Approaches to Parallelism: Choosing Your Models and Tools

Get an overview of these long-lived parallel programming workhorses, including their strengths and the types of problems each is best suited for.

Two decades is a millennium in technology years. And yet … Message Passing Interface (MPI), Open Multi-Processing* (OpenMP*) and Intel® Threading Building Blocks (Intel® TBB) have made the cut, helping the global developer community parallelize code for 25, 20 and 11 years, respectively. Pretty impressive. And they remain popular largely because they’re based on open source and standards-driven implementations, and they offer intuitive approaches to parallelism. Join us in this webinar where we’ll:

  • Explore the strengths of each parallel model
  • Discuss the types of problems for which each is best suited
  • Describe the latest features of each (spoiler alert :: the latest OpenMP specs provide directive-based approaches to accelerator offload and vectorization, and Intel TBB flow graph classes and functions allow easy expression of unstructured parallelism, dependency graphs, and data flow algorithms)

Cover the programming tools available to develop, debug and tune MPI, OpenMP and Intel TBB programs. If you haven’t yet, be sure to download both Intel® MPI Library and Intel TBB—part of the free Intel® Performance Libraries.

About the speaker

Henry A. Gabb , PhD, Sr. Principal Engineer, Intel Corporation

Henry is a senior principal engineer in the Intel Software and Services Group, Developer Products Division, and is the editor of The Parallel Universe, Intel’s quarterly magazine for software innovation. He first joined Intel in 2000 to help drive parallel computing inside and outside the company. He transferred to Intel Labs in 2010 to become the program manager for various research programs in academia, including the Universal Parallel Computing Research Centers at the University of California at Berkeley and the University of Illinois at Urbana-Champaign. Prior to joining Intel, Henry was Director of Scientific Computing at the U.S. Army Engineer Research and Development Center MSRC, a Department of Defense high-performance computing facility. Henry holds a B.S. in biochemistry from Louisiana State University, an M.S. in medical informatics from the Northwestern Feinberg School of Medicine, and a PhD in molecular genetics from the University of Alabama at Birmingham School of Medicine. He has published extensively in computational life science and high-performance computing. Henry recently rejoined Intel after spending four years working on a second PhD in information science at the University of Illinois at Urbana-Champaign, where he established an expertise in applied informatics and machine learning for problems in healthcare and chemical exposure.

Performance varies by use, configuration, and other factors. Learn more at www.Intel.com/PerformanceIndex.