This course covers concepts and approaches related to developing, profiling, tuning, and optimizing parallel software on multicore platforms from Intel, AMD, and Oracle Sun. Critical concepts and applied techniques are covered in detail to help you extract maximum performance from your applications. Specific techniques for tuning NUMA architectures, data race detection, profiling, and debugging are taught along with hands-on experience using Intel Threading Building Blocks and Array Building Blocks to parallelize software.

 

Length: 3 Days Cost: $3495

 

 

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"I'm pleased with both the course and the instructor. I would recommend both without hesitation." - Senior Member of Technical Staff, Sandia National Labs

 

"Thanks again for a great three days. This was the kick I needed to get moving." - Senior Member of Technical Staff, Sandia National Labs

 

"As always, the instructor's knowledge level and material presented were great. The instructor truly is an expert and it shows in every presentation." - Senior Member of Technical Staff, Sandia National Labs

 

"Thanks for this great multicore class. I really enjoyed it. I hope I get a chance to take one of your other courses." - Senior Member of Technical Staff, Sandia National Labs

 

 

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Software architects, developers, team leaders, and managers seeking to optimize and tune software running on multicore processors. Knowledge of parallel software development, the C++ programming language, and intermediate C++ software development experience is a pre-requisite for this course.

• A comprehensive training workshop: This course offers an in-depth overview of fundamental concepts, while offering advanced training and practical advice on profiling and optimizing C/C++ programs on multicore microprocessors.
• Gain critical insights on how to improve your software's performance: This course is designed to give you key skills using specialized tools to help you to correctly create, optimize, and tune parallel applications for multicore processors.
• Additional hands-on learning: This course provides laboratory sessions in optimizing and debugging parallel applications. It also includes walk-through laboratory exercises designed to increase your understanding of parallel tools, such as profilers and debuggers.

• Receive an in-depth theoretical background, covering processor memory models, NUMA hardware, operating systems kernels, multicore tuning, and modern multicore processors from Intel, AMD, and Oracle Sun.
• Cover critical concepts, such as sequential consistency, NUMA architectures, thread and memory affinity, locality, profiling, and tuning.
• Learn how to profile and tune parallel algorithms for best performance on multicore hardware.
• Define and correct multicore problems, such as false sharing, data races, unnecessary dependencies, load balancing, poor locality, and numerical performance.
• Explain operating system interactions and the relationship between shared memory and threads, including information on NUMA kernel support and multicore and power scheduling on Linux and Solaris operating systems.
• Explain how to deal with shared memory effectively and scalably including CPU selection, CPU-specific binding of threads, thread specific data, lock optimization, cache blocking, first-touch placement and data locality.
• Understand and use parallel technologies and programming methods, such as Intel TBB and Intel ABB using C++ and the Intel Compiler to express parallelism.
• Find data races using the Intel Thread Checker and Valgrind's ThreadSanitizer. Introduce pintool for dynamically instrumenting programs.
• Learn to use TAU (Tuning and Analysis Utilities), Open|SpeedShop, and likwid to profile applications.
• Learn to use Allinea DDT for debugging and visualizing parallel software.
• Gain hands-on experience with the Intel Compiler to build, tune, and run multithreaded programs during the laboratories and case studies.