A survey of bit-flip attacks on deep neural network and corresponding defense methods

C Qian, M Zhang, Y Nie, S Lu, H Cao - Electronics, 2023‏ - mdpi.com
As the machine learning-related technology has made great progress in recent years, deep
neural networks are widely used in many scenarios, including security-critical ones, which …

The gem5 simulator: Version 20.0+

J Lowe-Power, AM Ahmad, A Akram, M Alian… - arxiv preprint arxiv …, 2020‏ - arxiv.org
The open-source and community-supported gem5 simulator is one of the most popular tools
for computer architecture research. This simulation infrastructure allows researchers to …

Archgym: An open-source gymnasium for machine learning assisted architecture design

S Krishnan, A Yazdanbakhsh, S Prakash… - Proceedings of the 50th …, 2023‏ - dl.acm.org
Machine learning (ML) has become a prevalent approach to tame the complexity of design
space exploration for domain-specific architectures. While appealing, using ML for design …

Distilling bit-level sparsity parallelism for general purpose deep learning acceleration

H Lu, L Chang, C Li, Z Zhu, S Lu, Y Liu… - MICRO-54: 54th Annual …, 2021‏ - dl.acm.org
Along with the rapid evolution of deep neural networks, the ever-increasing complexity
imposes formidable computation intensity to the hardware accelerator. In this paper, we …

System simulation with gem5 and SystemC: The keystone for full interoperability

C Menard, J Castrillon, M Jung… - … on Embedded Computer …, 2017‏ - ieeexplore.ieee.org
SystemC TLM based virtual prototypes have become the main tool in industry and research
for concurrent hardware and software development, as well as hardware design space …

DRAMSys4. 0: a fast and cycle-accurate systemC/TLM-based DRAM simulator

L Steiner, M Jung, FS Prado, K Bykov… - … , Modeling, and Simulation …, 2020‏ - Springer
Abstract The simulation of DRAMs (Dynamic Random Access Memories) on system level
requires highly accurate models due to their complex timing and power behavior. However …

Sparse stream semantic registers: A lightweight ISA extension accelerating general sparse linear algebra

P Scheffler, F Zaruba, F Schuiki… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
Sparse linear algebra is crucial in many application domains, but challenging to handle
efficiently in both software and hardware, with one-and two-sided operand sparsity handled …

RTSim: A cycle-accurate simulator for racetrack memories

AA Khan, F Hameed, R Bläsing… - IEEE Computer …, 2019‏ - ieeexplore.ieee.org
Racetrack memories (RTMs) have drawn considerable attention from computer architects of
late. Owing to the ultra-high capacity and comparable access latency to SRAM, RTMs are …

Approximate computing with partially unreliable dynamic random access memory-approximate DRAM

M Jung, DM Mathew, C Weis, N Wehn - Proceedings of the 53rd Annual …, 2016‏ - dl.acm.org
In the context of approximate computing, Approximate Dynamic Random Access Memory
(ADRAM) enables the tradeoff between energy efficiency, performance and reliability. The …

Omitting refresh: A case study for commodity and wide i/o drams

M Jung, É Zulian, DM Mathew, M Herrmann… - Proceedings of the …, 2015‏ - dl.acm.org
Dynamic Random Access Memories (DRAM) have a big impact on performance and
contribute significantly to the total power consumption in systems ranging from mobile …