RRAM-based Low-Power Neuromorphic Computing Engine for Space Applications

With recent breakthroughs in AI and deep learning, applying these techniques to on-board computers for space applications has grown in interest to engineers on space applications. The space field brings its own challenges, such as reliability and power restrictions. The proposed solution in this work concerns a neuromorphic accelerator for a...

Moving workloads to a better place: Optimizing computer architectures for data-intensive applications

The performance of supercomputers is not growing anymore at the rate it once used to. Several years ago a break with historical trends appeared. First the break appeared at the lower end of worldwide supercomputer installations, but now it affects a significant number of systems with average performance. Power consumption is becoming the most...

Run-time Adaptable VLIW Processors: Resources, Performance, Power Consumption, and Reliability Trade-offs

In this dissertation, we propose to combine programmability with reconfigurability by implementing an adaptable programmable VLIW processor in a reconfigurable hardware. The approach allows applications to be developed at high-level (C language level), while at the same time, the processor organization can be adapted to the specific requirements...

Fault-tolerant architectures for nanoelectronic and quantum devices

The progress in CMOS technology has entered the sub-micron realm, and the technology will approach its limits within about 15 years. Already various novel information processing devices, based on quantum mechanical effects at the nanometer scale, have been widely investigated and some have been successfully demonstrated at the circuit level....

Transport Triggered Architectures: Design and Evaluation

Morphological image processing: Architecture and VLSI design