Aditya Dhakal

According to our database, Aditya Dhakal authored at least 15 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Predicting Heterogeneity and Serverless Principles of Converged High-Performance Computing, Artificial Intelligence, and Workflows.

Pedro Bruel, Sai Rahul Chalamalasetti, Aditya Dhakal, Eitan Frachtenberg, Ninad Hogade, Rolando Pablo Hong Enriquez, Alok Mishra, Dejan S. Milojicic, Pavana Prakash, Gourav Rattihalli

Computer, January, 2024

2023

Networked Architectures for Localization-Based Multi-User Augmented Reality.

Jiasi Chen, K. K. Ramakrishnan, Aditya Dhakal, Xukan Ran

IEEE Commun. Mag., December, 2023

D-STACK: High Throughput DNN Inference by Effective Multiplexing and Spatio-Temporal Scheduling of GPUs.

Aditya Dhakal, Sameer G. Kulkarni, K. K. Ramakrishnan

CoRR, 2023

Fine-grained accelerator partitioning for Machine Learning and Scientific Computing in Function as a Service Platform.

Aditya Dhakal, Philipp Raith, Logan T. Ward, Rolando P. Hong Enriquez, Gourav Rattihalli, Kyle Chard, Ian T. Foster, Dejan S. Milojicic

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

Kernel-as-a-Service: A Serverless Programming Model for Heterogeneous Hardware Accelerators.

Tobias Pfandzelter, Aditya Dhakal, Eitan Frachtenberg, Sai Rahul Chalamalasetti, Darel Emmot, Ninad Hogade, Rolando Pablo Hong Enriquez, Gourav Rattihalli, David Bermbach, Dejan S. Milojicic

Proceedings of the 24th International Middleware Conference, 2023

Fine-Grained Heterogeneous Execution Framework with Energy Aware Scheduling.

Gourav Rattihalli, Ninad Hogade, Aditya Dhakal, Eitan Frachtenberg, Rolando P. Hong Enriquez, Pedro Bruel, Alok Mishra, Dejan S. Milojicic

Proceedings of the 16th IEEE International Conference on Cloud Computing, 2023

2022

Slice-Tune: a system for high performance DNN autotuning.

Aditya Dhakal, K. K. Ramakrishnan, Sameer G. Kulkarni, Puneet Sharma, Junguk Cho

Proceedings of the Middleware '22: 23rd International Middleware Conference, Quebec, QC, Canada, November 7, 2022

SLAM-share: visual simultaneous localization and mapping for real-time multi-user augmented reality.

Aditya Dhakal, Xukan Ran, Yunshu Wang, Jiasi Chen, K. K. Ramakrishnan

Proceedings of the 18th International Conference on emerging Networking EXperiments and Technologies, 2022

2021

Primitives Enhancing GPU Runtime Support for Improved DNN Performance.

Aditya Dhakal, Sameer G. Kulkarni, K. K. Ramakrishnan

Proceedings of the 14th IEEE International Conference on Cloud Computing, 2021

2020

Spatial Sharing of GPU for Autotuning DNN models.

Aditya Dhakal, Junguk Cho, Sameer G. Kulkarni, K. K. Ramakrishnan, Puneet Sharma

CoRR, 2020

Machine Learning at the Edge: Efficient Utilization of Limited CPU/GPU Resources by Multiplexing.

Aditya Dhakal, Sameer G. Kulkarni, K. K. Ramakrishnan

Proceedings of the 28th IEEE International Conference on Network Protocols, 2020

ECML: Improving Efficiency of Machine Learning in Edge Clouds.

Aditya Dhakal, Sameer G. Kulkarni, K. K. Ramakrishnan

Proceedings of the 9th IEEE International Conference on Cloud Networking, 2020

GSLICE: controlled spatial sharing of GPUs for a scalable inference platform.

Aditya Dhakal, Sameer G. Kulkarni, K. K. Ramakrishnan

Proceedings of the SoCC '20: ACM Symposium on Cloud Computing, 2020

2019

NetML: An NFV Platform with Efficient Support for Machine Learning Applications.

Aditya Dhakal, K. K. Ramakrishnan

Proceedings of the 5th IEEE Conference on Network Softwarization, 2019

2017

Machine learning at the network edge for automated home intrusion monitoring.

Aditya Dhakal, K. K. Ramakrishnan

Proceedings of the 25th IEEE International Conference on Network Protocols, 2017