Modern computing relies on different processor architectures to balance performance, efficiency, and scalability. Whether running a simple smartphone app or processing massive datasets in artificial intelligence, the way a processor handles instructions has a direct impact on speed and power consumption.
This topic explores CISC (Complex Instruction Set Computing) and RISC (Reduced Instruction Set Computing) architectures, highlighting how they execute instructions and their real-world applications. It also covers multicore processing, which allows computers to handle multiple tasks simultaneously, and parallel processing, which breaks large problems into smaller, faster computations.
GPUs (Graphics Processing Units) play a key role in parallel computing, significantly outperforming traditional CPUs for certain tasks. Originally developed for rendering graphics, GPUs are now used in AI, scientific research, and complex simulations due to their ability to execute thousands of operations at once. Understanding the strengths and limitations of different processor types is essential for anyone interested in computer science, software development, or high-performance computing.
This unit will guide you through the key concepts behind processor efficiency, task execution, and the technology that powers modern devices.