Approximate Parallel Annealing Ising Machines (APAIMs): Controller and Arithmetic Design
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".