Parallel computation thesis

In computational complexity theory, the parallel computation thesis is a hypothesis which states that the time used by a (reasonable) parallel machine is polynomially related to the space used by a sequential machine.

Version

v1 · 2026-09-28 · History

Domain-specific #

11195

Domain group

Applied Sciences & Engineering

Origin domain

Computer Science & Software Engineering

Subdomains

Parallel Complexity Theory, Computational Complexity → Computer Science & Software Engineering

Core Idea

Parallel computation thesis is treated here as the recurring parallel complexity theory identity summarized by this source-grounded definition: In computational complexity theory, the parallel computation thesis is a hypothesis which states that the time used by a (reasonable) parallel machine is polynomially related to the space used by a sequential machine. In computational complexity theory, the parallel computation thesis is a hypothesis which states that the time used by a (reasonable) parallel machine is polynomially related to the space used by a sequential machine.

Scope of Application

• Definition. Conditional on a function T(n) , saying that the use of one resource R in one model is polynomially related to the use of another resource R' in another model means.

• Documented setting. In computational complexity theory, the parallel computation thesis is a hypothesis which states that the time used by a (reasonable) parallel machine is polynomially related to the space used by a.

• Documented setting. However, the model allows 2^{2 parallel threads of computation after T(n) steps.}

• Documented setting. In other words, for a computational model which allows computations to branch and run in parallel without bound, a formal language which is decidable under the model using no more than.

• Definition. Given two models of computation, such as Turing machines and PRAM, they would have computational resource usages.

Clarity

A clear use of Parallel computation thesis names the carrier, the operative relation, and the conditions under which the source treats the identity as present. The minimal definition is In computational complexity theory, the parallel computation thesis is a hypothesis which states that the time used by a (reasonable) parallel machine is polynomially related to the space used by a sequential machine.

Manages Complexity

Parallel computation thesis compresses multiple parallel complexity theory details into a stable diagnostic relation. The source shows both the central mechanism—in other words, for a computational model which allows computations to branch and run in parallel without bound, a formal language which is decidable under the model using no more than t(n) steps for inputs of length n is decidable by a non-branching machine using no more than.

Abstract Reasoning

1. Type the carrier. Identify the parallel complexity theory entities to which the claim applies.
2. State the relation. Use the source-grounded identity: In computational complexity theory, the parallel computation thesis is a hypothesis which states that the time used by a (reasonable) parallel machine is polynomially related to the space used by a sequential machine.
3. Check operation and conditions. For PRAM, the resources can be parallel time, total number of processors, etc.
4. Demand recognition evidence.

Knowledge Transfer

Within the home domain. Knowledge about Parallel computation thesis transfers literally when a new case preserves the same carrier type, relation, and recognition test. Conditional on a function T(n) , saying that the use of one resource R in one model is polynomially related to the use of another resource R' in another model means the following. In computational complexity theory, the parallel computation thesis is a hypothesis which states that the time used by a (reasonable) parallel machine is polynomially related to the space used by a sequential machine. Beyond the home domain.

Neighborhood in Abstraction Space

Parallel computation thesis sits in a crowded region of the domain-specific corpus (32^nd percentile for distinctiveness): several abstractions share nearly its structure, so a description that fits it tends to fit its neighbors too.

Family — Computation Models & Complexity Classes (37 abstractions)

Nearest neighbors

• Counter-machine model — 0.90
• Unambiguous finite automaton — 0.89
• Randomness extractor — 0.89
• NC (complexity) — 0.88
• Co-RE-complete — 0.88

Computed from structural-signature embeddings · 2026-10-08