System Emulation for AR and VR devices
From iis-projects
Contents
Overview
Status: Available
- Type: Semester Thesis/Master Thesis
- Professor: Prof. Dr. L. Benini
- Supervisors:
Introduction
Augmented Reality/Virtual Reality wearables are gaining momentum due to their potential to revolutionize how we perceive the world. Fitting smartphone-like processing capabilities into a lightweight form factor is quite challenging. The real-time processing constraints in a limited power budget require a novel approach across the entire stack, system-level design, and optimization.
In this project, the student has to extend the GVSoC[1] emulation platform to create/add the AR/VR wearable system to evaluate the architectures given in [2].
1. Traditional centralized camera sensor computing architecture. Here, the output of the sensors is connected via the MIPI Interface to the Processor/Aggregator system where the processing is done.
2. Distributed on-sensor computing architecture. Pre-processing is done on the sensor, and relevant data is only transferred to the Aggregator.
Character
- 10% Literature research
- 55% Extending GVSoC model
- 25% Workload creation and deployment
- 10% Verification
Required Skills
To work on this project, you will need the following:
- Knowledge in C++, Python
- Strong interest in computer architecture.
- Familiarity with Deep Learning and traditional DSP algorithms
- To have worked in the past with at least one RTL language (SystemVerilog or Verilog or VHDL) - having followed (or actively following during the project) the VLSI1 / VLSI2 courses is strongly recommended.
References
[1] Bruschi, Nazareno, et al. "GVSoC: a highly configurable, fast and accurate full-platform simulator for RISC-V based IoT processors." 2021 IEEE 39th International Conference on Computer Design (ICCD). IEEE, 2021.
[2] Gomez, Jorge, et al. "Distributed on-sensor compute system for AR/VR devices: A semi-analytical simulation framework for power estimation." arXiv preprint arXiv:2203.07474 (2022).
