scholarly journals Session-based concurrency, declaratively

2021 ◽  
Author(s):  
Mauricio Cano ◽  
Hugo A. López ◽  
Jorge A. Pérez ◽  
Camilo Rueda
Keyword(s):  
Message Passing ◽  
Partial Information ◽  
Contextual Information ◽  
Communication Patterns ◽  
Session Types ◽  
Information Constraints ◽  
Realistic Communication ◽  
Message Passing Programs

AbstractSession-based concurrency is a type-based approach to the analysis of message-passing programs. These programs may be specified in an operational or declarative style: the former defines how interactions are properly structured; the latter defines governing conditions for correct interactions. In this paper, we study rigorous relationships between operational and declarative models of session-based concurrency. We develop a correct encoding of session $$\pi $$ π -calculus processes into the linear concurrent constraint calculus ($$\texttt {lcc}$$ lcc ), a declarative model of concurrency based on partial information (constraints). We exploit session types to ensure that our encoding satisfies precise correctness properties and that it offers a sound basis on which operational and declarative requirements can be jointly specified and reasoned about. We demonstrate the applicability of our results by using our encoding in the specification of realistic communication patterns with time and contextual information.

scholarly journals MEMPHA: Model of Exascale Message-Passing Programs on Heterogeneous Architectures

2020 ◽  
Vol 31 (11) ◽  
pp. 2570-2581
Author(s):  
Sina Zangbari Koohi ◽  
Nor Asilah Wati Abdul Hamid ◽  
Mohamed Othman ◽  
Gafurjan Ibragimov
Keyword(s):  
Message Passing ◽  
Heterogeneous Architectures ◽  
Message Passing Programs

scholarly journals Human confidence judgments reflect reliability-based hierarchical integration of contextual information

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Philipp Schustek ◽  
Alexandre Hyafil ◽  
Rubén Moreno-Bote
Keyword(s):  
Sample Size ◽  
Latent Variables ◽  
Message Passing ◽  
Contextual Information ◽  
Probabilistic Inference ◽  
Contextual Variable ◽  
Hierarchical Levels ◽  
Sensory Evidence ◽  
Sensory Uncertainty ◽  
Simple Heuristics

AbstractOur immediate observations must be supplemented with contextual information to resolve ambiguities. However, the context is often ambiguous too, and thus it should be inferred itself to guide behavior. Here, we introduce a novel hierarchical task (airplane task) in which participants should infer a higher-level, contextual variable to inform probabilistic inference about a hidden dependent variable at a lower level. By controlling the reliability of past sensory evidence through varying the sample size of the observations, we find that humans estimate the reliability of the context and combine it with current sensory uncertainty to inform their confidence reports. Behavior closely follows inference by probabilistic message passing between latent variables across hierarchical state representations. Commonly reported inferential fallacies, such as sample size insensitivity, are not present, and neither did participants appear to rely on simple heuristics. Our results reveal uncertainty-sensitive integration of information at different hierarchical levels and temporal scales.

A scalable debugger for massively parallel message-passing programs

1994 ◽  
Vol 2 (2) ◽  
pp. 50-56 ◽  
Author(s):  
S. Sistare ◽  
D. Allen ◽  
R. Bowker ◽  
K. Jourdenais ◽  
J. Simons ◽  
...  
Keyword(s):  
Message Passing ◽  
Massively Parallel ◽  
Message Passing Programs
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