A GPU’s architecture is designed for massive parallelism, featuring thousands of lightweight cores that execute simple instructions across vast data elements simultaneously—ideal for tasks like AI training. In contrast, a CPU has fewer, complex cores optimized for sequential execution and branching logic. GPUs don’t function as PCIe controllers (a hardware role), nor are they single-core designs, making the parallel execution focus the key differentiator.
(Reference: NVIDIA GPU Architecture Whitepaper, Section on GPU Design Principles)
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