Aditya Dhakal

Orcid: 0000-0002-8297-8525

According to our database1, Aditya Dhakal authored at least 18 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Quantum optimization algorithms: Energetic implications.
Concurr. Comput. Pract. Exp., July, 2024

Predicting Heterogeneity and Serverless Principles of Converged High-Performance Computing, Artificial Intelligence, and Workflows.
Computer, January, 2024

Conspirator: SmartNIC-Aided Control Plane for Distributed ML Workloads.
Proceedings of the 2024 USENIX Annual Technical Conference, 2024

Opportunistic Energy-Aware Scheduling for Container Orchestration Platforms Using Graph Neural Networks.
Proceedings of the 24th IEEE International Symposium on Cluster, 2024

2023
Networked Architectures for Localization-Based Multi-User Augmented Reality.
IEEE Commun. Mag., December, 2023

D-STACK: High Throughput DNN Inference by Effective Multiplexing and Spatio-Temporal Scheduling of GPUs.
CoRR, 2023

Fine-grained accelerator partitioning for Machine Learning and Scientific Computing in Function as a Service Platform.
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.
Proceedings of the 24th International Middleware Conference, 2023

Fine-Grained Heterogeneous Execution Framework with Energy Aware Scheduling.
Proceedings of the 16th IEEE International Conference on Cloud Computing, 2023

2022
Slice-Tune: a system for high performance DNN autotuning.
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.
Proceedings of the 18th International Conference on emerging Networking EXperiments and Technologies, 2022

2021
Primitives Enhancing GPU Runtime Support for Improved DNN Performance.
Proceedings of the 14th IEEE International Conference on Cloud Computing, 2021

2020
Spatial Sharing of GPU for Autotuning DNN models.
CoRR, 2020

Machine Learning at the Edge: Efficient Utilization of Limited CPU/GPU Resources by Multiplexing.
Proceedings of the 28th IEEE International Conference on Network Protocols, 2020

ECML: Improving Efficiency of Machine Learning in Edge Clouds.
Proceedings of the 9th IEEE International Conference on Cloud Networking, 2020

GSLICE: controlled spatial sharing of GPUs for a scalable inference platform.
Proceedings of the SoCC '20: ACM Symposium on Cloud Computing, 2020

2019
NetML: An NFV Platform with Efficient Support for Machine Learning Applications.
Proceedings of the 5th IEEE Conference on Network Softwarization, 2019

2017
Machine learning at the network edge for automated home intrusion monitoring.
Proceedings of the 25th IEEE International Conference on Network Protocols, 2017


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