Coarse-grained Reconfigurable Arrays (CGRAs) have become prevailing to accelerate regular kernels coupled with a host processor. As the end-to-end applications are increasingly complex, it is necessary to consider mapping whole programs onto a monolithic CGRA, to avoid the bottleneck of host communication implied by Amdahl’s law.State-of-the-art studies have developed compiling methods that spatially pipeline the whole program over hardware with many cores. However, these methods mainly focus on static reconfigurable dataflow architectures and fail to exploit the dynamic reconfiguration potential of dataflow architectures, resulting in suboptimal performance and underutilization of hardware resources. Nevertheless, it is nontrivial to generate a performant mapping on dynamic reconfigurable dataflow architectures since instruction-level deadlocks are introduced. To address this challenge, this paper proposes EDWAC, a whole-program compiler that generates high-quality configurations for dynamic reconfigurable dataflow architectures. EDWAC resolves the deadlock problem by a two-stage deadlock-prevention mechanism, which comprises a shared-resource-constrained Place and Route (PnR) stage, and a Finite State Machine(FSM)-based resource reallocation stage. Together with a gated control flow Intermediate Representation (IR) design and throughput-oriented optimization methods, EDWAC achieves exceptional resource utilization and PnR feasibility.

Coarse-grained reconfigurable architecture (CGRA) is a promising programmable hardware with high power-efficiency and high performance. However, compiling and optimizing loops with irregular branches on CGRAs is a challenge to fulfill the performance potential. Existing predication techniques, such as partial predication (PP) and full predication (FP), conservatively implement software pipeline with a static initiation interval (II) obtained from the maximum graph, and thus only parts of the graph in each loop iteration will be actually executed, resulting in underexploited performance. To exploit more loop-level parallelism for irregular branches, this article proposes a novel dynamic-II pipeline (DIP) scheme, which realizes a pipeline with variable II by accommodating multiple iterations of short path in one static configuration. Since the DIP scheme is effective to only certain types of branches, this article designs a hybrid compilation framework integrating other complementary methods, which selects the appropriate method for source programs according to a proposed performance evaluation model. Experimental results show that: 1) the hybrid compilation framework can effectively extract branch features, correctly choose and implement corresponding branch processing methods within acceptable compile time and 2) as compared to PP and FP, DIP brings a significant total execution time (TET) reduction by 27.21% and 22.04% on average when the execution probability of a short branch is 50%.