[HTML][HTML] A comprehensive survey of industry practice in real-time systems
This paper presents results and observations from a survey of 120 industry practitioners in
the field of real-time embedded systems. The survey provides insights into the …
the field of real-time embedded systems. The survey provides insights into the …
[HTML][HTML] Bio-inspired computation for big data fusion, storage, processing, learning and visualization: state of the art and future directions
This overview gravitates on research achievements that have recently emerged from the
confluence between Big Data technologies and bio-inspired computation. A manifold of …
confluence between Big Data technologies and bio-inspired computation. A manifold of …
An empirical survey-based study into industry practice in real-time systems
This paper presents results and observations from a survey of 120 industry practitioners in
the field of real-time embedded systems. The survey provides insights into the …
the field of real-time embedded systems. The survey provides insights into the …
[HTML][HTML] CPS-based smart warehouse for industry 4.0: A survey of the underlying technologies
This paper discusses how the state-of-the-art techniques in cyber-physical systems facilitate
building smart warehouses to achieve the promising vision of industry 4.0. We focus on four …
building smart warehouses to achieve the promising vision of industry 4.0. We focus on four …
[PDF][PDF] Vicuna: A timing-predictable RISC-V vector coprocessor for scalable parallel computation
M Platzer, P Puschner - 33rd euromicro conference on real-time …, 2021 - drops.dagstuhl.de
In this work, we present Vicuna, a timing-predictable vector coprocessor. A vector processor
can be scaled to satisfy the performance requirements of massively parallel computation …
can be scaled to satisfy the performance requirements of massively parallel computation …
Security-aware task scheduling with deadline constraints on heterogeneous hybrid clouds
Hybrid cloud is a cost-effective way to address the problem of insufficient resources for
satisfying its users' requirements in a private cloud by elastically scaling up or down its …
satisfying its users' requirements in a private cloud by elastically scaling up or down its …
Neural network-based performance prediction for task migration on s-nuca many-cores
The performance of a task running on a many-core with distributed shared last-level cache
(LLC) strongly depends on two parameters: the power budget needed to guarantee …
(LLC) strongly depends on two parameters: the power budget needed to guarantee …
iHPSA: An improved bio-inspired hybrid optimization algorithm for task mapping in Network on Chip
Abstract System on a chip (SoC) is the leading technology in the recent global world of
digitization. The classical bus-based regular communication infrastructures of SoCs cannot …
digitization. The classical bus-based regular communication infrastructures of SoCs cannot …
Energy-efficient run-time mapping and thread partitioning of concurrent OpenCL applications on CPU-GPU MPSoCs
Heterogeneous Multi-Processor Systems-on-Chips (MPSoCs) containing CPU and GPU
cores are typically required to execute applications concurrently. However, as will be shown …
cores are typically required to execute applications concurrently. However, as will be shown …
Socodecnn: Program source code for visual cnn classification using computer vision methodology
Automated feature extraction from program source-code such that proper computing
resources could be allocated to the program is very difficult given the current state of …
resources could be allocated to the program is very difficult given the current state of …