👉 Mixed computing, also known as heterogeneous computing or multi-model computing, refers to the integration of different types of computing resources and processing models within a single system or environment to optimize performance, efficiency, and functionality. This approach combines various computing paradigms such as CPUs, GPUs, FPGAs, and specialized accelerators like TPUs, each designed for specific tasks, to handle diverse workloads more effectively. By leveraging the strengths of each computing model—such as GPUs for parallel processing, CPUs for general-purpose tasks, and FPGAs for customizable, high-performance operations—mixed computing aims to enhance computational power, reduce energy consumption, and improve overall system flexibility. This paradigm is particularly beneficial in scenarios requiring real-time processing, high-performance computing, and complex data analytics, where different tasks can be optimally distributed across multiple processing units.
