[JonChesterfield]

GPUs are pretty close to an instantiation of a dataflow architecture. I have a soft spot for vliw on deterministic memory latency but the runtime scheduler + variable memory latency is probably better.

The insight is that GPUs are memory driven - warps basically wait for memory operations to complete while other warps do stuff - so execution proceeds driven by memory access patterns.

[jacquesm]

Not quite, but yes, they are converging. But GPUs are not universal enough to be called dataflow computers. But there are some similarities. But unless I'm mistaken SIMD is fundamentally different compared to dataflow in that it executes all of the instructions in lockstep across a bunch of units rather than that each execution unit can have its own stream of opcodes. So GPUs have great performance but require that tasks be more inherently parallel than what you could (theoretically, mostly) do with a true dataflow computer.