What is HPC? High-Performance Computing (HPC) refers to the practice of aggregating computing power in a way that delivers much greater power than traditional computers and servers. HPC, or supercomputing, is like everyday computing, only more powerful. It is a way of processing large volumes of data at very high speeds using multiple computers and storage devices as a cohesive structure. HPC makes it possible to explore and find answers to some of the world's biggest problems in science, engineering, and business. An interesting example: Imagine that Volkswagen wants to test the resistance of a new car model before launching it on the market. Instead of spending enormous resources building and physically testing multiple prototypes of the car, they can use high-performance computing to perform detailed simulations. Volkswagen has a large data center with high-performance computers to run detailed simulations of the car's behavior in a variety of scenarios. Each simulation is like a virtual test, where different aspects of the vehicle are digitally evaluated. For example, engineers can simulate how the car behaves in different road conditions, such as sharp curves, wet roads, or even extreme collision situations without needing to test this in a physical car. HPC and the Future of the Technology Market With the advent of the massive use of artificial intelligence at a business and personal level, HPC has become indispensable, and I believe that the trend will be to have these technologies increasingly integrated into our daily lives. HPC plays a fundamental role in the construction of large models used in the area of artificial intelligence. AI algorithms, such as deep neural networks and machine learning algorithms, often require enormous amounts of computing power to train and run complex models on large data sets. In this sense, HPC provides the processing power necessary to handle these computationally intensive tasks efficiently. In the HPC area, we can see an interesting view of where the personal hardware market is heading: In HPC, accelerators such as GPUs and FPGAs are widely used to increase computational performance. These accelerators are becoming more common in personal devices, especially in smartphones and laptops to handle demanding graphics tasks, games, and AI applications. In the future, we can expect wider integration of specialized accelerators into hardware for personal use. Where to Start? Well, despite being a completely new area for some, it's not that complicated. In fact, there are few materials available in our language on the subject, but there are two with subtitles that provide a fairly good introduction to this world, and I will leave them in the reference links below! The important thing is to understand that despite being something we are not used to in our daily lives, it is still a computer. Some technologies are more present in this area such as C, C++, Python, and R. And some libraries and APIs such as CUDA, OPenMP, and others. The way of writing code is a little different, but it is still code. A great way to start is by looking at languages that offer options for parallelism. Free HPC Courses Introduction to parallel and high-performance computing Complete HPC Course - EN What is HPC? High-Performance Computing (HPC) refers to the practice of aggregating computing power in a way that delivers much greater power than traditional computers and servers. HPC, or supercomputing, is like everyday computing, only more powerful. It is a way of processing large volumes of data at very high speeds using multiple computers and storage devices as a cohesive structure. HPC makes it possible to explore and find answers to some of the world's biggest problems in science, engineering, and business. An interesting example: Imagine that Volkswagen wants to test the resistance of a new car model before launching it on the market. Instead of spending enormous resources building and physically testing multiple prototypes of the car, they can use high-performance computing to perform detailed simulations. An interesting example: Imagine that Volkswagen wants to test the resistance of a new car model before launching it on the market. Instead of spending enormous resources building and physically testing multiple prototypes of the car, they can use high-performance computing to perform detailed simulations. Volkswagen has a large data center with high-performance computers to run detailed simulations of the car's behavior in a variety of scenarios. Each simulation is like a virtual test, where different aspects of the vehicle are digitally evaluated. For example, engineers can simulate how the car behaves in different road conditions, such as sharp curves, wet roads, or even extreme collision situations without needing to test this in a physical car. Volkswagen has a large data center with high-performance computers to run detailed simulations of the car's behavior in a variety of scenarios. Each simulation is like a virtual test, where different aspects of the vehicle are digitally evaluated. For example, engineers can simulate how the car behaves in different road conditions, such as sharp curves, wet roads, or even extreme collision situations without needing to test this in a physical car. HPC and the Future of the Technology Market With the advent of the massive use of artificial intelligence at a business and personal level, HPC has become indispensable, and I believe that the trend will be to have these technologies increasingly integrated into our daily lives. HPC plays a fundamental role in the construction of large models used in the area of artificial intelligence. AI algorithms, such as deep neural networks and machine learning algorithms, often require enormous amounts of computing power to train and run complex models on large data sets. In this sense, HPC provides the processing power necessary to handle these computationally intensive tasks efficiently. In the HPC area, we can see an interesting view of where the personal hardware market is heading: In HPC, accelerators such as GPUs and FPGAs are widely used to increase computational performance. These accelerators are becoming more common in personal devices, especially in smartphones and laptops to handle demanding graphics tasks, games, and AI applications. In the future, we can expect wider integration of specialized accelerators into hardware for personal use. Where to Start? Well, despite being a completely new area for some, it's not that complicated. In fact, there are few materials available in our language on the subject, but there are two with subtitles that provide a fairly good introduction to this world, and I will leave them in the reference links below! The important thing is to understand that despite being something we are not used to in our daily lives, it is still a computer. Some technologies are more present in this area such as C, C++, Python, and R. And some libraries and APIs such as CUDA, OPenMP, and others. The way of writing code is a little different, but it is still code. A great way to start is by looking at languages that offer options for parallelism. Free HPC Courses Introduction to parallel and high-performance computing Complete HPC Course - EN Introduction to parallel and high-performance computing Introduction to parallel and high-performance computing Complete HPC Course - EN Complete HPC Course - EN
