The Barcelona Supercomputing Center (BSC) currently offers a number of courses covering CUDA architecture and programming languages for parallel computing. Please contact us for possible collaborations.

The 12th edition of the Programming and Tuning Massively Parallel Systems + Artificial Intelligence summer school (PUMPS+AI) is aimed at enriching the skills of researchers, graduate students and teachers with cutting-edge technique and hands-on experience in developing applications for many-core processors with massively parallel computing resources like GPU accelerators.

• Summer School Co-Directors: Mateo Valero (BSC and UPC) and Wen-mei Hwu (University of Illinois at Urbana-Champaign / NVIDIA)
• Local Organizers: Antonio J. Peña (Chair, BSC), Marc Jordà (BSC)
• Dates:
  • Applications due: July 17, 2022 Last spots available, first come first served
    • Due to space limitations, early application is strongly recommended. You may also be suggested to attend an online prerequisite training on basic CUDA programming before joining PUMPS.
  • Notification of acceptance:July 25, 2022 First come, first served

• Location: UPC Campus Nord, Barcelona (Spain)

• Organized by:
  • Barcelona Supercomputing Center (BSC)
  • University of Illinois at Urbana-Champaign (University of Illinois)
  • HiPEAC Network of Excellence (HiPEAC)
  • PUMPS is part of this year PRACE Advanced Training Centre program

• The following is a list of some of the topics that will be covered during the course:
  • Deep Learning / AI engine internals
  • High-level programming models (OpenACC, Python, and Mathematica on GPUs)
  • CUDA Algorithmic Optimization Strategies
  • Dealing with Sparse and Dynamic data
  • Efficiency in Large Data Traversal
  • Reducing Output Interference
  • Controlling Load Imbalance and Divergence
  • Acceleration of Collective Operations
  • Dynamic Parallelism and HyperQ
  • Debugging and Profiling CUDA Code
  • Multi-GPU Execution
  • Architecture Trends and Implications
  • Introduction to OmpSs and to the Paraver analysis tool
  • OmpSs: Leveraging GPU/CUDA Programming
  • Hands-on Labs: CUDA Optimizations on Scientific Codes; OmpSs Programming and Tuning

• Instructors:
  • Featured Lecturers: Wen-mei Hwu (NVIDIA)
  • Invited Lecturers: Juan Gómez-Luna (ETH Zurich)
  • BSC / UPC Lecturers: Antonio J. Peña, Marc Jorda, Leonidas Kosmidis, Bernat Font, Xavier Martorell and Xavier Teruel
• Prerequisites for the course are:
  • Basic CUDA knowledge is required to attend the course. Applicants that cannot certify their experience in CUDA programming will be asked to take a short on-line course covering the necessary introductory topics
  • C, C++, Java, or equivalent programming knowledge. Skills in parallel programming will be helpful

• Registration for the course is free for attendees from academia and public institutions. Please note that travel, lodging, and meals are not covered. Applicants from non-academic institutions (companies), please contact us by email at pumps at bsc.es for sponsorship possibilities.

• By the end of the summer school, participants will:
  • Be able to design algorithms (including deep learning / AI) that are suitable for accelerators.
  • Understand the most important architectural performance considerations for developing parallel applications.
  • Be exposed to computational thinking skills for accelerating applications in science and engineering.
  • Engage computing accelerators on science and engineering breakthroughs.

• Programming Languages: CUDA, MPI, OmpSs, OpenACC
• Hands-on Labs: Afternoon labs with teaching assistants for each audience/level.
  • Participants are expected to bring their own laptops to access the servers with GPU accelerators.
  • The afternoon lab sessions will provide hands-on experience with various languages and tools covered in the lectures and will comprise a brief introduction to the programming assignments, followed by independent work periods. Teaching assistants will be available in person and on the web to help with assignments.