1 citations · 2 across the 3 of their papers we have counts for
4 papers
Evaluating 5G-connected IoT for Power Line Temperature Prediction: Real-World Latency and Cost Trade-offs Between MEC and Cloud
Aakash Sharma, Sigmund Akselsen, Anders Andersen +2
One of the key promises of Mobile Edge Computing (MEC) is its low latency. Current large-scale IoT deployments rely on cloud for their reliability, low cost, and ease of use. For o…
GPU Cluster Scheduling for Network-Sensitive Deep Learning
Aakash Sharma, Vivek M. Bhasi, Sonali Singh +3
We propose a novel GPU-cluster scheduler for distributed DL (DDL) workloads that enables proximity based consolidation of GPU resources based on the DDL jobs' sensitivities to the…
Analysis of Distributed Deep Learning in the Cloud
Aakash Sharma, Vivek M. Bhasi, Sonali Singh +6
We aim to resolve this problem by introducing a comprehensive distributed deep learning (DDL) profiler, which can determine the various execution "stalls" that DDL suffers from whi…
CASH: A Credit Aware Scheduling for Public Cloud Platforms
Aakash Sharma, Saravanan Dhakshinamurthy, George Kesidis +1
The public cloud offers a myriad of services which allows its tenants to process large scale big data in a flexible, easy and cost effective manner. Tenants generally use large sca…