Name
Abstract | ||
|---|---|---|
ABSTRACTRecent advances in networking technology and serverless architectures have enabled automated distribution of compute workloads at the function level. As heterogeneity and physical distribution of computing resources increase, so too does the need to effectively use those resources. This is especially true when leveraging multiple compute resources in the form of local, distributed, and cloud resources. Adding to the complexity of the problem is different notions of "cost" when it comes to using these resources. Tradeoffs exist due to the inherent difference between costs of computation for the end user. For example, deploying a workload on the cloud could be much faster than using local resources but using the cloud incurs a financial cost. Here, the end user is presented with the tradeoff between time and money. We describe preliminary work towards Delts+, a framework that integrates multidimensional cost objectives, cost tradeoffs, and optimization under constraints. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3452413.3464790 | HPDC |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matt Baughman | 1 | 6 | 2.80 |
| Rohan Kumar | 2 | 8 | 1.54 |
| Ian T. Foster | 3 | 0 | 0.34 |
| Kyle Chard | 4 | 515 | 56.70 |