SC17 will be special in many ways. For one, it marks the conference’s 30th year and it also is the first time that the General Chair is from the international community. Bernd Mohr hails from Germany, works at the Jülich Supercomputing Centre, and is an avid outdoors man/hiker. He has served as a SC volunteer for many years and also sits on the SC Steering Committee.
Recently, HPCwire named him as one of their “People to Watch in 2017”. Listed below is an excerpt from that interview as well as a link to the entire article on their website.
HPCwire: Congratulations on being named General Chair for SC17! As the first SC General Chair from outside the US, what perspective will you be bringing to the role?
Thank you! Since people travel from all over the globe to come to a SC conference, one of our goals is to make certain that SC17 feels truly international. While SC is organized in a different US city every year, from the start it has been THE event where people from around the globe come together to network and to learn about the latest advancements in HPC, networking, data analytics and storage. The percentage of international attendees has steadily grown over the years and is now more than 25%. Within the SC committees, the percentage is even higher; over a third of our volunteers are from outside the US.
We also want to showcase that many interesting projects and research in HPC are done all over the world. While the community is following the Exascale efforts in the US, Japan, China and Europe, there is also amazing HPC work and research happening in places like South Africa, India, Saudi Arabia, Chile, Argentina, Brazil, and Mexico. Not to mention that our exhibit floor is generally sold out to capacity with companies coming from far away as Australia to participate in the SC experience.
We will also continue to promote diversity in HPC which has always been important to the organization, but was officially “started” at SC16 by General Chair John West from the Texas Advanced Computing Center. For SC17, we will work on extending this beyond the issue of gender and consider other factors like ethnicity and age.
This is an exciting time in the world of high performance computing – it truly has never been more important globally and I am proud to be so involved with such brilliant industry leaders and colleagues. We intend to make SC17 in Denver an international conference that is not to be missed.
HPCwire: What are some of the major trends today in HPC that you’ll be looking out for in 2017? You are active in several exascale research efforts, including the International Exascale Software Project as well as European and Jülich Exascale efforts. What developments do you see as the most promising and what are the thorniest challenges?
The hot topic is currently Deep Learning, other (big) data analytics methods and tools, and how they can be integrated with workflows to analyze large data sets coming from scientific instruments or HPC simulations. In this regard, I just want to point out that SC since 2009(!) has been called the International Conference on High Performance Computing, Networking, Analysis, and Storage. So SC had these topics on their radar for quite some time and it is nice to see that the HPC community finally realizes that there are other important issues beyond flops and vectorization.
Currently people are using different hardware configurations and software stacks for compute and data-driven workflows. It will be interesting to see whether the technology will advance to provide the capability to architect a common hardware and software platform to handle both sorts of workflows and to combine them, at least in the context of scientific data and HPC.
Finally, we currently see a variety of processor types (multicore, manycore, GPGPU) and cluster architectures (homogeneous and heterogeneous) and with it a plethora of programming models and tools. While this makes a great topic for panel discussions, research projects and hundreds of research papers for HPC experts, it is a nightmare for application programmers and users who struggle to adapt and optimize their codes for all these architectures. While with some effort, it might be possible to make a code run on many platforms, it is very difficult if not impossible to make the code execute efficiently and with comparable performance on all systems.