concept
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concept:distributed-data-structuresdistributed data structures
Data structures stored as collections of tuples in tuple space, accessible to many processes.
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Papers (1)
paper
- Linda in contextcites
Concepts (3)
concept
- data structuresrelated_toConventional programming constructs like variables, arrays; claimed unnecessary for Elephant programs.
- Tuple SpaceextendsA region where processes deposit and retrieve persistent tuples; central to Linda's asynchronous coordination model.
- Live Data Structuresassociated_withA structuring technique where each element of a result is computed by a separate process that turns into a data element; enables fine-grained parallelism.
Artifacts (1)
artifact
- Linda in Context (1989)introducesThe source article that introduces and argues for the Linda parallel programming model, comparing it to message-passing, concurrent objects, logic programming, and functional programming.
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Implementation technique used in Linda ports for distributed-memory machines like the Intel hypercube.
- Idea that information is spread across many neurons; superposition is a subtype.
- Key notion where alignment map ϕ maps neurons block-wise to latent variables before constructive abstraction
- The large-scale organizational pattern of a system whose preservation defines wholeness-preserving transformations
- The actual computational operations a model performs, which the paper argues need not mirror representational structure
- Training data with inherent geometric or relational structure, which induces geometric organization in model internals.
- The core method introduced in this paper: finds alignments between high-level causal variables and distributed neural representations via gradient descent.