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With the increasing interest in neuromorphic computing, designers of embedded systems face the challenge of efficiently simulating such platforms to enable architecture design exploration early in the development cycle. Executing artificial…
The management of the energy consumption and thermal dissipation of multi-core heterogeneous platforms is becoming increasingly important as it can have direct impact on the platform performance. This paper discusses an approach that…
Modern multicore systems are migrating from homogeneous systems to heterogeneous systems with accelerator-based computing in order to overcome the barriers of performance and power walls. In this trend, FPGA-based accelerators are becoming…
The complexity of automotive systems is increasing quickly due to the integration of novel functionalities such as assisted or autonomous driving. However, increasing complexity poses considerable challenges to the automotive supply chain…
The adoption of high-performance multi-core platforms in avionics and automotive systems introduces significant challenges in ensuring predictable execution, primarily due to shared resource interferences. Many existing approaches study…
Due to their cost, performance, area, and energy efficiency, MPSoCs offer appealing architecture for emerging mixed criticality systems (MCS) such as driverless cars, smart power grids, and healthcare devices. Furthermore, heterogeneity of…
The Adapteva Epiphany many-core architecture comprises a 2D tiled mesh Network-on-Chip (NoC) of low-power RISC cores with minimal uncore functionality. It offers high computational energy efficiency for both integer and floating point…
In the last decade, we have witnessed exponential growth in the complexity of control systems for safety-critical applications (automotive, robots, industrial automation) and their transition to heterogeneous mixed-criticality systems…
The field of edge computing has witnessed remarkable growth owing to the increasing demand for real-time processing of data in applications. However, challenges persist due to limitations in performance and power consumption. To overcome…
A surge in artificial intelligence and autonomous technologies have increased the demand toward enhanced edge-processing capabilities. Computational complexity and size of state-of-the-art Deep Neural Networks (DNNs) are rising…
Hybrid memory systems, comprised of emerging non-volatile memory (NVM) and DRAM, have been proposed to address the growing memory demand of applications. Emerging NVM technologies, such as phase-change memories (PCM), memristor, and 3D…
Modern physics experiments often utilize FPGA-based systems for real-time data acquisition. Integrated analog electronics demand for complex calibration routines. Furthermore, versatile configuration and control of the whole system is a key…
RISC-V cores have gained a lot of popularity over the last few years. However, being quite a recent and novel technology, there is still a gap in the availability of comprehensive simulation frameworks for RISC-V that cover both the…
The emergence of large-scale, sparse, multimodal, and agentic AI models has coincided with a shift in hardware toward supernode architectures that integrate hundreds to thousands of accelerators with ultra-low-latency interconnects and…
Parallel computing is a standard approach to achieving high-performance computing (HPC). Three commonly used methods to implement parallel computing include: 1) applying multithreading technology on single-core or multi-core CPUs; 2)…
Different GPU applications exhibit varying scalability patterns with network-on-chip (NoC), coalescing, memory and control divergence, and L1 cache behavior. A GPU consists of several StreamingMulti-processors (SMs) that collectively…
Task-based programming models have become very popular, as they offer an attractive solution to parallelize serial application code with task and data annotations. They usually depend on a runtime system that schedules the tasks to multiple…
Recent embedded systems are designed with high-performance System-on-Chips (SoCs) to satisfy the computational needs of complex applications widely used in real life, such as airplane controllers, autonomous driving automobiles, medical…
The growing complexity of cyber-physical systems (CPSs) calls for early prototyping tools that combine accuracy, speed, and usability. Virtual Platforms (VPs) provide fast functional simulation, but hybrid co-emulation solutions, in which…
While FPGA accelerator boards and their respective high-level design tools are maturing, there is still a lack of multi-FPGA applications, libraries, and not least, benchmarks and reference implementations towards sustained HPC usage of…