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Big data analytics for intelligent manufacturing systems: A review
With the development of Internet of Things (IoT), 5 G, and cloud computing technologies, the
amount of data from manufacturing systems has been increasing rapidly. With massive …
amount of data from manufacturing systems has been increasing rapidly. With massive …
A survey on distributed machine learning
J Verbraeken, M Wolting, J Katzy… - Acm computing surveys …, 2020 - dl.acm.org
The demand for artificial intelligence has grown significantly over the past decade, and this
growth has been fueled by advances in machine learning techniques and the ability to …
growth has been fueled by advances in machine learning techniques and the ability to …
Splitwise: Efficient generative llm inference using phase splitting
Generative large language model (LLM) applications are growing rapidly, leading to large-
scale deployments of expensive and power-hungry GPUs. Our characterization of LLM …
scale deployments of expensive and power-hungry GPUs. Our characterization of LLM …
On the opportunities and risks of foundation models
AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
Characterizing microservice dependency and performance: Alibaba trace analysis
Loosely-coupled and light-weight microservices running in containers are replacing
monolithic applications gradually. Understanding the characteristics of microservices is …
monolithic applications gradually. Understanding the characteristics of microservices is …
[HTML][HTML] Machine learning in python: Main developments and technology trends in data science, machine learning, and artificial intelligence
Smarter applications are making better use of the insights gleaned from data, having an
impact on every industry and research discipline. At the core of this revolution lies the tools …
impact on every industry and research discipline. At the core of this revolution lies the tools …
{SkyPilot}: An intercloud broker for sky computing
To comply with the increasing number of government regulations about data placement and
processing, and to protect themselves against major cloud outages, many users want the …
processing, and to protect themselves against major cloud outages, many users want the …
Personalized recommendation system based on collaborative filtering for IoT scenarios
Z Cui, X Xu, XUE Fei, X Cai, Y Cao… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Recommendation technology is an important part of the Internet of Things (IoT) services,
which can provide better service for users and help users get information anytime …
which can provide better service for users and help users get information anytime …
Big data analytics using cloud computing based frameworks for power management systems: Status, constraints, and future recommendations
Traditional parallel computing for power management systems has prime challenges such
as execution time, computational complexity, and efficiency like process time and delays in …
as execution time, computational complexity, and efficiency like process time and delays in …
Swift: Delay is simple and effective for congestion control in the datacenter
We report on experiences with Swift congestion control in Google datacenters. Swift targets
an end-to-end delay by using AIMD control, with pacing under extreme congestion. With …
an end-to-end delay by using AIMD control, with pacing under extreme congestion. With …