Zhengyao Lin | Searcharxiv

arXiv2026

Let it Flow: A Formally Verified Compilation Framework for Asynchronous Dataflow

Dataflow architectures have gained renewed interest due to their balance between power efficiency and performance. In (spatial) dataflow architectures, a program is represented as a set of entirely distributed and dynamically scheduled dataflow operators that communicate through asynchronous channels, which greatly improves data locality and parallelism. However, compiling to dataflow architectures remains an error-prone process, in order to maintain determinacy while enabling pipelining. Determinacy means that the result of a dataflow program is deterministic and independent of the schedule of operator execution, and pipelining is an important optimization in spatial dataflow that enables parallelism across loop iterations. In this work, we present Wavelet, the first effort to formally verify a compiler for asynchronous dataflow. We use a mix of techniques to achieve this goal. Our frontend uses a novel capability type system with fences to synchronize conflicting memory accesses and enable pipelining. We then verify a Lean formalization of two core passes of our compiler that translates elaborated programs from the type checker to dataflow graphs, proving important properties of forward simulation and determinacy. Notably, our formalization semantically propagates the soundness guarantees of the frontend type system, ensuring modularity between simulation and determinacy proofs. In evaluation, we show that dataflow graphs compiled by Wavelet have comparable sizes to those produced by an unverified optimizing compiler for the RipTide spatial dataflow architecture.

cs.PL↗

arXiv2023

WaveCert: Translation Validation for Asynchronous Dataflow Programs via Dynamic Fractional Permissions

Coarse-grained reconfigurable arrays (CGRAs) have gained attention in recent years due to their promising power efficiency compared to traditional von Neumann architectures. To program these architectures using ordinary languages such as C, a dataflow compiler must transform the original sequential, imperative program into an equivalent dataflow graph, composed of dataflow operators running in parallel. This transformation is challenging since the asynchronous nature of dataflow graphs allows out-of-order execution of operators, leading to behaviors not present in the original imperative programs. We address this challenge by developing a translation validation technique for dataflow compilers to ensure that the dataflow program has the same behavior as the original imperative program on all possible inputs and schedules of execution. We apply this method to a state-of-the-art dataflow compiler targeting the RipTide CGRA architecture. Our tool uncovers 8 compiler bugs where the compiler outputs incorrect dataflow graphs, including a data race that is otherwise hard to discover via testing. After repairing these bugs, our tool verifies the correct compilation of all programs in the RipTide benchmark suite.

cs.PL↗