MétaCan
Menu
Back to cohort

Approximate Parallel Annealing Ising Machines (APAIMs): Controller and Arithmetic Design

2023· article· en· W4402264015 on OpenAlexafffund
Qichao Tao, Tingting Zhang, Jie Han

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicQuantum Computing Algorithms and Architecture
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship CouncilUniversity of Alberta
KeywordsComputer scienceParallel computingArithmeticSimulated annealingIsing modelMathematicsAlgorithmPhysicsStatistical physics

Abstract

fetched live from OpenAlex

The demand for solving complex combinatorial optimization problems (COPs) in commercial and industrial applications motivates the development of efficient solvers. Ising model-based computers, or Ising machines, have emerged as high-performance solvers. Recently, an approximate parallel annealing Ising machine (APAIM) has been developed for solving constrained COPs such as the traveling salesman problem (TSP). To provide additional detail about the APAIM, this paper presents the designs of its controller and arithmetic units, especially that of the approximate adders in the local field accumulator units (LAUs) required for computing the Hamiltonian in the Ising model. The controller is implemented as a finite state machine and generates an instruction to determine the system operation. To improve hardware efficiency, the so-called lower-part-OR and truncated adder is used for the mantissa addition of floating-point numbers in the LAUs. Although the solution quality is slightly reduced, the use of approximate adders improves the hardware efficiency of a 64-spin APAIM.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.626
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.246
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes2
Has abstractyes

Explore more

Same topicQuantum Computing Algorithms and ArchitectureFrench-language works237,207