There is still an enormous difference in energy-efficiency between modern deep learning (DL) ASICs and the human brain. Modern DL HW platforms cannot get close even when flexibility is sacrificed in their hardware architecture in favor of energy-efficiency. Furthermore, the high compute, storage, and memory bandwidth requirements of modern DL applications put a lot of stress on the energy budget and result in a significant hardware cost. Within the pAvIS project, we will develop a neuromorphic AI microprocessor with low-power consumption and real-time performance for professional healthcare applications.
Within the larger pAvIs project, this PhD position will contribute to the implementation of low-power DL hardware accelerators that can efficiently execute AI functions at the edge of the sensor system. This enables a shift from processing at the back-end of the system (on general-purpose HW) to processing at the edge where the data is collected. Moving AI earlier in the signal processing chain will enable advancements inpatient diagnostics leading to better care. Topics of research will include design-space exploration of hardware architectures for neural net accelerator and optimization of their characteristics (serial/parallel, bit-width, memory access) in terms of classification speed, programmability, area, and energy consumption.
Electronic Systems group at TU/e and project partners
The Electronic Systems group consists of seven full professors, two associate professors, eight assistant professors, several postdocs, about 40 PDEng and PhD candidates and support staff. The ES group is world-renowned for its design automation and embedded systems research. It is our ambition to provide a scientific basis for design trajectories of electronic systems, ranging from digital circuits to cyber-physical systems. The trajectories are constructive and lead to high quality, cost-effective systems with predictable properties (functionality, timing, reliability, power dissipation, and cost). Design trajectories for applications that have strict real-time requirements and stringent power constraints are an explicit focus point of the group. Within this area, prof.dr. H. Corporaal and dr.ir. S. Stuijk have developed various novel power-efficient computer architectures and their associated compilation trajectories.
The pAvis project team is designed to combine extensive knowledge in the key fields. The project team includes industrial partners from Philips and GrAI Matter Labs. As part of this project, the PhD candidate will work closely with these industrial partners to ensure that the developed architecture is suitable for the systems developed by these partners.
We are looking for excellent candidates that add value to the ES group and match the following profile:
Do you recognize yourself in this profile and would you like to know more? Please contact
dr.ir. Sander Stuijk, s.stuijk[at]tue.nl, http://www.es.ele.tue.nl/~sander
For information about terms of employment, click here or contact mrs. Linda van den Boomen,
HR advisor l.j.c.v.d.boomen[at]tue.nl.
Please visit www.tue.nl/jobs to find out more about working at TU/e!
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