7th PUMPS Summer School, 2016
Objectives
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Organized by:
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Barcelona Supercomputing Center (BSC)
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University of Illinois at Urbana-Champaign (University of Illinois)
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Universitat Politecnica de Catalunya (UPC)
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HiPEAC Network of Excellence (HiPEAC)
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PUMPS is part of this year PRACE Advanced Training Centre program
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The following is a list of some of the topics that will be covered during the course:
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CUDA Algorithmic Optimization Strategies
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Dealing with Sparse and Dynamic data
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Efficiency in Large Data Traversal
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Reducing Output Interference
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Controlling Load Imbalance and Divergence
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Acceleration of Collective Operations
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Dynamic Parallelism and HyperQ
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Debugging and Profiling CUDA Code
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Multi-GPU Execution
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Architecture Trends and Implications
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Introduction to OmpSs and to the Paraver analysis tool
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OmpSs: Leveraging GPU/CUDA Programming
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Hands-on Labs: CUDA Optimizations on Scientific Codes; OmpSs Programming and Tuning
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Distinguished Lecturers: Wen-mei Hwu (University of Illinois at Urbana-Champaign) and David Kirk (NVIDIA Corporation )
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Invited Lecturer: Juan Gómez-Luna (Universidad de Córdoba)
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BSC / UPC Lecturers: Xavier Martorell and Xavier Teruel
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Teaching Assistants: Abdul Dakkak, Carl Pearson, Simon Garcia de Gonzalo, Marc Jorda, Pau Farre, Javier Bueno, Aimar Rodriguez
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Prerequisites for the course are:
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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
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C, C++, Java, or equivalent programming knowledge. Skills in parallel programming will be helpful
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Preliminary Overview
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By the end of the summer school, participants will:
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Be able to design algorithms that are suitable for accelerators.
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Understand the most important architectural performance considerations for developing parallel applications.
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Be exposed to computational thinking skills for accelerating applications in science and engineering.
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Engage computing accelerators on science and engineering breakthroughs.
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Programming Languages: CUDA, MPI, OmpSs, OpenCL
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Hands-on Labs: Afternoon labs with teaching assistants for each audience/level.
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Participants are expected to bring their own laptops to access the servers with GPU accelerators.
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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.
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Requirements
Basic knowledge of C/C++ programming
Attendees will need to bring their own laptops with a SSH client
Materials
INTELLECTUAL PROPERTY RIGHTS NOTICE:
• The User may only download, make and retain a copy of the materials for his/her use for non‐commercial and research purposes.
• The User may not commercially use the material, unless has been granted prior written consent by the Licensor to
do so; and cannot remove, obscure or modify copyright notices, text acknowledging or other means of identification or disclaimers as they appear.
• For further details, please contact BSC‐CNS patc [at] bsc [dot] es