High-Performance Computing (HPC) is a field that focuses on the use of supercomputers and advanced computing techniques to solve complex computational problems that require high processing capabilities. High-performance computing is used in multiple fields such as physics, chemistry, engineering, medicine, big data analysis, and deep learning. Here’s a comprehensive look at the key aspects of the HPC major:

HPC basics:

• Understand the basic principles of high-performance computing including parallel computing and distributed computing.
• Study the structure of supercomputers and how they work.

Parallel and distributed programming:

• Learn parallel programming techniques using languages ​​and frameworks such as MPI (Message Passing Interface) and OpenMP.
• Understand how to distribute tasks across multiple processing units to achieve better performance.

Operating systems for high-performance computing:

• Study of operating systems designed to support high-performance computing.
• Understand how to manage resources in large, parallel systems.

Data management and storage:

• Learn techniques for managing and storing big data in HPC environments.
• Use distributed file systems such as Lustre and GPFS.

Parallel algorithms:

• Develop and understand parallel algorithms that can be implemented on high-performance computers.
• Analyze the performance of algorithms and improve them to make the most of the computing infrastructure.

Cloud Computing:

• Using cloud computing technologies to support high-performance computing.
• Apply cloud services such as Amazon AWS and Google Cloud to run HPC applications.

Scientific and engineering applications:

• Application of HPC techniques in fields such as astrophysics, quantum chemistry, simulation engineering, and climate modeling.
• Develop simulation programs and mathematical models to solve complex scientific and engineering problems.

Performance analysis and improvement:

• Measure and analyze the performance of high-performance applications.
• Apply performance improvement techniques such as data and task parallelism, and optimize memory usage.

HPC Security:

• Study security challenges in HPC environments.
• Apply security strategies to protect data and computations in parallel and distributed systems.

Artificial Intelligence and Deep Learning:

• Using HPC technologies to accelerate deep learning and big data analysis processes.
• Application of HPC in training artificial intelligence models on large data sets.

Practical training and applied projects:

• Obtain practical experience through training in supercomputing centers and research laboratories.
• Apply theoretical knowledge in practical projects to analyze and process large and complex data.

Research and development in high-performance computing:

• Participate in research to develop new technologies and methods in the field of HPC.
• Publishing research and participating in scientific conferences to share results and innovations.

Interaction with industry:

• Work with advanced technology companies and research centers to develop HPC solutions that meet industry needs.
• Understand HPC applications in industry and how to improve productivity and efficiency.

Ethics and laws in high performance computing:

• Understand the ethical and legal issues related to the use of HPC.
• Apply ethical principles in all aspects of work in high performance computing.

The High Performance Computing major provides broad job opportunities in multiple fields such as scientific research, industry, technology, and medicine. This specialization contributes to the development of innovative technical solutions that contribute to solving complex problems and improving efficiency and productivity in various sectors.