Concept

Amazon Web Services

Publications associées (33)

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Modern data center fabrics open the possibility of microsecond distributed applications, such as data stores and message queues. A challenging aspect of their development is to ensure that, besides being fast in the common case, these applications react fa ...

USENIX Association2023

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Cloud function (CF) services, such as AWS Lambda, have been applied as the new computing infrastructure in implementing analytical query engines. For bursty and sparse workloads, CF-based query engine is more elastic than the traditional query engines runn ...

ACM2023

When to Hedge in Interactive Services

Edouard Bugnion, Mia Primorac

In online data-intensive (OLDI) services, each client request typically executes on multiple servers in parallel; as a result, “system hiccups”, although rare within a single server, can interfere with many client requests and cause violations of service-l ...

USENIX2021

Hybrid, Job-Aware, and Preemptive Datacenter Scheduling

Pamela Isabel Delgado Borda

Scheduling in datacenters is an important, yet challenging problem. Datacenters are composed of a large number, typically tens of thousands, of commodity computers running a variety of data-parallel jobs. The role of the scheduler is to assign cluster reso ...

EPFL2018

The rise of web-scale services has led to a staggering growth in user data on the Internet. To transform such a vast raw data into valuable information for the user and provide quality assurances, it is important to minimize access latency and enable in-me ...

EPFL2017

In cloud storage systems, hot data is usually replicated over multiple disks/servers in order to accommodate simultaneous access by multiple users as well as increase the fault tolerance of the system. Recent cloud storage research has proposed using avail ...

2017

Towards Real-Time High-Resolution Interferometric Imaging with Bluebild

Sepand Kashani

Rooted in radio-astronomy, the Bluebild algorithm is a paradigm-changing imager to estimate the sky intensity function. However, current imaging pipelines in radio-astronomy are highly-tailored to the CLEAN-family of imagers, and hence lack the flexibility ...

2017

Stealing Machine Learning Models via Prediction APIs

Florian Tramèr, Fan Zhang, Ari Juels

Machine learning (ML) models may be deemed confidential due to their sensitive training data, commercial value, or use in security applications. Increasingly often, confidential ML models are being deployed with publicly accessible query interfaces. ML-as- ...

Usenix Assoc2016

Near-Memory Data Services

Babak Falsafi

This column introduces seven invited position papers about the challenges and opportunities in near-data processing. "Near-Memory Data Services" by Babak Falsafi, "Automata Processing: The Memory Is the Processor!" by Mircea Stan, Kevin Skadron, "Overcomin ...

Institute of Electrical and Electronics Engineers2016

Frugal Topology Construction for Stream Aggregation in the Cloud

Rachid Guerraoui, Rhicheek Patra, Bao Duy Tran

Aggregation of streamed data is key to the expansion of the Internet of Things. This paper addresses the problem of designing a topology for reliably aggregating data flows from many devices arriving at a datacenter. Reliability here means ensuring operati ...

Ieee2016

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