If you want to become a high-performance computing engineer, it is not difficult to get started and master the relevant foundation.
The key lies in interest and self-motivation, because this is a field that is biased toward low-level development and requires a solid foundation in C and C++ programming.
In addition, mathematical ability is also very important, because algorithm development involves some basic mathematical knowledge. For most people, it is enough to learn the basics of matrix calculations or linear algebra without going beyond these areas.
In addition, understanding the principles of computer composition is also an essential knowledge for high-performance computing engineers. This field involves the combination of software and hardware. It is necessary to have a certain understanding of the principles of computer composition. Although it is not necessary to design computers or chips, it is very important to understand the basic architecture and principles. It is even better if you also have parallel computing experience, because techniques such as parallelization and heterogeneous computing are very important in the field of high-performance computing.
The most important thing is to be interested in this field and keep your original intention. If you are interested in this field, it is no problem to choose it. Compared with the algorithm development of some AI applications, high-performance computing may not be able to attract attention by building a framework and displaying effects like the latter, but pays more attention to performance optimization and evaluation.
For additional HPC project experience, work on academic research projects, open source projects, or internships. In addition, participating in competition projects and continuing education training is also a good choice. Through these avenues, you can collaborate with professionals, expand your network, and improve your own practical ability.
The field requirements of high-performance computing engineers are significantly different from those of upper-level application development. In the field of high-performance computing, the requirements for scientific research papers are relatively high, and the competition is fierce. This is because there are relatively few people working in this field, so the level of competition is high. Moreover, since high-performance computing involves the construction of underlying systems and prototype systems, the requirements for system capabilities are higher.
If you are interested in this field and have the pursuit of system development, high performance computing is definitely an ideal direction. It may not pursue gorgeous effects and visual displays like other fields, but pay more attention to actual performance indicators. In the field of high-performance computing, you will pay more attention to the evaluation of performance charts, calculation time, scalability, etc., which may be relatively boring. However, that doesn't mean it lacks challenge and fulfillment.
Compared with upper-level application development, high-performance computing has unique requirements in terms of technical requirements and publishing papers. There are relatively few top conferences in this field, and the number of accepted articles is limited. This is mainly due to the fact that there are relatively few practitioners in the field of HPC, and thus the level of competition is high. Whether it is a graduation thesis or a scientific research project, you need to reach the level of prototype system development, not just publish a few papers. This puts higher requirements on your system capabilities, which is also a significant difference from typical algorithm development and upper-level application development in other fields.
If you are interested in this field and maintain a passion for system development, then high performance computing is undoubtedly an ideal direction. To succeed in this field, you need a firm interest and self-motivation, a solid programming foundation, good mathematical ability, an understanding of computer composition principles, and familiarity with related technologies such as parallel computing. By accumulating project experience, participating in competitions, continuing to learn and looking for cooperation opportunities, you will gradually grow into an excellent high-performance computing engineer.
Here, Yuancode Technology (https://www.ydma.com) has prepared a high-performance computing training course for you, covering CPU, GPU and supercomputing operation and maintenance. Among them, the ape code - high performance computing from novice to master series courses (parallel optimization of CPU and GPU) is especially recommended
This is a high-performance computing special course jointly developed by experts from top domestic scientific research institutes and engineers from well-known enterprises. Wei et al. You will have the opportunity to learn what you have learned through engineering practical projects, and cooperate and learn closely with top domestic experts and engineers.