Name
Abstract | ||
|---|---|---|
Cloud providers offer a variety of storage solutions for hosting data, both in price and in performance. For Analytics and machine learning applications, object storage services are the go-to solution for hosting the datasets that exceed tens of gigabytes in size. However, such a choice results in performance degradation for these applications and requires extra engineering effort in the form of c... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/CLOUD53861.2021.00084 | 2021 IEEE 14th International Conference on Cloud Computing (CLOUD) |
Keywords | DocType | ISSN |
Training,Degradation,Deep learning,Cloud computing,Codes,Conferences,Benchmark testing | Conference | 2159-6182 |
ISBN | Citations | PageRank |
978-1-6654-0060-2 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Panos Koutsovasilis | 1 | 0 | 0.34 |
| Srikumar Venugopal | 2 | 0 | 0.34 |
| Yiannis Gkoufas | 3 | 17 | 5.96 |
| Christian Pinto | 4 | 0 | 2.03 |