Data · dataset · 2026
Microarchitecture and workload-aware error prediction based on artificial intelligence
Listed in ZivaHub and Deakin Research Online and DMU Figshare — shown once because both records carry DOI 10.17034/32640663.v1
This dissertation focusses on modelling the data-dependent dynamic timing behaviour of modern, complex designs, in an effort to assist in evaluating the impact of timing errors early in the design cycle or navigate the selection of more optimistic operating conditions.
Description
This thesis investigates in-depth the factors that contribute to timing error manifestation in pipelined architectures and discusses AI-based solutions and improvements.<br><br>
Links
Where it is published
- DOI doi.org/10.17034/32640663.v1 ↗
DOI / persistent id · from zivahub uct ac za
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from zivahub uct ac za
Topics
- From keywords
- Artificial intelligence · Artificial intelligence · Artificial intelligence · Computer Science & AI · Computer Science & AI · Computer Science & AI · Earth & Environmental Science · Earth & Environmental Science · Earth & Environmental Science · Machine learning · Machine learning · Machine learning · Neural networks · Neural networks · Neural networks
Provenance · 3 source records, 19 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ZivaHub | oai:figshare.com:article/32640663 | 8 d ago | JSON v1 |
| Deakin Research Online | oai:figshare.com:article/32640663 | 8 d ago | JSON v1 |
| DMU Figshare | oai:figshare.com:article/32640663 | 8 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:field:461104 | mapping · figshare dmu ac uk | vocabulary-mapper@1.0.0 | keywords['neural networks'] |
| concepts[field].anzsrc:field:461104 | mapping · zivahub uct ac za | vocabulary-mapper@1.0.0 | keywords['neural networks'] |
| concepts[field].anzsrc:field:461104 | mapping · dro deakin edu au | vocabulary-mapper@1.0.0 | keywords['neural networks'] |
| concepts[field].anzsrc:group:4602 | mapping · zivahub uct ac za | vocabulary-mapper@1.0.0 | keywords['artificial intelligence'] |
| concepts[field].anzsrc:group:4602 | mapping · dro deakin edu au | vocabulary-mapper@1.0.0 | keywords['artificial intelligence'] |
| concepts[field].anzsrc:group:4602 | mapping · figshare dmu ac uk | vocabulary-mapper@1.0.0 | keywords['artificial intelligence'] |
| concepts[field].anzsrc:group:4611 | mapping · dro deakin edu au | vocabulary-mapper@1.0.0 | keywords['machine learning'] |
| concepts[field].anzsrc:group:4611 | mapping · figshare dmu ac uk | vocabulary-mapper@1.0.0 | keywords['machine learning'] |
| concepts[field].anzsrc:group:4611 | mapping · zivahub uct ac za | vocabulary-mapper@1.0.0 | keywords['machine learning'] |
| concepts[field].local:field:computer-science-ai | mapping · figshare dmu ac uk | connector:figshare_dmu_ac_uk@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · dro deakin edu au | connector:dro_deakin_edu_au@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · dro deakin edu au | connector:dro_deakin_edu_au@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · figshare dmu ac uk | connector:figshare_dmu_ac_uk@1.0.0 | |
| description | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/description |
| license_text | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| publication_date | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| title | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/title |