1 citations · 1 across the 5 of their papers we have counts for
5 papers
HAS-GPU: Efficient Hybrid Auto-scaling with Fine-grained GPU Allocation for SLO-aware Serverless Inferences
Jianfeng Gu, Puxuan Wang, Isaac David Nunez Araya +2
Serverless Computing (FaaS) has become a popular paradigm for deep learning inference due to the ease of deployment and pay-per-use benefits. However, current serverless inference…
VersaSlot: Efficient Fine-grained FPGA Sharing with Big.Little Slots and Live Migration in FPGA Cluster
Jianfeng Gu, Hao Wang, Xiaorang Guo +2
As FPGAs gain popularity for on-demand application acceleration in data center computing, dynamic partial reconfiguration (DPR) has become an effective fine-grained sharing techniq…
Command-line Risk Classification using Transformer-based Neural Architectures
Paolo Notaro, Soroush Haeri, Jorge Cardoso +1
To protect large-scale computing environments necessary to meet increasing computing demand, cloud providers have implemented security measures to monitor Operations and Maintenanc…
Apodotiko: Enabling Efficient Serverless Federated Learning in Heterogeneous Environments
Mohak Chadha, Alexander Jensen, Jianfeng Gu +2
Federated Learning (FL) is an emerging machine learning paradigm that enables the collaborative training of a shared global model across distributed clients while keeping the data…
Training Heterogeneous Client Models using Knowledge Distillation in Serverless Federated Learning
Mohak Chadha, Pulkit Khera, Jianfeng Gu +2
Federated Learning (FL) is an emerging machine learning paradigm that enables the collaborative training of a shared global model across distributed clients while keeping the data…