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finding:linda-applications-show-good-speedup-through-64-nodes-on-shared-memory-and-distributed-memory-multicomputers

Linda applications show good speedup through 64 nodes on shared-memory and distributed-memory multicomputers.

Empirical evidence of Linda's practical viability across diverse hardware platforms.

Source paper

extracted_from

Linda in context

(1989) · Carrier, Nicholas · Gelernter, David

Neighborhood — ranked by edge-count

Claims (2)

claim

Linda is a simpler, more powerful and more elegant model than any of these four alternatives (message-passing, concurrent objects, logic languages, functional).
supports
The central thesis of the paper, stated explicitly in the introduction.
Linda achieves scalable performance on distributed-memory machines.
supports
Supported by reported speedup through 64 nodes on iPSC/2.

Communities (3)

community

Design principles for care-centered systems
members_of
Cross-scale frameworks linking spatial patterns, diagrams, and simplicity as expressions of care in design.
Linda and coordination-oriented programming systems
members_of
Tuple space coordination languages (Linda, Parlog) enabling scalable parallel systems with composable specifications, circa 1980s–90s multicomputer platforms.
Linda parallel programming model
members_of
Tuple-space coordination language showing scalable speedup on shared/distributed memory multicomputers

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

Linda applications show good speedup through 64 nodes on Encore Multimax and Sequent Balance.finding0.898
Linda runs on shared-memory (Encore Multimax, Sequent Balance/Symmetry, Alliant FX/8), distributed-memory (Intel iPSC/2, S/Net), and LAN (Vax/VMS) environments.finding0.840
Lists the concrete systems on which Linda had been implemented.
Linda is portable across a wide range of parallel machines.claim0.806
Claim supported by the list of implemented platforms.
Linda can express fine-grained wavefront computations cleanly; future implementations on next-generation machines can support them efficiently.hypothesis0.793
The Linda model doesn't care how the multiple execution threads in a Linda program compute what they compute; it deals only with how these execution threads are created and organized into a coherent program.concept0.780
Foundational principle: Linda's orthogonality to base language and computation model is its core strength.
Linda is a more practical and a more elegant alternative to concurrent logic programming.claim0.775
Overall comparison conclusion against concurrent logic.
In Linda, no separate merge process is needed for multiple client streams.claim0.758
Linda's tuple space allows many-to-one communication without an extra merger.
The Linda code is insensitive to the number of clients, whereas Parlog requires a merge process that depends on the count.claim0.756
Demonstrates flexibility advantage.