High-Performance GPU Acceleration – Part 1: Code Design
Learn how to design software for CPU-to-GPU offload—plus how to optimize the GPU code—using the intuitive user interface of Intel Advisor. Part 1 of a 2-part series.
Heterogeneous computing comes with the challenge of designing code that can work in multi-processor/accelerator 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 2-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 3DFD example (3D isotropic Finite Difference), you will learn how to:
- Optimize your CPU application for memory and compute
- Identify efficient GPU offload opportunities and quantify the potential performance speed up
- See performance headroom of your GPU offloaded code against hardware limitations, and get insights for an effective optimization roadmap
(Part 2 coming in November)