IWOCL / SYCLcon DIGITAL

COVID-19 UPDATE — Last updated Mar 12

IWOCL and SYCLcon 2020 will now take place as a digital event starting the week of the 27th April.

We will be contacting all our speakers and poster authors in the coming days with details of the new arrangements for recording their presentations for on-demand viewing.  The proceedings will be published as planned and according to the schedules already announced.

Delegates who have already registered will be contacted and issued a refund.  Registration for IWOCL / SYCLcon Digital will be free and will include access to those parts of the program that we plan to live broadcast (e.g. panel discussions).

—  More details to follow  —

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Join us online for the 8th International Workshop on OpenCL (IWOCL) and SYCLcon 2020 for all the latest research, insights and knowledge sharing from the international community of high-performance computing specialist working with OpenCL, SYCL, SPIR and Vulkan for compute.  The online content provides a rich mix of tutorials, technical presentations, research papers, posters and panel discussions.  It also provides a formal channel for community feedback to the Khronos Group, the industry body responsible for the standards.

The call for submissions is now closed and the program is currently being compiled and is expected to cover:

  • Scientific and high-performance computing (HPC) application development
  • Machine Learning Training and Inferencing
  • The use of OpenCL and SYCL on CPU, GPU, DSP, NNP, FPGA and hardware accelerators for mobile, embedded, cloud, edge and automotive platforms
  • Development tools, including debuggers and profilers
  • HPC frameworks developed on top of OpenCL, SYCL or Vulkan
  • The emerging use of Vulkan in scientific and high-performance computing (HPC)
OpenCL Conference

Keynote Presentation

Preparing to Program Aurora at Exascale:
Early Experiences and Future Directions

Hal Finkel

Lead, Compiler Technology and Programming Languages
Leadership Computing Facility, Argonne National Laboratory

Argonne National Laboratory’s Leadership Computing Facility will be home to Aurora, our first exascale supercomputer. Aurora promises to take scientific computing to a whole new level, and scientists and engineers from many different fields will take advantage of Aurora’s unprecedented computational capabilities to push the boundaries of human knowledge. In addition, Aurora’s support for advanced machine-learning and big-data computations will enable scientific workflows incorporating these techniques along with traditional HPC algorithms.

Argonne National Laboratory’s Leadership Computing Facility will be home to Aurora, our first exascale supercomputer. Aurora promises to take scientific computing to a whole new level, and scientists and engineers from many different fields will take advantage of Aurora’s unprecedented computational capabilities to push the boundaries of human knowledge. In addition, Aurora’s support for advanced machine-learning and big-data computations will enable scientific workflows incorporating these techniques along with traditional HPC algorithms.

Programming the state-of-the-art hardware in Aurora will be accomplished using state-of-the-art programming models. Some of these models, such as OpenMP, are long-established in the HPC ecosystem. Other models, such as Intel’s oneAPI, based on SYCL, are relatively-new models constructed with the benefit of significant experience. Many applications will not use these models directly, but rather, will use C++ abstraction libraries such as Kokkos or RAJA. Python will also be a common entry point to high-performance capabilities. As we look toward the future, features in the C++ standard itself will become increasingly relevant for accessing the extreme parallelism of exascale platforms.

This presentation will summarize the experiences of our team as we prepare for Aurora, exploring how to port applications to Aurora’s architecture and programming models, and distilling the challenges and best practices we’ve developed to date. oneAPI/SYCL and OpenMP are both critical models in these efforts, and while the ecosystem for Aurora has yet to mature, we’ve already had a great deal of success.

Importantly, we are not passive recipients of programming models developed by others. Our team works not only with vendor-provided compilers and tools, but also develops improved open-source LLVM-based technologies that feed both open-source and vendor-provided capabilities. In addition, we actively participate in the standardization of OpenMP, SYCL, and C++. To conclude, I’ll share our thoughts on how these models can best develop in the future to support exascale-class systems.

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