Publications related to Magnetic-core memory

Magnon-Assisted Magnetization Reversal of Ni81Fe19 Nanostripes on Y3Fe5O12 with Different Interfaces

Dirk Grundler, Andrea Mucchietto, Korbinian Baumgärtl

Magnetic bit writing by short-wave magnons without conversion to the electrical domain is expected to be a game-changer for in-memory computing architectures. Recently, the reversal of nanomagnets by propagating magnons was demonstrated. However, experimen ...

2024

A 128-kbit GC-eDRAM With Negative Boosted Bootstrap Driver for 11.3x Lower-Refresh Frequency at a 2.5% Area Overhead in 28-nm FD-SOI

Andreas Peter Burg, Robert Giterman, Halil Andac Yigit, Emmanuel Nieto Casarrubias

Gain-cell embedded DRAM (GC-eDRAM) is a high-density logic-compatible alternative to conventional static random-access memory (SRAM) and embedded DRAM (eDRAM). However, GC-eDRAM suffers from a reduced data retention time (DRT) at deeply-scaled process node ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Bit-Line Computing for CNN Accelerators Co-Design in Edge AI Inference

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

By supporting the access of multiple memory words at the same time, Bit-line Computing (BC) architectures allow the parallel execution of bit-wise operations in-memory. At the array periphery, arithmetic operations are then derived with little additional o ...

2023

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

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

Anastasia Ailamaki, Syed Mohammad Aunn Raza, Hamish Mcniece Hill Nicholson, Periklis Chrysogelos

Accessing input data is a critical operation in data analytics: i) slow data access significantly degrades performance, and ii) storing everything in the fastest medium, i.e., memory, incurs high operational and hardware costs. Further, while GPUs offer in ...

2023

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

Sabine Süsstrunk, Mathieu Salzmann, Yulun Jiang, Chen Liu, Zhuoyi Huang

We address the problem of stably and efficiently training a deep neural network robust to adversarial perturbations bounded by an

l_1

norm. We demonstrate that achieving robustness against

l_1

-bounded perturbations is more challenging than in the

l_2

...

2023

STEPS 4.0: Fast and memory-efficient molecular simulations of neurons at the nanoscale

James Gonzalo King, Pramod Shivaji Kumbhar, Omar Awile, Christos Kotsalos, Iain Hepburn, Weiliang Chen, Tristan Mathieu Carel, Samuel Marie A Melchior, Baudouin Paul Michel Maria Joseph Del Marmol, Alessandro Cattabiani, Giacomo Castiglioni, Nicola Cantarutti

Recent advances in computational neuroscience have demonstrated the usefulness and importance of stochastic, spatial reaction-diffusion simulations. However, ever increasing model complexity renders traditional serial solvers, as well as naive parallel imp ...

FRONTIERS MEDIA SA2022

In-Memory Hardware and Architectural Extensions for Workloads Acceleration

William Andrew Simon

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

AstriFlash: A Flash-Based System for Online Services

Babak Falsafi, Lei Yan, Siddharth Gupta, Mark Johnathon Sutherland, Yunho Oh

Modern datacenters host datasets in DRAM to offer large-scale online services with tight tail-latency requirements. Unfortunately, as DRAM is expensive and increasingly difficult to scale, datacenter operators are forced to consider denser storage technolo ...

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

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Magnon-Assisted Magnetization Reversal of Ni81Fe19 Nanostripes on Y3Fe5O12 with Different Interfaces

A 128-kbit GC-eDRAM With Negative Boosted Bootstrap Driver for 11.3x Lower-Refresh Frequency at a 2.5% Area Overhead in 28-nm FD-SOI

Bit-Line Computing for CNN Accelerators Co-Design in Edge AI Inference

Chaosity: Understanding Contemporary NUMA-architectures

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

STEPS 4.0: Fast and memory-efficient molecular simulations of neurons at the nanoscale

In-Memory Hardware and Architectural Extensions for Workloads Acceleration

AstriFlash: A Flash-Based System for Online Services

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

A 128-kbit GC-eDRAM With Negative Boosted Bootstrap Driver for 11.3x Lower-Refresh Frequency at a 2.5% Area Overhead in 28-nm FD-SOI

Chaosity: Understanding Contemporary NUMA-architectures

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

Magnon-Assisted Magnetization Reversal of Ni81Fe19 Nanostripes on Y3Fe5O12 with Different Interfaces

Bit-Line Computing for CNN Accelerators Co-Design in Edge AI Inference

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

STEPS 4.0: Fast and memory-efficient molecular simulations of neurons at the nanoscale

In-Memory Hardware and Architectural Extensions for Workloads Acceleration

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

AstriFlash: A Flash-Based System for Online Services