Name
Title | ||
|---|---|---|
Godec - An Open-Source Data Processing Framework for Deploying ML Data Flows in Edge-Computing Environments. |
Abstract | ||
|---|---|---|
We present Godec, a C++-based framework that allows easy transition of complex machine learning (ML) data flows to edge-computing environments where common data processing frameworks do not apply. Godec allows for free mixing of technologies such as Kaldi, TensorFlow and custom modules, all wrapped into a single OS process, making it easy to deploy inference engines on constrained environments like Android, iOS or embedded Linux. Godec achieves this by connecting the components into an arbitrary graph specified by a simple JSON file during startup. Despite being multithreaded, results between runs are guaranteed identical, allowing for immediate transition from offline experiments to deployment. The source code is released under the MIT license https://github.com/raytheonbbn/Godec, with the authors’ hoping that the community will find it a useful tool to create their own components for it, in turn enabling others to mix and merge disparate technologies into applications of their own. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/978-3-030-59824-2_7 | EDGE |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ralf Meermeier | 1 | 0 | 0.34 |
| Le Zhang | 2 | 268 | 32.16 |
| Francis Keith | 3 | 1 | 1.06 |
| William Hartmann | 4 | 64 | 10.66 |
| Stavros Tsakalidis | 5 | 213 | 13.83 |
| Andrew Tabarez | 6 | 0 | 0.34 |