A design flow for scheduling spiking deep convolutional neural networks on heterogeneous neuromorphic system-on-chip
A Das - ACM Transactions on Embedded Computing Systems, 2023 - dl.acm.org
Neuromorphic systems-on-chip (NSoCs) integrate CPU cores and neuromorphic hardware
accelerators on the same chip. These platforms can execute spiking deep convolutional …
accelerators on the same chip. These platforms can execute spiking deep convolutional …
Design space exploration for secure iot devices and cyber-physical systems
L Gressl, C Steger, U Neffe - ACM Transactions on Embedded …, 2021 - dl.acm.org
With the advent of the Internet of Things (IoT) and Cyber-Physical Systems (CPS),
embedded devices have been gaining importance in our daily lives, as well as industrial …
embedded devices have been gaining importance in our daily lives, as well as industrial …
Nlp-fast: a fast, scalable, and flexible system to accelerate large-scale heterogeneous nlp models
Emerging natural language processing (NLP) models have become more complex and
bigger to provide more sophisticated NLP services. Accordingly, there is also a strong …
bigger to provide more sophisticated NLP services. Accordingly, there is also a strong …
Real-time scheduling of machine learning operations on heterogeneous neuromorphic SoC
A Das - 2022 20th ACM-IEEE International Conference on …, 2022 - ieeexplore.ieee.org
Neuromorphic Systems-on-Chip (NSoCs) are becoming heterogeneous by integrating
general-purpose processors (GPPs) and neural processing units (NPUs) on the same SoC …
general-purpose processors (GPPs) and neural processing units (NPUs) on the same SoC …
SAFEPOWER project: Architecture for safe and power-efficient mixed-criticality systems
M Fakih, A Lenz, M Azkarate-Askasua, J Coronel… - Microprocessors and …, 2017 - Elsevier
With the ever increasing industrial demand for bigger, faster and more efficient systems, a
growing number of cores is integrated on a single chip. Additionally, their performance is …
growing number of cores is integrated on a single chip. Additionally, their performance is …
ForSyDe: System design using a functional language and models of computation
The ForSyDe methodology aims to push system design to a higher level of abstraction by
combining the functional programming paradigm with the theory of Models of Computation …
combining the functional programming paradigm with the theory of Models of Computation …
Building IoT systems using distributed first-class reactive programming
C De Troyer, J Nicolay… - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
Contemporary IoT systems are challenging to develop, deploy, and maintain. This is
because of their ever-increasing scale, dynamic network topologies, heterogeneity and …
because of their ever-increasing scale, dynamic network topologies, heterogeneity and …
CONTREX: Design of embedded mixed-criticality CONTRol systems under consideration of EXtra-functional properties
K Grüttner, R Görgen, S Schreiner, F Herrera… - Microprocessors and …, 2017 - Elsevier
The increasing processing power of today's HW/SW platforms leads to the integration of
more and more functions in a single device. Additional design challenges arise when these …
more and more functions in a single device. Additional design challenges arise when these …
Flexible and tradeoff-aware constraint-based design space exploration for streaming applications on heterogeneous platforms
Due to its complexity, the problem of mapping and scheduling streaming applications on
heterogeneous MPSoCs under real-time and performance constraints has traditionally been …
heterogeneous MPSoCs under real-time and performance constraints has traditionally been …
Towards Synthetic Trace Generation of Modeling Operations using In-Context Learning Approach
Producing accurate software models is crucial in model-driven software engineering (MDE).
However, modeling complex systems is an error-prone task that requires deep application …
However, modeling complex systems is an error-prone task that requires deep application …