41 citations · 144 across the 18 of their papers we have counts for
20 papers
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…
gFaaS: Enabling Generic Functions in Serverless Computing
Mohak Chadha, Paul Wieland, Michael Gerndt
With the advent of AWS Lambda in 2014, Serverless Computing, particularly Function-as-a-Service (FaaS), has witnessed growing popularity across various application domains. FaaS en…
GreenCourier: Carbon-Aware Scheduling for Serverless Functions
Mohak Chadha, Thandayuthapani Subramanian, Eishi Arima +3
This paper presents GreenCourier, a novel scheduling framework that enables the runtime scheduling of serverless functions across geographically distributed regions based on their…
Sustainability in HPC: Vision and Opportunities
Mohak Chadha, Eishi Arima, Amir Raoofy +2
Tackling climate change by reducing and eventually eliminating carbon emissions is a significant milestone on the path toward establishing an environmentally sustainable society. A…
FaST-GShare: Enabling Efficient Spatio-Temporal GPU Sharing in Serverless Computing for Deep Learning Inference
Jianfeng Gu, Yichao Zhu, Puxuan Wang +2
Serverless computing (FaaS) has been extensively utilized for deep learning (DL) inference due to the ease of deployment and pay-per-use benefits. However, existing FaaS platforms…
Exploring the Use of WebAssembly in HPC
Mohak Chadha, Nils Krueger, Jophin John +3
Containerization approaches based on namespaces offered by the Linux kernel have seen an increasing popularity in the HPC community both as a means to isolate applications and as a…
FedLesScan: Mitigating Stragglers in Serverless Federated Learning
Mohamed Elzohairy, Mohak Chadha, Anshul Jindal +4
Federated Learning (FL) is a machine learning paradigm that enables the training of a shared global model across distributed clients while keeping the training data local. While mo…
Migrating from Microservices to Serverless: An IoT Platform Case Study
Mohak Chadha, Victor Pacyna, Anshul Jindal +2
Microservice architecture is the common choice for developing cloud applications these days since each individual microservice can be independently modified, replaced, and scaled.…
Bunk8s: Enabling Easy Integration Testing of Microservices in Kubernetes
Christoph Reile, Mohak Chadha, Valentin Hauner +3
Microservice architecture is the common choice for cloud applications these days since each individual microservice can be independently modified, replaced, and scaled. However, th…
SLAM: SLO-Aware Memory Optimization for Serverless Applications
Gor Safaryan, Anshul Jindal, Mohak Chadha +1
Serverless computing paradigm has become more ingrained into the industry, as it offers a cheap alternative for application development and deployment. This new paradigm has also c…
Scalable Infrastructure for Workload Characterization of Cluster Traces
Thomas van Loo, Anshul Jindal, Shajulin Benedict +2
In the recent past, characterizing workloads has been attempted to gain a foothold in the emerging serverless cloud market, especially in the large production cloud clusters of Goo…
Estimating the Capacities of Function-as-a-Service Functions
Anshul Jindal, Mohak Chadha, Shajulin Benedict +1
Serverless computing is a cloud computing paradigm that allows developers to focus exclusively on business logic as cloud service providers manage resource management tasks. Server…
Towards Demystifying Intra-Function Parallelism in Serverless Computing
Michael Kiener, Mohak Chadha, Michael Gerndt
Serverless computing offers a pay-per-use model with high elasticity and automatic scaling for a wide range of applications. Since cloud providers abstract most of the underlying i…
FedLess: Secure and Scalable Federated Learning Using Serverless Computing
Andreas Grafberger, Mohak Chadha, Anshul Jindal +2
The traditional cloud-centric approach for Deep Learning (DL) requires training data to be collected and processed at a central server which is often challenging in privacy-sensiti…
DeepEdgeBench: Benchmarking Deep Neural Networks on Edge Devices
Stephan Patrick Baller, Anshul Jindal, Mohak Chadha +1
EdgeAI (Edge computing based Artificial Intelligence) has been most actively researched for the last few years to handle variety of massively distributed AI applications to meet up…
Architecture-Specific Performance Optimization of Compute-Intensive FaaS Functions
Mohak Chadha, Anshul Jindal, Michael Gerndt
FaaS allows an application to be decomposed into functions that are executed on a FaaS platform. The FaaS platform is responsible for the resource provisioning of the functions. Re…
Modelling DVFS and UFS for Region-Based Energy Aware Tuning of HPC Applications
Mohak Chadha, Michael Gerndt
Energy efficiency and energy conservation are one of the most crucial constraints for meeting the 20MW power envelope desired for exascale systems. Towards this, most of the resear…
Function Delivery Network: Extending Serverless Computing for Heterogeneous Platforms
Anshul Jindal, Michael Gerndt, Mohak Chadha +2
Serverless computing has rapidly grown following the launch of Amazon's Lambda platform. Function-as-a-Service (FaaS) a key enabler of serverless computing allows an application to…
Extending SLURM for Dynamic Resource-Aware Adaptive Batch Scheduling
Mohak Chadha, Jophin John, Michael Gerndt
With the growing constraints on power budget and increasing hardware failure rates, the operation of future exascale systems faces several challenges. Towards this, resource awaren…