Publications associées à Multitâche préemptif

Channel-Aware 5G RAN Slicing with Customizable Schedulers

This paper focuses on 5G RAN slicing, where the 5G radio resources must be divided across slices (or enterprises) so as to achieve high spectrum efficiency, fairness and isolation across slices, and the ability for each slice to customize how the radio res ...

USENIX ASSOC2023

Content Based Status Updates

Emre Telatar, Elie Najm, Rajai Nasser

Consider a stream of status updates generated by a source, where each update is of one of two types: high priority or ordinary (low priority). These updates are to be transmitted through a network to a monitor. However, the transmission policy of each pack ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Task scheduling for highly concurrent analytical and transaction workloads

Anastasia Ailamaki, Iraklis Psaroudakis

Systems and method for a task scheduler with dynamic adjustment of concurrency levels and task granularity are disclosed for improved execution of highly concurrent analytical and transactional systems. The task scheduler can avoid both over commitment and ...

2020

Improving Main-memory Database System Performance through Cooperative Multitasking

Georgios Psaropoulos

Database systems access memory either sequentially or randomly. Contrary to sequential access and despite the extensive efforts of computer architects, compiler writers, and system builders, random access to data larger than the processor cache has been s ...

EPFL2019

Exploiting Flow Graph of System of ODEs to Accelerate the Simulation of Biologically-Detailed Neural Networks

Felix Schürmann, Michael Lee Hines, Bruno Ricardo Da Cunha Magalhães

Exposing parallelism in scientific applications has become a core requirement for efficiently running on modern distributed multicore SIMD compute architectures. The granularity of parallelism that can be attained is a key determinant for the achievable ac ...

IEEE2019

A Regularization Framework for Learning Over Multitask Graphs

Ali H. Sayed, Stefan Vlaski, Roula Nassif

This letter proposes a general regularization framework for inference over multitask networks. The optimization approach relies on minimizing a global cost consisting of the aggregate sum of individual costs regularized by a term that allows to incorporate ...

IEEE Institute of Electrical and Electronics Engineers2019

dhSegment: A generic deep-learning approach for document segmentation

Frédéric Kaplan, Sofia Ares Oliveira, Benoît Laurent Auguste Seguin

In recent years there have been multiple successful attempts tackling document processing problems separately by designing task specific hand-tuned strategies. We argue that the diversity of historical document processing tasks prohibits to solve them one ...

IEEE2018

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

Reliability Mechanisms for Controllers in Real-Time Cyber-Physical Systems

Maaz Mashood Mohiuddin

Cyber-physical systems (CPSs) are real-world processes that are controlled by computer algorithms. We consider CPSs where a centralized, software-based controller maintains the process in a desired state by exchanging measurements and setpoints with proces ...

EPFL2018

A Scalable and Secure System Architecture for Smart Buildings

Georgios Lilis

Recent years has seen profound changes in building technologies both in Europe and worldwide. With the emergence of Smart Grid and Smart City concepts, the Smart Building has attracted considerable attention and rapid development. The introduction of novel ...

EPFL2017