Why GPUs are Ideal for Deep Learning

The third reason is not that important performance-wise, but it does offer an additional insight into GPUs' undeniable supremacy over CPUs. The first part of the process involves fetching memory from the main or RAM memory and transferring it over to on-chip memory, or the L1 cache (instruction memory) and registers. Registers are attached directly to the execution unit, which for GPUs is the stream processor and for CPUs the core. This is where all the computation happens. Normally, you'd want both L1 and register memory to be as close to the execution engine and allow for a quick access by keeping the memories small.