Enroll Course: https://www.udemy.com/course/learn-to-use-hpc-systems-and-supercomputers/
In today’s data-driven world, the ability to process vast amounts of information quickly and efficiently is paramount. Whether you’re delving into machine learning, big data analytics, or complex scientific simulations, High Performance Computing (HPC) systems and supercomputers are the engines that drive progress. If you’ve ever felt the need for more computing power or wanted to understand how these massive systems work, Udemy’s ‘Scientific Computing Masterclass: Parallel and Distributed’ is a course you absolutely need to explore.
This comprehensive course, the first of its kind on Udemy for HPC, serves as an excellent introduction to the world of parallel and distributed computing. It’s designed to equip you with the knowledge and skills to leverage HPC systems and supercomputers to tackle complex problems, significantly accelerating your research and development.
**What You’ll Learn:**
The syllabus is impressively thorough, covering everything from the foundational history of supercomputing to the intricate details of HPC cluster architecture. You’ll gain a deep understanding of:
* **HPC Fundamentals:** Differentiating between supercomputers and HPC clusters, understanding the components of an HPC cluster (login nodes, compute nodes, storage nodes, networks), and the benefits of cluster computing.
* **Job Schedulers:** In-depth introductions to PBS (including commands like `qsub`, `qstat`, `qdel`, `qalter`, job states, variables, and array jobs) and Slurm (covering basic commands, distributed MPI and GPU jobs, multi-threaded OpenMP jobs, and job dependencies).
* **Parallel Programming:** A solid grounding in OpenMP (clauses, worksharing, parallel loops, vector addition) and MPI (hello world, send/receive, ping-pong).
* **GPU Computing:** A beginner-friendly guide to GPUs and CUDA programming, including a well-explained ‘hello world’ example and clear lessons on CUDA memory models. The course also features a new section on AMD GPU programming with ROCm and HIP, making it current with the latest hardware advancements.
* **Cloud HPC:** Practical insights into leveraging AWS for HPC, including building and running codes on AWS HPC clusters.
**Course Delivery and Support:**
What truly sets this course apart is its commitment to student success. The instructor provides a university semester’s worth of knowledge in a single, accessible video format. Beyond the core content, students gain free access to an interactive version of the course on the Scientific Programming School platform, complete with code playgrounds. Furthermore, a live Zoom lecture series covers key aspects of parallel and distributed computing, offering real-time interaction and clarification.
The course also fosters a strong community through a Q&A live community, allowing students to get help from peers and the instructor. This holistic approach ensures that even complex topics are made digestible and approachable.
**Recommendation:**
The ‘Scientific Computing Masterclass: Parallel and Distributed’ is an invaluable resource for anyone looking to enhance their computational capabilities. Its comprehensive coverage, practical examples, and exceptional student support make it a highly recommended course for students, researchers, data scientists, and engineers working or aspiring to work in fields that demand high-performance computing. If you’re ready to supercharge your problem-solving skills, this course is your gateway.
Enroll Course: https://www.udemy.com/course/learn-to-use-hpc-systems-and-supercomputers/