|This course covers concepts and approaches related to programming GPU processors using OpenACC directives and the PGI AcceleratorTM 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 OpenACC directives to serial software. Using a directive based approach, 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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Pre-Assessment | Testimonials
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.
This comprehensive workshop will give you the framework and details you need to apply to your next multicore programming project. The benefits of this course include:
- Offers a detailed overview of fundamental concepts, while providing advanced training and practical advice on GPU programming using OpenACC directives and PGI Accelerator Workstation.
- 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 OpenACC directives 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.
Our goal is to give you the information you need to succeed in your next multicore programming project. While we will adjust the details to suit your needs, here is what you will learn in this course:
- Correctly indentify concurrency opportunities and parallelize algorithms to run on the GPU.
- Install NVIDIA and PGI tools and compile CUDA and OpenACC 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 OpenACC API.
- 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.