How would you envision that working at the hardware level? GPUs are massively parallel devises, they need to keep the scheduler and ALU logic as simple and compact as possible. SIMD is a natural way to implement this. In real world, SIMT is just SIMD with some additional capabilities for control flow and a programming model that focuses on SIMD lanes as threads of execution.
What’s interesting is that modern SIMT is exposing quite a lot of its SIMD underpinnings, because that allows you to implement things much more efficiently. A hardware-accelerated SIMD sum is way faster than adding values in shared memory.
What’s interesting is that modern SIMT is exposing quite a lot of its SIMD underpinnings, because that allows you to implement things much more efficiently. A hardware-accelerated SIMD sum is way faster than adding values in shared memory.