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pro vyhledávání: '"Gerndt, Michael"'
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 decentralized. Recent works on designing systems for efficient FL have
Externí odkaz:
http://arxiv.org/abs/2404.14033
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 decentralized. Recent works on designing systems for efficient FL have
Externí odkaz:
http://arxiv.org/abs/2402.07295
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 enables an application to be decomposed into fine-grained functions that
Externí odkaz:
http://arxiv.org/abs/2401.10367
Autor:
Chadha, Mohak, Subramanian, Thandayuthapani, Arima, Eishi, Gerndt, Michael, Schulz, Martin, Abboud, Osama
This paper presents GreenCourier, a novel scheduling framework that enables the runtime scheduling of serverless functions across geographically distributed regions based on their carbon efficiencies. Our framework incorporates an intelligent schedul
Externí odkaz:
http://arxiv.org/abs/2310.20375
Tackling climate change by reducing and eventually eliminating carbon emissions is a significant milestone on the path toward establishing an environmentally sustainable society. As we transition into the exascale era, marked by an increasing demand
Externí odkaz:
http://arxiv.org/abs/2309.13473
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 utilize GPUs in a coarse manner for DL inferences, without taking into
Externí odkaz:
http://arxiv.org/abs/2309.00558
Autor:
Chadha, Mohak, Krueger, Nils, John, Jophin, Jindal, Anshul, Gerndt, Michael, Benedict, Shajulin
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 format to package and distribute them. However, their adoption and us
Externí odkaz:
http://arxiv.org/abs/2301.03982
Autor:
Elzohairy, Mohamed, Chadha, Mohak, Jindal, Anshul, Grafberger, Andreas, Gu, Jianfeng, Gerndt, Michael, Abboud, Osama
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 most prior work on designing systems for FL has focused on using statefu
Externí odkaz:
http://arxiv.org/abs/2211.05739
Autor:
John, Jophin, Gerndt, Michael
Dynamic resource management opens up numerous opportunities in High Performance Computing. It improves the system-level services as well as application performance. Checkpointing can also be deemed as a system-level service and can reap the benefits
Externí odkaz:
http://arxiv.org/abs/2211.04305
Microservice architecture is the common choice for developing cloud applications these days since each individual microservice can be independently modified, replaced, and scaled. As a result, application development and operating cloud infrastructur
Externí odkaz:
http://arxiv.org/abs/2210.04212