You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
Trying to cope with the constantly growing number of cores per processor, hardware architects are experimenting with modular non-cache-coherent architectures. Such architectures delegate the memory coherency to the software. On the contrary, high productivity languages, like Java, are designed to abstract away the hardware details and allow developers to focus on the implementation of their algorithm. Such programming languages rely on a process virtual machine to perform the necessary operations to implement the corresponding memory model. Arguing about the correctness of such implementations is not trivial though. In this work we present our implementation of the Java Memory Model in a Java Virtual Machine targeting a 512-core non-cache-coherent memory architecture. We shortly discuss design decisions and present early evaluation results, which demonstrate that our implementation scales with the number of cores. We model our implementation as the operational semantics of a Java Core Calculus that we extend with synchronization actions, and prove its adherence to the Java Memory Model.

Cited Abstract(s):
[1]: The specification of the Java Memory Model (jmm) is phrased in terms of acceptors of execution sequences rather than the standard generative view of operational semantics. This creates a mismatch with language-based techniques, such as simulation arguments and proofs of type safety. We describe a semantics for the jmm using standard programming language techniques that captures its full expressivity. For data-race-free programs, our model coincides with the jmm. For lockless programs, our model is more expressive than the jmm. The stratification properties required to avoid causality cycles are derived, rather than mandated in the style of the jmm. The jmm is arguably non-canonical in its treatment of the interaction of data races and locks as it fails to validate roach-motel reorderings and various peephole optimizations. Our model differs from the jmm in these cases. We develop a theory of simulation and use it to validate the legality of the above optimizations in any program context.

[2]: A semantics to a small fragment of Java capturing the new memory model (JMM) described in the Language Specification is given by combining operational, denotational and axiomatic techniques in a novel semantic framework. The operational steps (specified in the form of SOS) construct denotational models (configuration structures) and are constrained by the axioms of a configuration theory. The semantics is proven correct with respect to the Language Specification and shown to capture many common examples in the JMM literature.
We thus consider our approach to be closer to the implementation. Cenciarelli [2] use a combination of operational, denotational, and axiomatic semantics to define the JMM @. In that work, the authors show that all the generated executions adhere to the JMM, but as in [1] they do not account for the memory hierarchy.