Zobrazeno 1 - 10
of 262
pro vyhledávání: '"Zervas, Georgios"'
Publikováno v:
OFC'23: Proceedings of the Optical Fiber Communications Conference and Exhibition, 2023
We propose a new algorithm for generating custom network traffic matrices which achieves 13x, 38x, and 70x faster generation times than prior work on networks with 64, 256, and 1024 nodes respectively.
Comment: Accepted to OFC'23: Proceedings of
Comment: Accepted to OFC'23: Proceedings of
Externí odkaz:
http://arxiv.org/abs/2302.09970
From natural language processing to genome sequencing, large-scale machine learning models are bringing advances to a broad range of fields. Many of these models are too large to be trained on a single machine, and instead must be distributed across
Externí odkaz:
http://arxiv.org/abs/2301.13799
Distributed deep learning (DDL) systems strongly depend on network performance. Current electronic packet switched (EPS) network architectures and technologies suffer from variable diameter topologies, low-bisection bandwidth and over-subscription af
Externí odkaz:
http://arxiv.org/abs/2211.15226
Autor:
Shabka, Zacharaya, Zervas, Georgios
Resource-disaggregated data centre architectures promise a means of pooling resources remotely within data centres, allowing for both more flexibility and resource efficiency underlying the increasingly important infrastructure-as-a-service business.
Externí odkaz:
http://arxiv.org/abs/2211.02466
Proportional-integral-derivative (PID) control underlies more than $97\%$ of automated industrial processes. Controlling these processes effectively with respect to some specified set of performance goals requires finding an optimal set of PID parame
Externí odkaz:
http://arxiv.org/abs/2210.13906
We discuss estimation of the differentiated products demand system of Berry et al (1995) (BLP) by maximum likelihood estimation (MLE). We derive the maximum likelihood estimator in the case where prices are endogenously generated by firms that set pr
Externí odkaz:
http://arxiv.org/abs/2111.12397
Publikováno v:
Volume 46, 2022, 100695, ISSN 1573-4277
Benchmarking is commonly used in research fields, such as computer architecture design and machine learning, as a powerful paradigm for rigorously assessing, comparing, and developing novel technologies. However, the data centre networking community
Externí odkaz:
http://arxiv.org/abs/2107.01398
Autor:
Shabka, Zacharaya, Zervas, Georgios
Resource-disaggregated data centres (RDDC) propose a resource-centric, and high-utilisation architecture for data centres (DC), avoiding resource fragmentation and enabling arbitrarily sized resource pools to be allocated to tasks, rather than server
Externí odkaz:
http://arxiv.org/abs/2106.02412
Publikováno v:
In Optical Switching and Networking February 2024 51