D5.1 Analysis of Models and Practices for Industrial Access
Bibliographic record
Abstract
In PRACE-3IP, WP5 “Services for industrial users and SMEs” has the objective to design and pilot an effective and integrated set of high-level, coherent and complementary services to industrial users and in particular to Small Medium Enterprises (SMEs) which may be interested in advanced HPC resources to enhance their innovation and competitiveness through high performance simulation. These services will be gathered in an Integrated Access Programme (IAP) for Industries and SMEs and will be proposed to the PRACE AISBL for the inclusion in its services offer. The objective of this deliverable is to identify and analyse the models and the practices to define an effective IAP. The industry support models currently operating in eight HPC infrastructures in Europe and three in USA and Canada have been investigated. The analysis has been done leveraging on the work of earlier studies and activating specific contacts with these main infrastructures. A sub-set of the initiatives provided from these infrastructures specifically targeted the SME. In these examples the support programmes were mainly enabler actions with the goal to use the HPC infrastructures to demonstrate to the SMEs the benefit of adopting advanced simulation methods. To complete the analysis, the investigation has been extended to support models offered by eleven non HPC research infrastructures in order to evaluate the offer in different areas respect to the HPC services (Synchrotrons, Molecular Biology and Genomics, Technological Innovation, Micro and Nano Technologies, Semiconductors research, Clinical trials, etc.). The results of all these investigations of HPC and non HPC Infrastructure, integrated with the requirements of industrial users analysed in PRACE-1IP WP5 have permitted to identify a set of the main current needs of industrial users towards HPC. These needs span from raising awareness to coaching, from training and information to trying out HPC solutions to open research and development access to HPC infrastructure. All these elements should contribute to an effective Integrated Access Programme provision for Industry and SMEs offered by PRACE.
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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 | 0.013 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".