Publications associées à Baie (centre de données)

Is the powersave governor really saving power?

David Atienza Alonso, Luis Maria Costero Valero, Darong Huang

A frequency scaling governor is critical for the performance management of cloud servers, as it enhances energy efficiency and helps to control operational temperatures, thereby ensuring system reliability. However, our in-depth analysis of the application ...

2024

Genuinely distributed Byzantine machine learning

Rachid Guerraoui, El Mahdi El Mhamdi, Le Nguyen Hoang, Sébastien Louis Alexandre Rouault, Arsany Hany Abdelmessih Guirguis

Machine learning (ML) solutions are nowadays distributed, according to the so-called server/worker architecture. One server holds the model parameters while several workers train the model. Clearly, such architecture is prone to various types of component ...

2022

LENA: Communication-Efficient Distributed Learning with Self-Triggered Gradient Uploads

Martin Jaggi, Sebastian Urban Stich, Hossein Shokri Ghadikolaei

In distributed optimization, parameter updates from the gradient computing node devices have to be aggregated in every iteration on the orchestrating server. When these updates are sent over an arbitrary commodity network, bandwidth and latency can be limi ...

MICROTOME PUBLISHING2021

Genuinely Distributed Byzantine Machine Learning

Rachid Guerraoui, El Mahdi El Mhamdi, Le Nguyen Hoang, Sébastien Louis Alexandre Rouault, Arsany Hany Abdelmessih Guirguis

Machine Learning (ML) solutions are nowadays distributed, according to the so-called server/worker architecture. One server holds the model parameters while several workers train the model. Clearly, such architecture is prone to various types of component ...

Association for Computing Machinery2020

Functionality Enhanced Memories for Edge-AI Embedded Systems

David Atienza Alonso, Alexandre Sébastien Julien Levisse, Pierre-Emmanuel Julien Marc Gaillardon, Marco Antonio Rios, William Andrew Simon

With the surge in complexity of edge workloads, it appeared in the scientific community that such workloads cannot be anymore overflown to the cloud due to the huge edge device to server communication energy cost and the high energy consumption induced in ...

IEEE2019

Hardware-conscious Query Processing in GPU-accelerated Analytical Engines

Anastasia Ailamaki, Periklis Chrysogelos, Panagiotis Sioulas

In order to improve their power efficiency and computational capacity, modern servers are adopting hardware accelerators, especially GPUs. Modern analytical DMBS engines have been highly optimized for multi-core multi-CPU query execution, but lack the nece ...

2019

HetExchange: Encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines

Anastasia Ailamaki, Periklis Chrysogelos, Manolis Karpathiotakis, Raja Appuswamy

Modern server hardware is increasingly heterogeneous as hardware accelerators, such as GPUs, are used together with multicore CPUs to meet the computational demands of modern data analytics workloads. Unfortunately, query parallelization techniques used by ...

2019

The mean-field behavior of processor sharing systems with general job lengths under the SQ(d) policy

Arpan Mukhopadhyay

This paper addresses the mean-field behavior of large-scale systems of parallel servers with a processor sharing service discipline when arrivals are Poisson and jobs have general service time distributions when an SQ(d) routing policy is used. Under this ...

ELSEVIER SCIENCE BV2018

Increasing Availability in Distributed Storage Systems via Clustering

Michael Christoph Gastpar, Saeid Sahraei

We introduce the Fixed Cluster Repair System (FCRS) as a novel architecture for Distributed Storage Systems (DSS) that achieves a small repair bandwidth while guaranteeing a high availability. Specifically, we partition the set of servers in a DSS into s c ...

2018

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Baie (centre de données)

Is the powersave governor really saving power?

Genuinely distributed Byzantine machine learning

LENA: Communication-Efficient Distributed Learning with Self-Triggered Gradient Uploads

Genuinely Distributed Byzantine Machine Learning

Functionality Enhanced Memories for Edge-AI Embedded Systems

Hardware-conscious Query Processing in GPU-accelerated Analytical Engines

HetExchange: Encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines

Network-Compute Co-Design for Distributed In-Memory Computing

The mean-field behavior of processor sharing systems with general job lengths under the SQ(d) policy

Increasing Availability in Distributed Storage Systems via Clustering

Graph Chatbot

Chattez avec Graph Search

Hardware-conscious Query Processing in GPU-accelerated Analytical Engines

Functionality Enhanced Memories for Edge-AI Embedded Systems

Network-Compute Co-Design for Distributed In-Memory Computing

HetExchange: Encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines

Increasing Availability in Distributed Storage Systems via Clustering

The mean-field behavior of processor sharing systems with general job lengths under the SQ(d) policy

Genuinely distributed Byzantine machine learning

Genuinely Distributed Byzantine Machine Learning

Is the powersave governor really saving power?

LENA: Communication-Efficient Distributed Learning with Self-Triggered Gradient Uploads