Publications associées à Earliest deadline first scheduling

OASIS: An integrated optimisation framework for activity scheduling

Activity-based models offer the potential for a far deeper understanding of daily mobility behaviour than trip-based models. Based on the fundamental assumption that travel demand is derived from the need to do activities, they are flexible tools that aim ...

EPFL2024

Channel-Aware 5G RAN Slicing with Customizable Schedulers

Haitham Al Hassanieh

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

Simulating intra-household interactions for in- and out-of-home activity scheduling

Michel Bierlaire, Timothy Michael Hillel, Negar Rezvany

Various interactions, time arrangements, and constraints exist for individuals scheduling their day as a member of a household, which affect their in-home as well as out-of-home activity schedule. However, the existing activity-based models are mostly base ...

Pergamon-Elsevier Science Ltd2023

Chaosity: Understanding Contemporary NUMA-architectures

Anastasia Ailamaki, Viktor Sanca, Syed Mohammad Aunn Raza, Hamish Mcniece Hill Nicholson, Andreea Nica

Modern hardware is increasingly complex, requiring increasing effort to understand in order to carefully engineer systems for optimal performance and effective utilization. Moreover, established design principles and assumptions are not portable to modern ...

2023

Analysis of Dampers in Time-Sensitive Networks With Non-Ideal Clocks

Jean-Yves Le Boudec, Ehsan Mohammadpour

Dampers are devices that reduce delay jitter in the context of time-sensitive networks, by delaying packets for the amount written in packet headers. Jitter reduction is required by some real-time applications; beyond this, dampers have the potential to so ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

DASS: Combining Dynamic & Static Scheduling in High-Level Synthesis

Paolo Ienne, Lana Josipovic

A central task in high-level synthesis is scheduling: the allocation of operations to clock cycles. The classic approach to scheduling is static, in which each operation is mapped to a clock cycle at compile-time, but recent years have seen the emergence o ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

From C/C plus plus Code to High-Performance Dataflow Circuits

Paolo Ienne, Andrea Guerrieri, Lana Josipovic

High-level synthesis (HLS) tools typically generate statically scheduled datapaths. Static scheduling implies that the resulting circuits have a hard time exploiting parallelism in code with potential memory dependences, with control dependences, or where ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Equinox: Training (for Free) on a Custom Inference Accelerator

Babak Falsafi, Martin Jaggi, Ahmet Caner Yüzügüler, Louis Coulon, Mario Paulo Drumond Lages De Oliveira, Arash Pourhabibi Zarandi

DNN inference accelerators executing online services exhibit low average loads because of service demand variability, leading to poor resource utilization. Unfortunately, reclaiming idle inference cycles is difficult as other workloads can not execute on a ...

ACM2021

When to Hedge in Interactive Services

Edouard Bugnion, Aikaterini Argyraki, 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 ...

USENIX ASSOC2021

Combining Dynamic & Static Scheduling in High-level Synthesis

Paolo Ienne, Lana Josipovic

A central task in high-level synthesis is scheduling: the allocation of operations to clock cycles. The classic approach to scheduling is static, in which each operation is mapped to a clock cycle at compile-time, but recent years have seen the emergence o ...

ASSOC COMPUTING MACHINERY2020