Hardware Acceleration
Hardware acceleration is a technique that offloads specific computational tasks from a general-purpose CPU to specialized hardware components, such as GPUs, TPUs, FPGAs, or ASICs, to improve performance and efficiency. It leverages the parallel processing capabilities and optimized architectures of these dedicated units to handle tasks like graphics rendering, machine learning inference, video encoding, or cryptographic operations more effectively than software running on a CPU alone.
Developers should learn and use hardware acceleration when building applications that require high-performance computing, such as real-time graphics in games or simulations, AI/ML model training and inference, video processing, or data-intensive scientific calculations. It is essential for optimizing resource usage, reducing latency, and enabling scalable solutions in fields like computer vision, natural language processing, and high-frequency trading, where CPU-based processing would be too slow or inefficient.