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Milijana Surbatovich

Publications and source records attributed to Milijana Surbatovich.

3 recordsLinked to original sources

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↗

Towards a Formal Foundation of Intermittent Computing

Intermittently powered devices enable new applications in harsh or inaccessible environments, such as space or in-body implants, but also introduce problems in programmability and correctness. Researchers have developed programming models to ensure that programs make progress and do not produce erroneous results due to memory inconsistencies caused by intermittent executions. As the technology has matured, more and more features are added to intermittently powered devices, such as I/O. Prior work has shown that all existing intermittent execution models have problems with repeated device or sensor inputs (RIO). RIOs could leave intermittent executions in an inconsistent state. Such problems and the proliferation of existing intermittent execution models necessitate a formal foundation for intermittent computing. In this paper, we formalize intermittent execution models, their correctness properties with respect to memory consistency and inputs, and identify the invariants needed to prove systems correct. We prove equivalence between several existing intermittent systems. To address RIO problems, we define an algorithm for identifying variables affected by RIOs that need to be restored after reboot and prove the algorithm correct. Finally, we implement the algorithm in a novel intermittent runtime system that is correct with respect to input operations and evaluate its performance.

cs.PL↗

Automatically Enforcing Fresh and Consistent Inputs in Intermittent Systems

Intermittently powered energy-harvesting devices enable new applications in inaccessible environments. Program executions must be robust to unpredictable power failures, introducing new challenges in programmability and correctness. One hard problem is that input operations have implicit constraints, embedded in the behavior of continuously powered executions, on when input values can be collected and used. This paper aims to develop a formal framework for enforcing these constraints. We identify two key properties -- freshness (i.e., uses of inputs must satisfy the same time constraints as in continuous executions) and temporal consistency (i.e., the collection of a set of inputs must satisfy the same time constraints as in continuous executions). We formalize these properties and show that they can be enforced using atomic regions. We develop Ocelot, an LLVM-based analysis and transformation tool targeting Rust, to enforce these properties automatically. Ocelot provides the programmer with annotations to express these constraints and infers atomic region placement in a program to satisfy them. We then formalize Ocelot's design and show that Ocelot generates correct programs with little performance cost or code changes.

cs.PL↗