{ "model": { "rank": 6881, "code": "thing-q232661", "model_id": "vr.tr.parallel-computing", "name": "parallel computing", "purpose": "Enable an agent to recognise parallel computation, assess its correctness and performance, and choose justified ways to partition, coordinate and execute computational work.", "family": "Thing Registry", "category": "Activities and processes", "status": "research-draft", "kind": "thing", "plane": "ACT", "domain": "ACT.ACT", "industry": "", "version": "", "url": "/models/thing/q232661/", "tier": 2, "score": 58, "payload": { "layer": "wikidata", "aliases": [ "multicomputer", "embarrassingly parallel", "hardware multithreading", "MIMD", "MISD", "automatic vectorization", "SIMT", "uniform memory access", "MPMD", "SPMD", "Instruction level parallelism", "loop-level parallelism", "data parallelism", "link aggregation", "data-intensive computing", "loop scheduling", "task parallelism", "process-oriented programming", "multiprocessing", "speculative multithreading", "temporal multithreading", "simultaneous multithreading", "multiprocessor system" ], "aliasCount": 23, "merged": 23, "knownIn": 58, "facets": null, "markers": [], "lexicalClass": "", "senseRank": null, "alsoRegisteredAs": null, "source": { "dataset": "wikidata", "item": "Q232661", "url": "https://www.wikidata.org/wiki/Q232661", "license": "CC0 1.0" } }, "research": { "vercy": "1.0-draft", "publication": { "status": "research-draft", "adjudicationStatus": "unreviewed", "publishableCanonical": false, "generatedAt": "2026-09-09T23:42:10Z", "providers": [ "Codex" ], "breadth": "recalled by Codex without web access - no source was read", "missingProviders": [], "pass": 2, "cost": { "grok": { "seconds": 20.7, "error": "Reading additional input from stdin...\nOpenAI Codex v0.153.4\n--------\nworkdir: R:\\02_PROJECTS\\02_Meta_Models_Platforms\\Ver.cy\\current\\thing-registry-backlog\nmodel: gpt-6-astra\nprovider: openai\napproval: never\nsandbox: read-only\nreasoning effort: none\nreasoning summaries: none\nsession id: 01a0888b-e7d8-7d30-9bd9-f247049ec86b\n--------\nuser\nDescribe what is already known about one registered thing. Answer as JSON only, no prose around it.\n\nThing: parallel computing\nSense to describe: (none recorded)\nDomain code: ACT.ACT\nAlso known as: (none)\n\n\nContext for this batch of 1001 things:\n# Batch 007: 1", "usd": 0, "recall": true }, "codex": { "seconds": 65.4, "error": "Reading additional input from stdin...\nOpenAI Codex v0.153.4\n--------\nworkdir: R:\\02_PROJECTS\\02_Meta_Models_Platforms\\Ver.cy\\current\\thing-registry-backlog\nmodel: gpt-6-astra\nprovider: openai\napproval: never\nsandbox: read-only\nreasoning effort: none\nreasoning summaries: none\nsession id: 01a0888b-e7d0-7f63-a3f6-798f0a11ca90\n--------\nuser\nYou are drafting a Vercy meta-model for one registered thing. Answer as JSON only, no prose around it.\n\nThing: parallel computing\nRegistry id: vr.tr.parallel-computing\nPlane / domain: ACT / ACT.ACT\nRegistry definition: (none recorded)\nNames folded into this en" } } }, "metaModel": { "id": "THING-Q232661", "registryId": "vr.tr.parallel-computing", "name": "parallel computing", "version": "0.1.0-research.1", "entryKind": "thing", "family": "Thing Registry", "domain": [ "ACT.ACT" ], "status": "research-draft" }, "canonicalUrl": "https://ver.cy/models/thing/q232661/", "model": { "registry_id": "vr.tr.parallel-computing", "name": "parallel computing", "purpose": "Enable an agent to recognise parallel computation, assess its correctness and performance, and choose justified ways to partition, coordinate and execute computational work.", "definition": "Parallel computing is the execution of multiple parts of a computation simultaneously on multiple processing elements, with decomposition and coordination arranged to preserve the computation's intended result.", "scope_statement": "This model owns parallel computing as the organisation of computational work for simultaneous execution across multiple processing resources, including the relationships among decomposition, dependencies, execution, correctness and scaling.", "in_scope": [ "Operational boundaries between parallelism, concurrency, distribution and vectorisation", "Decomposition of computations into tasks or data partitions with explicit dependencies", "Mapping work and data onto processing resources", "Communication, synchronisation and correctness under parallel execution", "Measurement of speedup, efficiency, scaling and resource costs" ], "out_of_scope": [ "Processor and accelerator hardware design, owned by computer architecture models", "General network infrastructure and protocols, owned by networking models", "Distributed service governance, replication and availability beyond their role in a parallel computation", "Application-domain meaning and scientific validity of the computation's inputs and outputs", "Programming-language and runtime specifications except where they constrain parallel execution" ], "distinguishing_features": [ "For a realised execution, identify computation occurring simultaneously on distinct processing resources; interleaving tasks on one execution resource establishes concurrency but does not by itself establish parallel execution.", "Identify how simultaneous work contributes to a defined computational objective; independently operating computers do not alone establish a parallel computation.", "Separate a program's available parallelism from the parallelism realised in a particular run; a parallel-capable program can execute serially.", "Do not require separate machines: multiple cores, accelerators or execution lanes within one machine can provide parallel execution.", "Do not require speedup: coordination overhead or imbalance can make a parallel execution slower than its serial baseline." ], "characteristics": [ { "name": "Parallelism form", "kind": "category", "unit_or_values": "Task, data, pipeline, vector or instruction-level; multiple values permitted", "why_it_matters": "Identifies which work can overlap and what decomposition or execution mechanisms are relevant." }, { "name": "Dependency structure", "kind": "relation", "unit_or_values": "Ordering and data-dependency relations among work units, with cycles or iteration boundaries identified", "why_it_matters": "Constrains legal schedules and exposes work that must remain ordered." }, { "name": "Work and critical-path span", "kind": "measurement", "unit_or_values": "Operations or time under a stated execution-cost model", "why_it_matters": "Distinguishes total computational work from the dependency chain limiting achievable parallelism." }, { "name": "Processing-resource allocation", "kind": "measurement", "unit_or_values": "Counts by resource type, such as nodes, cores, hardware threads, accelerators and lanes", "why_it_matters": "Makes allocation explicit without treating heterogeneous resources as interchangeable." }, { "name": "Memory and communication organisation", "kind": "category", "unit_or_values": "Shared memory, distributed memory or hybrid; communication mechanisms recorded separately", "why_it_matters": "Determines data accessibility, movement requirements and coordination choices." }, { "name": "Work-unit granularity", "kind": "measurement", "unit_or_values": "Operations, elements or execution time per task or partition, including distribution", "why_it_matters": "Helps assess whether useful work outweighs scheduling and communication overhead." }, { "name": "Correctness assessment", "kind": "state", "unit_or_values": "Unassessed, supported within stated evidence scope, or violated; equivalence criterion attached", "why_it_matters": "Prevents performance gains from being accepted when ordering, numerical or output requirements fail." }, { "name": "Speedup and parallel efficiency", "kind": "measurement", "unit_or_values": "Speedup T_baseline/T_parallel; efficiency speedup/p where a comparable resource count p is meaningful", "why_it_matters": "Relates elapsed-time gains to resource use while requiring an explicit baseline and allocation." }, { "name": "Scaling regime", "kind": "category", "unit_or_values": "Strong scaling, weak scaling or another explicitly defined workload-resource relationship", "why_it_matters": "Prevents comparisons between measurements that change problem size differently." }, { "name": "Load imbalance", "kind": "measurement", "unit_or_values": "Distribution of useful work time and waiting time across workers; summary formula stated", "why_it_matters": "Shows whether completion is dominated by uneven assignment, resource differences or delayed workers." } ], "affordances": [ "Identify independent work and propose a decomposition that preserves required dependencies.", "Select a resource mapping and data placement appropriate to the workload and execution environment.", "Choose communication and synchronisation mechanisms consistent with the correctness contract.", "Compare parallel executions against a declared baseline under a reproducible measurement protocol.", "Diagnose limits caused by serial dependencies, imbalance, data movement or coordination overhead.", "Adjust granularity, scheduling or resource allocation and evaluate whether the change improves the declared objective." ] }, "sources": [], "structure": { "bundles": [ { "id": "parallelism-boundaries", "name": "Parallelism boundaries", "description": "Establishes what is being called parallel and the level at which that claim applies.", "rationale": "An agent must distinguish available parallel work from actual simultaneous execution and avoid equating parallelism with distribution or speedup.", "layers": [ { "id": "instance-and-observation", "name": "Instance and observation", "description": "Locates the claim in an algorithm, program, runtime configuration or observed execution.", "findings": [ { "id": "claimed-and-realised-parallelism", "name": "Claimed and realised parallelism", "description": "Record whether parallelism is a capability or an observed property, together with the processing resources and observation interval.", "questions": [ { "text": "Does this instance denote a parallel algorithm, a parallel-capable implementation or a particular execution?", "kind": "definition", "id": "claimed-and-realised-parallelism-q01" }, { "text": "What trace or measurement demonstrates simultaneous computation, and at what resource and time resolution?", "kind": "measurement", "id": "claimed-and-realised-parallelism-q02" } ] } ] }, { "id": "forms-and-neighbours", "name": "Forms and neighbours", "description": "Identifies the forms of parallelism and their overlap with neighbouring concepts.", "findings": [ { "id": "parallelism-classification", "name": "Parallelism classification", "description": "Record the relevant task, data, pipeline or lower-level parallelism without treating these categories as mutually exclusive.", "questions": [ { "text": "Which work overlaps: different tasks, partitions of the same operation, pipeline stages or execution lanes?", "kind": "definition", "id": "parallelism-classification-q01" }, { "text": "What makes this claim about parallel computing rather than only concurrency, distributed deployment or independent computer use?", "kind": "boundary", "id": "parallelism-classification-q02" } ] } ] } ] }, { "id": "work-decomposition-and-dependencies", "name": "Work decomposition and dependencies", "description": "Represents the independent work, required ordering and partition boundaries of a computation.", "rationale": "Useful parallel execution depends on exposing enough independent work while preserving dependencies and controlling partition costs.", "layers": [ { "id": "dependency-limits", "name": "Dependency limits", "description": "Identifies ordering constraints and the chains that limit simultaneous progress.", "findings": [ { "id": "work-and-span-account", "name": "Work and span account", "description": "Record work units, dependency relations, total work and critical-path span under an explicit cost model.", "questions": [ { "text": "Which dependencies arise from the computation itself, and which are introduced by the implementation?", "kind": "boundary", "id": "work-and-span-account-q01" }, { "text": "What are total work and critical-path span for the stated input, and how were their costs estimated?", "kind": "measurement", "id": "work-and-span-account-q02" } ] } ] }, { "id": "partition-and-granularity", "name": "Partition and granularity", "description": "Describes how tasks and data are divided and how much useful work each division contains.", "findings": [ { "id": "partition-quality", "name": "Partition quality", "description": "Record partition sizes, boundary exchanges, duplicated work and variability in task cost.", "questions": [ { "text": "How are tasks or data partitioned, and what communication or redundant computation does each boundary introduce?", "kind": "definition", "id": "partition-quality-q01" }, { "text": "Which granularity changes could reduce overhead without eliminating enough parallel work to leave resources idle?", "kind": "action", "id": "partition-quality-q02" } ] } ] } ] }, { "id": "resource-mapping-and-data-movement", "name": "Resource mapping and data movement", "description": "Connects computational work to execution resources, scheduling and data location.", "rationale": "The same decomposition can behave differently depending on placement, resource heterogeneity, memory locality and transfer costs.", "layers": [ { "id": "placement-and-scheduling", "name": "Placement and scheduling", "description": "Records where work runs and how ready work is assigned over time.", "findings": [ { "id": "worker-assignment", "name": "Worker assignment", "description": "Record worker-to-resource mapping, scheduling policy, oversubscription and constraints on task migration.", "questions": [ { "text": "How do software workers map to physical execution resources, including accelerators and shared resources?", "kind": "definition", "id": "worker-assignment-q01" }, { "text": "Would static assignment, dynamic scheduling or work stealing better address the observed task-cost variation and locality constraints?", "kind": "action", "id": "worker-assignment-q02" } ] } ] }, { "id": "locality-and-transfers", "name": "Locality and transfers", "description": "Tracks the data access and movement required for workers to progress.", "findings": [ { "id": "data-movement-account", "name": "Data movement account", "description": "Record data ownership or sharing, placement, transfer volume and contention affecting execution.", "questions": [ { "text": "Which data accesses are local, shared-memory remote, device transfers or inter-node messages?", "kind": "definition", "id": "data-movement-account-q01" }, { "text": "How much elapsed time and traffic are attributable to data movement, and what evidence identifies bandwidth or latency limits?", "kind": "measurement", "id": "data-movement-account-q02" } ] } ] } ] }, { "id": "coordination-and-correctness", "name": "Coordination and correctness", "description": "Defines acceptable results and the coordination needed to obtain them across parallel executions.", "rationale": "Parallel schedules can change visibility, ordering and numerical results; an agent needs a correctness contract before modifying execution.", "layers": [ { "id": "ordering-and-progress", "name": "Ordering and progress", "description": "Captures communication protocols, synchronisation and assumptions about memory visibility and progress.", "findings": [ { "id": "coordination-contract", "name": "Coordination contract", "description": "Record ownership rules, required ordering, coordination mechanisms and the runtime guarantees they depend on.", "questions": [ { "text": "Which locks, atomics, barriers, message exchanges or ownership rules enforce required ordering and visibility?", "kind": "definition", "id": "coordination-contract-q01" }, { "text": "Which runtime or memory-model guarantees support those mechanisms, and where are those guarantees documented?", "kind": "provenance", "id": "coordination-contract-q02" }, { "text": "What evidence addresses races, deadlock, starvation and mismatched collective operations where applicable?", "kind": "measurement", "id": "coordination-contract-q03" } ] } ] }, { "id": "result-equivalence", "name": "Result equivalence", "description": "Establishes how outputs from different schedules and resource allocations are judged.", "findings": [ { "id": "acceptable-output-variation", "name": "Acceptable output variation", "description": "Record whether correctness requires exact equality, numerical tolerance or another application-defined relation.", "questions": [ { "text": "Must parallel results match a reference bit for bit, within a numerical tolerance or through another explicit equivalence criterion?", "kind": "definition", "id": "acceptable-output-variation-q01" }, { "text": "How will schedule-dependent reductions, random-number generation and resource-count changes be checked against that criterion?", "kind": "action", "id": "acceptable-output-variation-q02" } ] } ] } ] }, { "id": "performance-and-scaling-decisions", "name": "Performance and scaling decisions", "description": "Supports reproducible performance assessment and justified changes to parallel execution.", "rationale": "Resource count alone does not establish benefit; decisions require comparable baselines, a declared objective and evidence about limiting costs.", "layers": [ { "id": "measurement-contract", "name": "Measurement contract", "description": "Defines the workload, baseline and timing boundaries used in performance claims.", "findings": [ { "id": "comparable-performance-evidence", "name": "Comparable performance evidence", "description": "Record input, implementation, resource allocation, timing inclusions, repeated-run variation and baseline selection.", "questions": [ { "text": "Which baseline is used, and are its algorithm, optimisation level, input and output requirements comparable to the parallel run?", "kind": "boundary", "id": "comparable-performance-evidence-q01" }, { "text": "What elapsed-time distribution, speedup and resource cost were measured, including or excluding setup, transfers and output as explicitly stated?", "kind": "measurement", "id": "comparable-performance-evidence-q02" } ] } ] }, { "id": "scaling-limits-and-interventions", "name": "Scaling limits and interventions", "description": "Relates changes in workload and resources to measured bottlenecks and possible improvements.", "findings": [ { "id": "scaling-decision", "name": "Scaling decision", "description": "Record the scaling regime, measured limits and evidence supporting a proposed intervention or stopping point.", "questions": [ { "text": "As resources increase, is total workload fixed, workload per resource fixed or another relationship used?", "kind": "definition", "id": "scaling-decision-q01" }, { "text": "How do serial work, coordination, imbalance and data movement contribute to the observed scaling limit?", "kind": "measurement", "id": "scaling-decision-q02" }, { "text": "Which measured change justifies adding resources, changing decomposition or reducing the allocation for the declared time, cost or energy objective?", "kind": "action", "id": "scaling-decision-q03" } ] } ] } ] }, { "id": "evidence-and-external-alignment", "name": "Evidence and external alignment", "description": "What the world already says about this thing, gathered so the model can be checked against it.", "rationale": "A model that cannot be lined up against existing standards, identifiers and practice cannot be adopted by anyone who already uses them.", "layers": [ { "id": "reported-evidence", "name": "Reported evidence", "description": "Findings from the breadth pass, kept separate from the structural claims.", "findings": [ { "id": "evidence-confidence-notes", "name": "Check these first", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ "This is recall-based content; no sources were consulted.", "The listed kinds overlap: decomposition strategies and memory architectures are separate classification axes.", "Performance comparisons require an explicit baseline, workload and definition of processing element; terminology also varies on whether instruction-level parallelism is included." ], "questions": [ { "id": "evidence-confidence-notes-q01", "text": "Which of these check these first hold for the sense of parallel computing this model covers, and on what evidence?", "kind": "provenance" } ] }, { "id": "evidence-kinds", "name": "Kinds and varieties", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ "Data parallelism", "Task parallelism", "Pipeline parallelism", "Shared-memory parallel computing", "Distributed-memory parallel computing", "Hybrid shared-memory and distributed-memory parallel computing" ], "questions": [ { "id": "evidence-kinds-q01", "text": "Which of these kinds and varieties hold for the sense of parallel computing this model covers, and on what evidence?", "kind": "provenance" } ] }, { "id": "evidence-standards-and-regulation", "name": "Standards and regulation", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ "MPI standard, maintained by the MPI Forum, specifies interfaces for message passing in parallel programs.", "OpenMP specification, maintained by the OpenMP Architecture Review Board, specifies directives, routines and environment variables for parallel programming.", "OpenCL specification, maintained by the Khronos Group, specifies programming interfaces and execution models for heterogeneous parallel computing." ], "questions": [ { "id": "evidence-standards-and-regulation-q01", "text": "Which of these standards and regulation hold for the sense of parallel computing this model covers, and on what evidence?", "kind": "provenance" } ] }, { "id": "evidence-real-world-use", "name": "Real-world use", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ "Numerical simulation of weather, fluid flow and physical systems", "Training and inference for machine learning models", "Rendering images and processing video", "Executing database queries and large-scale data processing", "Scientific searches and ensembles of independent simulation runs" ], "questions": [ { "id": "evidence-real-world-use-q01", "text": "Which of these real-world use hold for the sense of parallel computing this model covers, and on what evidence?", "kind": "provenance" } ] }, { "id": "evidence-measurements", "name": "Typical measurements", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ { "quantity": "Speedup", "typical_range": "Workload-dependent; T1/Tp compares execution time on one processing element with time on p elements; values below 1 indicate slowdown.", "unit": "dimensionless ratio" }, { "quantity": "Parallel efficiency", "typical_range": "Commonly between 0 and 1; calculated as speedup divided by p, with values above 1 possible when memory or other execution effects produce superlinear speedup.", "unit": "dimensionless ratio" }, { "quantity": "Strong scaling", "typical_range": "Measured by varying processing-element count while holding total problem size fixed; no universal numerical range.", "unit": "execution time in seconds versus processing-element count" }, { "quantity": "Weak scaling", "typical_range": "Measured by increasing problem size with processing-element count while holding work per element approximately fixed; ideal execution time remains constant.", "unit": "execution time in seconds versus processing-element count" } ], "questions": [ { "id": "evidence-measurements-q01", "text": "Which of these typical measurements hold for the sense of parallel computing this model covers, and on what evidence?", "kind": "provenance" } ] }, { "id": "evidence-failure-modes-and-hazards", "name": "Failure modes and hazards", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ "Data races and incorrect synchronization can corrupt results or make behaviour depend on timing.", "Deadlock or livelock can prevent useful progress.", "Load imbalance and serial portions can leave processing elements idle and limit speedup.", "Communication overhead, synchronization costs and memory-bandwidth contention can make parallel execution slower than serial execution.", "Changes in floating-point operation order can alter numerical results and impede reproducibility." ], "questions": [ { "id": "evidence-failure-modes-and-hazards-q01", "text": "Which of these failure modes and hazards hold for the sense of parallel computing this model covers, and on what evidence?", "kind": "provenance" } ] }, { "id": "evidence-neighbours", "name": "Neighbouring kinds and how to tell them apart", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ { "name": "Concurrent computing", "difference": "Concurrency concerns computations whose progress overlaps; parallel computing requires simultaneous execution, whereas concurrency can occur through interleaving on one processing element." }, { "name": "Distributed computing", "difference": "Distributed computing concerns components on distinct networked computers; parallel computing can occur within one computer, and a distributed system need not execute parts of a computation simultaneously." }, { "name": "High-performance computing", "difference": "High-performance computing concerns demanding computational workloads and performance; parallel computing is an execution approach used both in such systems and in ordinary devices." }, { "name": "Vector computing", "difference": "Vector computing applies operations to vectors of data and is one mechanism for data parallelism; parallel computing also includes independently executing tasks and processes." } ], "questions": [ { "id": "evidence-neighbours-q01", "text": "Which of these neighbouring kinds and how to tell them apart hold for the sense of parallel computing this model covers, and on what evidence?", "kind": "provenance" } ] } ] } ] } ] }, "openQuestions": [ "Which authoritative definitions should anchor the registry entry, and how do they treat implicit instruction-level parallelism and vector execution?", "Should the catalogue treat an ensemble of independent jobs as one parallel computation when its only shared objective is aggregate throughput?", "Which neighbouring registered models already own concurrency, distributed computing and computer architecture, and where should explicit links replace duplicated content?", "What normalisation, if any, makes efficiency comparisons meaningful across heterogeneous CPU and accelerator allocations?", "How much fault recovery and partial-result handling should this model own for long-running parallel jobs before responsibility passes to a distributed-systems model?" ], "statistics": { "bundles": 6, "layers": 11, "findings": 17, "questions": 29 } }, "draft": { "generator": "vr.draft.v3", "status": "draft-generated", "researched": false, "archetype": "abstract concept", "method": "Written from the archetype playbook - what this kind of thing needs beyond identity and provenance - and from the structure that recurred across 6,333 models already researched by two engines. Applied to this entry by rule. No source was read for this thing and no claim here is researched. This entry carries no facets of its own, so they were inferred from its domain - a guess about a whole domain applied to one thing.", "facetsInferred": true, "nextPass": "A researcher replaces this draft with a sourced specification. Treat every sentence below as a proposal to argue with.", "purpose": "Give an agent a durable, checkable way to recognise a parallel computing, record what state it is in, and decide what may be done with it.", "whatItIs": "Enable an agent to recognise parallel computation, assess its correctness and performance, and choose justified ways to partition, coordinate and execute computational work.", "characteristics": { "substance": "activity", "origin": "conceptual", "agency": "inert" }, "whatYouCanDoWithIt": [ "observed and measured" ], "distinguishingFeatures": [ "Names folded into this entry, which a task may need to split apart again: multicomputer, embarrassingly parallel, hardware multithreading, MIMD, MISD, automatic vectorization, SIMT, uniform memory access, MPMD, SPMD, Instruction level parallelism, loop-level parallelism.", "23 finer distinctions are held as aliases rather than separate entries, because telling them apart needs a task that asks for it.", "Described in 58 Wikipedia languages, which is a measure of how widely the thing is known, not of how important it is." ], "openQuestionsForResearch": [ "Which of the bundles below does a real task actually need, and which are ceremony?", "What does this thing have that the facets do not capture at all?", "Which neighbouring kind is most often confused with a parallel computing, and on what evidence are they told apart?" ], "whatItIsMadeOf": "something that happens over time", "physicalCharacter": [ "Does nothing on its own; everything it does, something else did to it.", "These come from the domain this entry sits in rather than from the entry itself, so treat them as a first guess about the whole domain applied to one thing." ], "whatCanBeDoneWithIt": [ "observe it, measure it, record its state" ], "howItIsRecognised": [ "Nothing to see. What is recognised is an instance of it, and which instances count is exactly what is argued about." ], "relatedModels": [ { "relation": "covers", "note": "Finer kinds folded into this entry because telling them apart needs a task that asks for it. Each is a model waiting to be split out when one does.", "targets": [ "multicomputer", "embarrassingly parallel", "hardware multithreading", "MIMD", "MISD", "automatic vectorization", "SIMT", "uniform memory access", "MPMD", "SPMD", "Instruction level parallelism", "loop-level parallelism" ] } ], "standing": "Described in 58 Wikipedia languages, which measures how widely it is written about rather than how important or how common it is. 23 finer distinctions are held inside this entry as names rather than as separate models.", "structure": { "bundles": [ { "id": "identity-and-classification", "name": "Identity, naming and classification", "description": "How an agent tells one parallel computing from another, and a parallel computing from things that resemble it.", "rationale": "Recognition comes before every other claim. Without stable identity nothing else in the model can be trusted to be about the same thing twice.", "layers": [ { "id": "naming-and-identifiers", "name": "Names and identifiers", "description": "The names this thing goes by and the identifiers that survive translation and time.", "findings": [ { "id": "preferred-name-and-aliases", "name": "Preferred name, aliases and local names", "description": "Which name to use, which names mean the same thing, and which merely sound similar.", "questions": [ { "id": "preferred-name-and-aliases-q01", "text": "What identifies and describes the name of a parallel computing, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "preferred-name-and-aliases-q02", "text": "Who or what asserted this about the name of a parallel computing, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "preferred-name-and-aliases-q03", "text": "What may an agent decide or do once the name of a parallel computing is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] }, { "id": "stable-identifiers", "name": "Stable identifiers and external keys", "description": "Identifiers that keep pointing at this kind of thing across systems and languages.", "questions": [ { "id": "stable-identifiers-q01", "text": "What identifies and describes an identifier for a parallel computing, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "stable-identifiers-q02", "text": "Who or what asserted this about an identifier for a parallel computing, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "stable-identifiers-q03", "text": "What may an agent decide or do once an identifier for a parallel computing is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] } ] }, { "id": "classification-and-granularity", "name": "Classification and granularity", "description": "Where a parallel computing sits among kinds, and how finely a task needs to cut it.", "findings": [ { "id": "kind-and-parents", "name": "Kind, parents and neighbouring kinds", "description": "The classes this thing belongs to and the ones it is next to.", "questions": [ { "id": "kind-and-parents-q01", "text": "What identifies and describes the kind of a parallel computing, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "kind-and-parents-q02", "text": "Who or what asserted this about the kind of a parallel computing, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "kind-and-parents-q03", "text": "What may an agent decide or do once the kind of a parallel computing is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] }, { "id": "distinguishing-features", "name": "Distinguishing features", "description": "What separates a parallel computing from the things most often confused with it.", "questions": [ { "id": "distinguishing-features-q01", "text": "What identifies and describes what distinguishes a parallel computing, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "distinguishing-features-q02", "text": "Who or what asserted this about what distinguishes a parallel computing, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "distinguishing-features-q03", "text": "What may an agent decide or do once what distinguishes a parallel computing is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] } ] } ] }, { "id": "state-and-lifecycle", "name": "State and lifecycle", "description": "The states a parallel computing passes through and the events that move it between them.", "rationale": "Most decisions about a thing depend on what state it is in now, which is a claim with a time on it, not a property.", "layers": [ { "id": "lifecycle-stages", "name": "Lifecycle stages", "description": "From coming into existence to ceasing to be one of these.", "findings": [ { "id": "stages-and-transitions", "name": "Stages and transitions", "description": "The stages worth naming and what moves a parallel computing between them.", "questions": [ { "id": "stages-and-transitions-q01", "text": "What identifies and describes the lifecycle of a parallel computing, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "stages-and-transitions-q02", "text": "Who or what asserted this about the lifecycle of a parallel computing, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "stages-and-transitions-q03", "text": "What may an agent decide or do once the lifecycle of a parallel computing is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] } ] }, { "id": "observations-and-status", "name": "Observations and current status", "description": "What is observed about a parallel computing, how often and by whom.", "findings": [ { "id": "observation-record", "name": "Observation record", "description": "How an observation of a parallel computing is recorded so that it can be superseded rather than overwritten.", "questions": [ { "id": "observation-record-q01", "text": "What identifies and describes an observation of a parallel computing, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "observation-record-q02", "text": "Who or what asserted this about an observation of a parallel computing, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "observation-record-q03", "text": "What may an agent decide or do once an observation of a parallel computing is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] } ] } ] }, { "id": "process-and-outcome", "name": "Process, inputs and outcome", "description": "How a parallel computing proceeds, what it needs and what it leaves behind.", "rationale": "An activity is known by its steps and its results, and both have to be recordable while it is still running.", "layers": [ { "id": "steps-and-sequence", "name": "Steps and sequence", "description": "The steps of a parallel computing, their order and what may run in parallel.", "findings": [ { "id": "steps-and-preconditions", "name": "Steps, preconditions and completion", "description": "What has to be true before each step of a parallel computing and what marks it done.", "questions": [ { "id": "steps-and-preconditions-q01", "text": "What identifies and describes a step of a parallel computing, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "steps-and-preconditions-q02", "text": "Who or what asserted this about a step of a parallel computing, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "steps-and-preconditions-q03", "text": "What may an agent decide or do once a step of a parallel computing is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] } ] }, { "id": "inputs-and-results", "name": "Inputs, resources and results", "description": "What a parallel computing consumes and what it produces.", "findings": [ { "id": "inputs-and-outputs", "name": "Inputs, outputs and side effects", "description": "The resources a parallel computing takes and the results it leaves, wanted or not.", "questions": [ { "id": "inputs-and-outputs-q01", "text": "What identifies and describes the inputs and results of a parallel computing, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "inputs-and-outputs-q02", "text": "Who or what asserted this about the inputs and results of a parallel computing, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "inputs-and-outputs-q03", "text": "What may an agent decide or do once the inputs and results of a parallel computing is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] } ] } ] }, { "id": "definitions-in-contest", "name": "Definitions and who holds them", "description": "What parallel computing is taken to mean, and by whom.", "rationale": "When a field disagrees about a concept, the disagreement is the content. A model that picks one definition silently destroys the information.", "layers": [ { "id": "competing-definitions", "name": "Competing definitions", "description": "The main readings and the traditions behind them.", "findings": [ { "id": "definition-map", "name": "Definitions and their holders", "description": "Each definition with the school or body that holds it.", "questions": [ { "id": "definition-map-q01", "text": "Which definitions of parallel computing are in use, and which tradition or body holds each?", "kind": "definition" }, { "id": "definition-map-q02", "text": "What turns on the difference between them in practice?", "kind": "boundary" } ] } ] }, { "id": "operationalisation", "name": "Operationalisation", "description": "How it is measured or applied when it has to be.", "findings": [ { "id": "operational-record", "name": "Measures and proxies", "description": "Instruments and indicators used to stand in for it.", "questions": [ { "id": "operational-record-q01", "text": "How is parallel computing operationalised or measured in practice, and by what instrument?", "kind": "measurement" }, { "id": "operational-record-q02", "text": "What does that operationalisation leave out, and when does that matter?", "kind": "boundary" } ] } ] } ] }, { "id": "instances-and-use", "name": "Instances, use and consequence", "description": "What counts as an instance of parallel computing and what follows from calling something that.", "rationale": "Applying a concept is an act with consequences, so a model must say what the label licenses and what it does not.", "layers": [ { "id": "instances", "name": "What counts as an instance", "description": "Clear cases, borderline cases and non-cases.", "findings": [ { "id": "instance-tests", "name": "Tests for an instance", "description": "What would settle whether something falls under it.", "questions": [ { "id": "instance-tests-q01", "text": "What would settle whether something is an instance of parallel computing?", "kind": "boundary" }, { "id": "instance-tests-q02", "text": "Which borderline cases are argued about, and on what grounds?", "kind": "definition" } ] } ] }, { "id": "consequence", "name": "Consequence of application", "description": "Rights, duties or decisions that follow from the label.", "findings": [ { "id": "consequence-record", "name": "What the label licenses", "description": "What an agent may do once something is classified this way.", "questions": [ { "id": "consequence-record-q01", "text": "What follows practically once something is treated as parallel computing?", "kind": "action" }, { "id": "consequence-record-q02", "text": "What must an agent not infer from the label alone?", "kind": "action" } ] } ] } ] }, { "id": "provenance-and-evidence", "name": "Provenance, evidence and time", "description": "Where every claim about a parallel computing came from and when it held.", "rationale": "A claim without a source and a time cannot be superseded, only overwritten, and an agent that overwrites loses the ability to explain itself.", "layers": [ { "id": "source-and-authority", "name": "Source and authority", "description": "Who said it, on what evidence, and how strongly.", "findings": [ { "id": "claim-provenance", "name": "Claim provenance and confidence", "description": "The authority behind each claim about a parallel computing and how confident it is.", "questions": [ { "id": "claim-provenance-q01", "text": "What identifies and describes a claim about a parallel computing, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "claim-provenance-q02", "text": "Who or what asserted this about a claim about a parallel computing, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "claim-provenance-q03", "text": "What may an agent decide or do once a claim about a parallel computing is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] } ] }, { "id": "time-and-versions", "name": "Time, versions and supersession", "description": "When a claim was true, when it was learnt, and what replaced it.", "findings": [ { "id": "validity-and-supersession", "name": "Validity period and supersession", "description": "How an old claim about a parallel computing is retired without being erased.", "questions": [ { "id": "validity-and-supersession-q01", "text": "What identifies and describes the validity of a claim about a parallel computing, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "validity-and-supersession-q02", "text": "Who or what asserted this about the validity of a claim about a parallel computing, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "validity-and-supersession-q03", "text": "What may an agent decide or do once the validity of a claim about a parallel computing is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] } ] } ] } ] }, "statistics": { "bundles": 6, "layers": 12, "findings": 14, "questions": 38 } } } }