This course covers concepts and approaches related to programming GPU processors using the PGI Accelerator™ programming model. Extensive coverage of GPU hardware, memories, data transport, and performance optimization enable the student to understand the fundamental aspects of GPU programming. In-depth, hands-on lectures and laboratories demonstrate how to apply the PGI Accelerator to students' software. Using the PGI Accelerator, students will capitalize on low-cost, high performance GPU computing hardware to improve application performance while reducing maintenance and porting requirements.

 

Length: 2 Days Cost: $1895

 

 

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Software architects, developers, team leaders, and managers seeking to improve their GPU software skills using the PGI Accelerator Programming Model with C or Fortran. Knowledge of computer architectures and intermediate C or Fortran programming, as well as corresponding software development experience are mandatory pre-requisites for this course.

• Offers a detailed overview of fundamental concepts, while providing advanced training and practical advice on GPU programming using the PGI Accelerator compiler.
• Teaches everything necessary to start developing high-performance GPU software on Linux, Windows, and Mac platforms using the PGI Accelerator programming model.
• Demonstrates how programmers can gain detailed control over loop mapping, memory allocation, and optimization for the GPU memory hierarchy.
• Shows how to use the PGI Accelerator programming model to take advantage of massive parallelism, increase throughput, minimize data traffic, and improve program portability.
• Learn to reduce the costs associated with parallel programming by harnessing the potential of GPU processing power.

• Correctly indentify concurrency opportunities and parallelize algorithms to run on the GPU.
• Install NVIDIA and PGI tools and compile CUDA and PGI Accelerator programs.
• Understand the NVIDIA GPU hardware platform and the underlying technical architecture, including high-throughput SIMD processing and hardware threading architecture concepts.
• Recognize the difference between GPU memory types and the advantages and disadvantages of each.
• Learn to determine the best methods for software development with the PGI Accelerator programming model.
• Understand the PGI Accelerator command set and its application to C and Fortran codes.
• Learn the specific skills to accelerate applications on x64+GPU platforms with the PGI Accelerator compilers.
• Learn to tune data movement, memory loads and stores, and loop schedules for maximum effect.
• Effectively orchestrate the tranport of data to and from GPU memory.
• Learn to meld multicore processors and GPUs to take maximum advantage of modern platform performance.
• Discover how to take advantage of multiple GPUs in the same computer.
• Cover debugging strategies for PGI Accelerator codes.
• Participate in hands-on laboratories to reinforce the theory and concepts presented in the class.