👉 Competing computing refers to the practice of utilizing multiple, diverse computing resources, such as CPUs, GPUs, FPGAs, and specialized hardware like TPUs or ASICs, in parallel or sequentially to solve complex computational problems more efficiently than a single resource could. This approach leverages the unique strengths of each type of hardware to optimize performance, reduce latency, and enhance energy efficiency. For instance, GPUs excel at parallel processing tasks like graphics rendering or machine learning, while CPUs are better suited for sequential tasks and complex logic. By distributing workloads across these varied resources, competing computing aims to tackle problems that are too large or complex for traditional computing architectures, making it particularly valuable in fields like artificial intelligence, scientific simulations, and big data analytics.
