Related papers: A Survey of Embedded Software Profiling Methodolog…
The increasing complexity and the short life cycles of embedded systems are pushing the current system-on-chip designs towards a rapid increasing on the number of programmable processing units, while decreasing the gate count for custom…
Embedded system software is highly constrained from performance, memory footprint, energy consumption and implementing cost view point. It is always desirable to obtain better Instructions per Cycle. Instruction cache has major contribution…
Developing high performance embedded vision applications requires balancing run-time performance with energy constraints. Given the mix of hardware accelerators that exist for embedded computer vision (e.g. multi-core CPUs, GPUs, and…
The use of reconfigurable computing, and FPGAs in particular, to accelerate computational kernels has the potential to be of great benefit to scientific codes and the HPC community in general. However, whilst recent advanced in FPGA tooling…
The remarkable growth and significant success of machine learning have expanded its applications into programming languages and program analysis. However, a key challenge in adopting the latest machine learning methods is the representation…
Heterogeneous computing is one of the most important computational solutions to meet rapidly increasing demands on system performance. It typically allows the main flow of applications to be executed on a CPU while the most computationally…
In order to compare and benchmark the mathematical software, the performance profiles have been introduced [1]. However, it has been proved that the algorithm is not flawless. The main issue with the performance profile is that it may rank…
We introduce SysML-Sec, a SysML-based Model-Driven Engineering environment aimed at fostering the collaboration between system designers and security experts at all methodological stages of the development of an embedded system. A central…
Trends in hardware, the prevalence of the cloud, and the rise of highly demanding applications have ushered an era of specialization that quickly changes how data is processed at scale. These changes are likely to continue and accelerate in…
Automation engineering is the task of integrating, via software, various sensors, actuators, and controls for automating a real-world process. Today, automation engineering is supported by a suite of software tools including integrated…
Model Predictive Control (MPC) is a powerful and flexible design tool of high-performance controllers for physical systems in the presence of input and output constraints. A challenge for the practitioner applying MPC is the need of tuning…
Contemporary intelligent systems incorporate software components, including machine learning components. As they grow in complexity and data volume such machine learning systems face unique quality challenges like scalability and…
Computer vision applications constitute one of the key drivers for embedded multicore architectures. Although the number of available cores is increasing in new architectures, designing an application to maximize the utilization of the…
Many tools and libraries employ hardware performance monitoring (HPM) on modern processors, and using this data for performance assessment and as a starting point for code optimizations is very popular. However, such data is only useful if…
Modern cyber-physical systems (CPS) have a close inter-dependence between software and physical components. Automotive embedded systems are typical CPS, as physical chips, sensors and actuators are physical components and software embedded…
For several decades, the CPU has been the standard model to use in the majority of computing. While the CPU does excel in some areas, heterogeneous computing, such as reconfigurable hardware, is showing increasing potential in areas like…
There is growing interest in lowering the energy consumption of computation. Energy transparency is a concept that makes a program's energy consumption visible from software to hardware through the different system layers. Such transparency…
Due to decelerating gains in single-core CPU performance, computationally expensive simulations are increasingly executed on highly parallel hardware platforms. Agent-based simulations, where simulated entities act with a certain degree of…
Process mining offers techniques to exploit event data by providing insights and recommendations to improve business processes. The growing amount of algorithms for process discovery has raised the question of which algorithms perform best…
Cryptographic algorithms are computationally costly and the challenge is more if we need to execute them in resource constrained embedded systems. Field Programmable Gate Arrays (FPGAs) having programmable logic de- vices and processing…