Amazon Web Services

By R. Das, P. de Guise. 2019

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In ML Systems & Hardware

Citations in the corpus

Measuring the Carbon Intensity of AI in Cloud Instances (2022, background): “…of the compute regions themselves, with several server locations partially powered by renewable energy sources such as solar and wind [12, 29, 40] and giving users the necessary tools to pick compute regions with a smaller carbon footprint [13, 17], which are often tied to the amount of…”
Quantifying the Carbon Emissions of Machine Learning (2019, background): “Finally, to the best of our knowledge, while not yet 100% carbon neutral on an organizational level, Amazon Web Services is also funding renewable energy projects and some of their data centers are powered by renewable energy [15].”
Faasm: Lightweight Isolation for Efficient Stateful Serverless Computing (2020, background): “Existing serverless platforms such as Google Cloud Functions [27], IBM Cloud Functions [33], Azure Functions [44] and AWS Lambda [5] isolate functions in ephemeral, stateless containers .”
Outracing champion Gran Turismo drivers with deep reinforcement learning (2022, unknown): “Research on autonomous racing has accelerated in recent years, leveraging full-sized 7–10 , scale 11–15 and simulated 16–25 vehicles.”
A Survey on Distributed Machine Learning (2019, methodology): “The service includes support for TensorFlow, MXNet, and Spark [7].”
Orbital Edge Computing: Nanosatellite Constellations as a New Class of Computer System (2020, background): “The SpaceNet challenge [94] illustrates broad interest in visual computing on space data, and the proposed Amazon ground station network [2] further cements the value of computing on visual and other space sensor data.”
Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming (2023, unknown): “Currently, these models power AI Coding Assis-tants including Github Copilot [31], CodeWhisperer [2] Tabnine [85] that provide code-completion functionality.”
Machine Learning With Big Data: Challenges and Approaches (2017, background): “In addition to these two categories, it is important to note several machine learning as a service offerings: Microsoft Azure Machine Learning, now part of Cortana Intelligence Suite [69]; Google Cloud Machine Learning Platform [70]; Amazon Machine Learning [71]; and IBM Watson Analytics [72].”
Edge server placement in mobile edge computing (2019, background): “An effective approach to enhancing the performance of mobile applications is to offload some of their tasks to remote resource-rich clouds [4],[5],[6],[7].”
My VM is Lighter (and Safer) than your Container (2017, background): “…is reported to run all of its services in containers [4], and Container as a Service (CaaS) products are available from a number of major players including Azure’s Container Service [32], Amazon’s EC2 Container Service and Lambda offerings [1, 2], and Google’s Container Engine service [10].”
Quantum computing with Qiskit (2024, background): “Some of these tools are explicitly built around OpenQASM [18, 19, 45, 77], while others support serialization to and from it [17, 24, 33, 41, 48, 52, 83, 86, 88].”