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Scale-out non-uniform memory access

Related publications (32)

In-Memory Hardware and Architectural Extensions for Workloads Acceleration

Utilization of edge devices has exploded in the last decade, with such use cases as wearable devices, autonomous driving, and smart homes. As their ubiquity grows, so do expectations of their capabilities. Simultaneously, their formfactor and use cases lim ...

EPFL2022

Error Resilient In-Memory Computing Architecture for CNN Inference on the Edge

David Atienza Alonso, Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Flavio Ponzina, Marco Antonio Rios

The growing popularity of edge computing has fostered the development of diverse solutions to support Artificial Intelligence (AI) in energy-constrained devices. Nonetheless, comparatively few efforts have focused on the resiliency exhibited by AI workload ...

2022

VWR2A: A Very-Wide-Register Reconfigurable-Array Architecture for Low-Power Embedded Devices

David Atienza Alonso, Benoît Walter Denkinger, Miguel Peon Quiros

Edge-computing requires high-performance energy-efficient embedded systems. Fixed-function or custom accelerators, such as FFT or FIR filter engines, are very efficient at implementing a particular functionality for a given set of constraints. However, the ...

ASSOC COMPUTING MACHINERY2022

A Low-Complexity LoRa Synchronization Algorithm Robust to Sampling Time Offsets

Orion Afisiadis, Mathieu Pierre Xhonneux

LoRaWAN is nowadays one of the most popular protocols for low-power Internet of Things communications. Although its physical layer, namely LoRa, has been thoroughly studied in the literature, aspects related to the synchronization of LoRa receivers have re ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Adaptive table placement in NUMA architectures

Anastasia Ailamaki, Iraklis Psaroudakis

Techniques and solutions are provided for performing adaptive database table placement in a non-uniform memory access (NUMA) architecture. The adaptive table placement can occur in response to changing workloads on the NUMA nodes. For example, if a particu ...

2022

Performance Estimation of High-Level Dataflow Program on Heterogeneous Platforms

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

The performance of programs written in languages following the dataflow model of computation (MoC) largely depends on the configuration (partitioning, mapping, scheduling, buffer dimensioning) chosen during the synthesis stages. Furthermore, this programmi ...

2022

DFAulted: Analyzing and Exploiting CPU Software Faults Caused by FPGA-Driven Undervolting Attacks

Mirjana Stojilovic, David Dervishi, Dina Gamaleldin Ahmed Shawky Mahmoud

Field-programmable gate arrays (FPGAs) combine hardware reconfigurability with a high degree of parallelism. Consequently, FPGAs offer performance gains and power savings for many applications. A recent trend has been to leverage the hardware versatility o ...

2022

Toward Mobile Distributed Ledgers

Boi Faltings, Sujit Prakash Gujar, Dimitrios Chatzopoulos, Anurag Jain

Advances in mobile computing have paved the way for new types of distributed applications that can be executed solely by mobile devices on Device-to-Device (D2D) ecosystems (e.g., crowdsensing). Sophisticated applications, like cryptocurrencies, need distr ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Differentiated consistency for worldwide gossips

Davide Frey, Pierre-Louis Blaise Roman

Eventual consistency is a consistency model that favors liveness over safety. It is often used in large-scale distributed systems where models ensuring a stronger safety incur performance that are too low to be deemed practical. Eventual consistency tends ...

2022

Efficient protocols for oblivious linear function evaluation from ring-LWE

Juan Ramón Troncoso-Pastoriza

An oblivious linear function evaluation protocol, or OLE, is a two-party protocol for the function f (x) = ax + b, where a sender inputs the field elements a, b, and a receiver inputs x and learns f (x). OLE can be used to build secret-shared multiplicatio ...

IOS PRESS2022

System Support for Robust Distributed Learning

Arsany Hany Abdelmessih Guirguis

Machine learning (ML) applications are ubiquitous. They run in different environments such as datacenters, the cloud, and even on edge devices. Despite where they run, distributing ML training seems the only way to attain scalable, high-quality learning. B ...

EPFL2022

Miss-Optimized Memory Systems: Turning Thousands of Outstanding Misses into Reuse Opportunities

Mikhail Asiatici

Even if Dennard scaling came to an end fifteen years ago, Moore' s law kept fueling an exponential growth in compute performance through increased parallelization. However, the performance of memory and, in particular, Dynamic Random Access Memory (DRAM), ...

EPFL2021