Wouldn’t it be great if we could port a code to a new high-performance architecture without substantially changing the code yet achieving a similar level of performance as hand-optimized code? This webinar will frame the discussion around ‘performance portability’, why it is important and desirable, and how to quantitatively measure it. The webinar will start with a background check on how the concept of performance portability came about and past attempts to define it and quantify it. Then we will introduce a simple yet powerful metric and an empirical methodology to quantitatively assess a code’s performance portability across multiple platforms. The methodology uses the Roofline performance model to measure an ‘architectural efficiency’ term in the metric proposed by Pennycook et al. We will dive into a few nuances of this methodology, for example, how and why empirical ceilings should be used for performance bounds, how to accurately account for complex instructions such as divides, how to model strided memory accesses, and how to select the appropriate Roofline ceilings and application performance points to make sure that the performance portability analysis is not erroneously skewed. We will also show some results of measuring performance portability using the aforementioned metric and methodology on two modern architectures, Intel Xeon Phi and NVIDIA V100 GPUs.

Presenters

• John Pennycook (Intel)
• Charlene Yang (Lawrence Berkeley National Laboratory)
• Jack Deslippe (Lawrence Berkeley National Laboratory)

Presenter Bios

John Pennycook is an HPC Application Engineer in the HPC Ecosystem and Applications team at Intel Corporation, focused on enabling developers to fully utilize the parallelism available in modern processors. He is experienced in optimizing and parallelizing applications from a range of scientific domains, and serves as Intel’s representative on the steering committee for the Intel eXtreme Performance Users Group. John has a PhD in Computer Science from the University of Warwick.

Charlene Yang is an application performance specialist at NERSC, LBNL. Her work is focused on performance characterization, performance optimization, and performance portability. Charlene works with code teams in the NERSC Exascale Science Application Program, helps identify their codes’ performance bottlenecks and provides advice on optimization strategies. Charlene is an advocate of Roofline Performance Model and has been actively involved in the development of this model. Charlene holds a PhD degree in Electrical and Electronic Engineering from The University of Western Australia.

Jack Deslippe is the application performance group lead at NERSC. Jack and his group are partnering with DOE application teams to evaluate and improve the performance of applications on Cori and future systems at NERSC. He received a Ph.D. from UC Berkeley in physics in 2011, with research centered on computational materials physics and nano-science, including the development and scaling of electronic-structure codes. Jack has been at NERSC since 2011, acting as a consultant and developer for materials science applications and currently leads the NERSC Exascale Science Applications Program (NESAP).