Report Open Access
Benchmarking Machine Learning in HEP
Sabina Manafli
Citation Style Language JSON Export
{
"publisher": "Zenodo",
"DOI": "10.5281/zenodo.1967555",
"author": [
{
"family": "Sabina Manafli"
}
],
"issued": {
"date-parts": [
[
2018,
12,
5
]
]
},
"abstract": "<p>The interest on machine learning workloads in the HEP community has increased exponentially in the last years, making more and more important the need of a thorough benchmarking of the most relevant/significant workloads that are going to run on the experiments. The purpose of this project is to build a set of techniques to benchmark deep neural networks on different<br>\nhardware. By using different tools and methodologies we make several important observations and conclusions based on the performance of deep learning application running on GPUs which have different compute capabilities.</p>",
"title": "Benchmarking Machine Learning in HEP",
"type": "article",
"id": "1967555"
}
157
136
views
downloads
| All versions | This version | |
|---|---|---|
| Views | 157 | 156 |
| Downloads | 136 | 135 |
| Data volume | 43.0 MB | 42.7 MB |
| Unique views | 147 | 146 |
| Unique downloads | 134 | 133 |
Indexed in
- Publication date:
- December 5, 2018
- DOI:
-
- Keyword(s):
- CERN openlab summer student programme
- Communities:
- License (for files):
- Creative Commons Attribution 4.0 International