Aditya Dhakal

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 17

Top Topics

High Throughput

Service Platform

Scientific Computing

Top Venues

Publications

Pedro Bruel, Sai Rahul Chalamalasetti, Aditya Dhakal, Eitan Frachtenberg, Ninad Hogade, Rolando Pablo Hong Enriquez, Alok Mishra, Dejan Milojicic, Pavana Prakash, Gourav Rattihalli
Predicting Heterogeneity and Serverless Principles of Converged High-Performance Computing, Artificial Intelligence, and Workflows. Computer 57 (1) (2024)
Rolando P. Hong Enriquez, Rosa M. Badia, Barbara M. Chapman, Kirk Bresniker, Scott Pakin, Alok Mishra, Pedro Bruel, Aditya Dhakal, Gourav Rattihalli, Ninad Hogade, Eitan Frachtenberg, Dejan S. Milojicic
Quantum optimization algorithms: Energetic implications. Concurr. Comput. Pract. Exp. 36 (16) (2024)
Yunming Xiao, Diman Zad Tootaghaj, Aditya Dhakal, Lianjie Cao, Puneet Sharma, Aleksandar Kuzmanovic
Conspirator: SmartNIC-Aided Control Plane for Distributed ML Workloads. USENIX ATC (2024)
Gourav Rattihalli, Ninad Hogade, Aditya Dhakal, Eitan Frachtenberg, Rolando P. Hong Enriquez, Pedro Bruel, Alok Mishra, Dejan S. Milojicic
Fine-Grained Heterogeneous Execution Framework with Energy Aware Scheduling. CLOUD (2023)
Tobias Pfandzelter, Aditya Dhakal, Eitan Frachtenberg, Sai Rahul Chalamalasetti, Darel Emmot, Ninad Hogade, Rolando Pablo Hong Enriquez, Gourav Rattihalli, David Bermbach, Dejan S. Milojicic
Kernel-as-a-Service: A Serverless Programming Model for Heterogeneous Hardware Accelerators. Middleware (2023)
Jiasi Chen, K. K. Ramakrishnan, Aditya Dhakal, Xukan Ran
Networked Architectures for Localization-Based Multi-User Augmented Reality. IEEE Commun. Mag. 61 (12) (2023)
Aditya Dhakal, Sameer G. Kulkarni, K. K. Ramakrishnan
D-STACK: High Throughput DNN Inference by Effective Multiplexing and Spatio-Temporal Scheduling of GPUs. CoRR (2023)
Aditya Dhakal, Philipp Raith, Logan T. Ward, Rolando P. Hong Enriquez, Gourav Rattihalli, Kyle Chard, Ian T. Foster, Dejan S. Milojicic
Fine-grained accelerator partitioning for Machine Learning and Scientific Computing in Function as a Service Platform. SC Workshops (2023)
Aditya Dhakal, Xukan Ran, Yunshu Wang, Jiasi Chen, K. K. Ramakrishnan
SLAM-share: visual simultaneous localization and mapping for real-time multi-user augmented reality. CoNEXT (2022)
Aditya Dhakal, K. K. Ramakrishnan, Sameer G. Kulkarni, Puneet Sharma, Junguk Cho
Slice-Tune: a system for high performance DNN autotuning. Middleware (2022)
Aditya Dhakal, Sameer G. Kulkarni, K. K. Ramakrishnan
Primitives Enhancing GPU Runtime Support for Improved DNN Performance. CLOUD (2021)
Aditya Dhakal, Sameer G. Kulkarni, K. K. Ramakrishnan
Machine Learning at the Edge: Efficient Utilization of Limited CPU/GPU Resources by Multiplexing. ICNP (2020)
Aditya Dhakal, Sameer G. Kulkarni, K. K. Ramakrishnan
GSLICE: controlled spatial sharing of GPUs for a scalable inference platform. SoCC (2020)
Aditya Dhakal, Junguk Cho, Sameer G. Kulkarni, K. K. Ramakrishnan, Puneet Sharma
Spatial Sharing of GPU for Autotuning DNN models. CoRR (2020)
Aditya Dhakal, Sameer G. Kulkarni, K. K. Ramakrishnan
ECML: Improving Efficiency of Machine Learning in Edge Clouds. CloudNet (2020)
Aditya Dhakal, K. K. Ramakrishnan
NetML: An NFV Platform with Efficient Support for Machine Learning Applications. NetSoft (2019)
Aditya Dhakal, K. K. Ramakrishnan
Machine learning at the network edge for automated home intrusion monitoring. ICNP (2017)