics to make informed design and optimization decisions that take advantage of target hardware.

In Part 1 of this two-part webinar series, technical consulting engineer Cory Levels focuses on designing software for efficient offload from CPUs to GPUS—even before final hardware is available—using Intel® Advisor. Using a walkthrough of an ISO 3D Isotropic Finite Difference example, learn how to:

• Optimize your CPU application for memory and compute.
• Identify efficient GPU offload opportunities and quantify the potential performance speedup.
• See performance headroom of your GPU offloaded code against hardware limitations, and get insights for an effective optimization roadmap.

• Get Intel Advisor 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 Advisor.

• Sign up for an Intel® Tiber™ AI 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.