👉 Temp computing, or in-memory computing, is a computational paradigm that aims to reduce the latency and energy consumption associated with data movement in traditional computing architectures. Instead of transferring data between the CPU and memory, which can be a bottleneck, temp computing stores data directly in the memory where the computation occurs. This approach leverages high-speed memory technologies, such as RAM or specialized memory like HBM (High Bandwidth Memory), to perform computations on data residing in the same location, significantly speeding up processing times and reducing power usage. This is particularly beneficial for applications involving large datasets, such as machine learning, scientific simulations, and real-time analytics, where minimizing data transfer overhead is crucial for performance.
