Bibliographic record
Abstract
Traditionally in the design automation field, simulation has been applied to explore low-level design details. However, a focus upon design specification driven simulation environments has been missing. Such tools can conceptually capture an initial design specification and allow design exploration at a highly abstract level with a simulation-based environment prior to synthesis. At this design stage, software and hardware elements can be indistinguishable and represent a good opportunity for addressing system level concerns such as partitioning, co-design and architectural trade-offs. With the advent of more complex systems, the ability to model and verify properties of various alternative designs is mandatory to produce cost effective and sound systems. Specification driven design implies a need to support architectural design and rapid prototyping systems (RPS) within a design flow. The system design activity is generally the starting point within the design phase of a product life-cycle - which involves the design capture of specifications into an executable model. Hence language requirements at this stage encompass modeling capabilities. The design and modeling of the conceptual system at this abstract level implies that the design environment must support concepts such as generic model reuse, component and structural reuse, intelligent library management, and hierarchical design. After a suitable model is defined, the language must provide support for experimentation and analysis. These activities are crucial for a designer to explore a given design space, make appropriate trade-offs and partition the design to different hardware/software configurations. Such activities can be supported through design simulators and formal methods. This paper examines the benefits of applying a specification driven approach and presents a framework for environments that can support the related design activities. The Design Analysis and Simulation Environment (DASE) based upon this framework has been successfully implemented through a joint initiative between Bell Canada and McGill University.
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 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".