2 citations · 3 across the 3 of their papers we have counts for
5 papers · 1 filter
Effective Elastic Scaling of Deep Learning Workloads
Vaibhav Saxena, K. R. Jayaram, Saurav Basu +2
The increased use of deep learning (DL) in academia, government and industry has, in turn, led to the popularity of on-premise and cloud-hosted deep learning platforms, whose goals…
FfDL : A Flexible Multi-tenant Deep Learning Platform
K. R. Jayaram, Vinod Muthusamy, Parijat Dube +9
Deep learning (DL) is becoming increasingly popular in several application domains and has made several new application features involving computer vision, speech recognition and s…
Elastic Remote Methods
K. R. Jayaram
For distributed applications to take full advantage of cloud computing systems, we need middleware systems that allow developers to build elasticity management components right int…
Dependability in a Multi-tenant Multi-framework Deep Learning as-a-Service Platform
Scott Boag, Parijat Dube, Kaoutar El Maghraoui +7
Deep learning (DL), a form of machine learning, is becoming increasingly popular in several application domains. As a result, cloud-based Deep Learning as a Service (DLaaS) platfor…
IBM Deep Learning Service
Bishwaranjan Bhattacharjee, Scott Boag, Chandani Doshi +15
Deep learning driven by large neural network models is overtaking traditional machine learning methods for understanding unstructured and perceptual data domains such as speech, te…