1 citations · 1 across the 3 of their papers we have counts for
6 papers
EMLIO: Minimizing I/O Latency and Energy Consumption for Large-Scale AI Training
Hasibul Jamil, MD S Q Zulkar Nine, Tevfik Kosar
Large-scale deep learning workloads increasingly suffer from I/O bottlenecks as datasets grow beyond local storage capacities and GPU compute outpaces network and disk latencies. W…
Energy-Efficient and High-Performance Data Transfers with DRL Agents
Hasibul Jamil, Jacob Goldverg, Elvis Rodrigues +2
The rapid growth of data across fields of science and industry has increased the need to improve the performance of end-to-end data transfers while using the resources more efficie…
A Two-Phase Dynamic Throughput Optimization Model for Big Data Transfers
Zulkar Nine, Tevfik Kosar
The amount of data moved over dedicated and non-dedicated network links increases much faster than the increase in the network capacity, but the current solutions fail to guarantee…
Energy-Efficient Mobile Network I/O Optimization at the Application Layer
Kemal Guner, MD S Q Zulkar Nine, Tevfik Kosar +1
Mobile data traffic (cellular + WiFi) will exceed PC Internet traffic by 2020. As the number of smartphone users and the amount of data transferred per smartphone grow exponentiall…
OneDataShare: A Vision for Cloud-hosted Data Transfer Scheduling and Optimization as a Service
Asif Imran, Md S Q Zulkar Nine, Kemal Guner +1
Fast, reliable, and efficient data transmission across wide-area networks is a predominant bottleneck for data-intensive cloud applications. This paper introduces OneDataShare, whi…
Data Transfer Optimization Based on Offline Knowledge Discovery and Adaptive Real-time Sampling
MD S Q Zulkar Nine, Kemal Guner, Ziyun Huang +3
The amount of data moved over dedicated and non-dedicated network links increases much faster than the increase in the network capacity, but the current solutions fail to guarantee…