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Spatial architecture is a high-performance architecture that uses controlflow graphs and data flow graphs as the computational model andproducer/consumer models as the execution models. However, existing spatialarchitectures suffer from control flow handling challenges. Upon categorizingtheir PE execution models, we find that they lack autonomous, peer-to-peer, andtemporally loosely-coupled control flow handling capability. This leads tolimited performance in intensive control programs.  A spatial architecture, Marionette, is proposed, with an explicit-designedcontrol flow plane. The Control Flow Plane enables autonomous, peer-to-peer andtemporally loosely-coupled control flow handling. The Proactive PEConfiguration ensures timely and computation-overlapped configuration toimprove handling Branch Divergence. The Agile PE Assignment enhance thepipeline performance of Imperfect Loops. We develop full stack of Marionette(ISA, compiler, simulator, RTL) and demonstrate that in a variety ofchallenging intensive control programs, compared to state-of-the-art spatialarchitectures, Marionette outperforms Softbrain, TIA, REVEL, and RipTide bygeomean 2.88x, 3.38x, 1.55x, and 2.66x.

Towards Efficient Control Flow Handling in Spatial Architecture via Architecting the Control Flow Plane