scholarly journals Repairing and mechanising the JavaScript relaxed memory model

2020 ◽  
Author(s):  
Conrad Watt ◽  
Christopher Pulte ◽  
Anton Podkopaev ◽  
Guillaume Barbier ◽  
Stephen Dolan ◽  
...  
Keyword(s):  
Memory Model ◽  
Relaxed Memory Model ◽  
Relaxed Memory

scholarly journals A Verification Framework for Assembly Programs Under Relaxed Memory Model Using SMT Solver

2018 ◽  
Vol E101.D (12) ◽  
pp. 3038-3058
Author(s):  
Pattaravut MALEEHUAN ◽  
Yuki CHIBA ◽  
Toshiaki AOKI
Keyword(s):  
Memory Model ◽  
Smt Solver ◽  
Relaxed Memory Model ◽  
Relaxed Memory

scholarly journals The leaky semicolon: compositional semantic dependencies for relaxed-memory concurrency

2022 ◽  
Vol 6 (POPL) ◽  
pp. 1-30
Author(s):  
Alan Jeffrey ◽  
James Riely ◽  
Mark Batty ◽  
Simon Cooksey ◽  
Ilya Kaysin ◽  
...  
Keyword(s):  
Improve Performance ◽  
Compositional Semantic ◽  
Sequential Composition ◽  
Predicate Transformers ◽  
Relaxed Memory Model ◽  
Semantic Dependencies ◽  
Event Based ◽  
Predicate Transformer ◽  
Prior Models ◽  
Relaxed Memory

Program logics and semantics tell a pleasant story about sequential composition: when executing (S1;S2), we first execute S1 then S2. To improve performance, however, processors execute instructions out of order, and compilers reorder programs even more dramatically. By design, single-threaded systems cannot observe these reorderings; however, multiple-threaded systems can, making the story considerably less pleasant. A formal attempt to understand the resulting mess is known as a “relaxed memory model.” Prior models either fail to address sequential composition directly, or overly restrict processors and compilers, or permit nonsense thin-air behaviors which are unobservable in practice. To support sequential composition while targeting modern hardware, we enrich the standard event-based approach with preconditions and families of predicate transformers. When calculating the meaning of (S1; S2), the predicate transformer applied to the precondition of an event e from S2 is chosen based on the set of events in S1 upon which e depends. We apply this approach to two existing memory models.

Fluency: A trigger of familiarity for relational representations?

2019 ◽  
Vol 42 ◽  
Author(s):  
Talya Sadeh
Keyword(s):  
Memory Model ◽  
Lines Of Evidence

Abstract According to Bastin et al.’s integrative memory model, familiarity may be attributed to both entity representations and relational representations. However, the model does not specify what triggers familiarity for relational representations. I argue that fluency is a key player in the attribution of familiarity regardless of the type of representation. Two lines of evidence are reviewed in support of my claim.

Synesthetic Binding and the Reactivation Model of Memory

2017 ◽  
Author(s):  
Berit Brogaard
Keyword(s):  
Sensory Neurons ◽  
Memory Retrieval ◽  
Brain Activity ◽  
Receptive Fields ◽  
Memory Model ◽  
Multisensory Perception ◽  
Feedback Mechanisms

Despite the recent surge in research on, and interest in, synesthesia, the mechanism underlying this condition is still unknown. Feedforward mechanisms involving overlapping receptive fields of sensory neurons as well as feedback mechanisms involving a lack of signal disinhibition have been proposed. Here I show that a broad range of studies of developmental synesthesia indicate that the mechanism underlying the phenomenon may in some cases involve the reinstatement of brain activity in sensory or cognitive streams in a way that is similar to what happens during memory retrieval of semantically associated items. In the chapter’s final sections I look at the relevance of synesthesia research, given the memory model, to our understanding of multisensory perception and common mapping patterns.

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