Difference between revisions of "Probing the limits of fake-quantised neural networks"
From iis-projects
Line 1: | Line 1: | ||
== Introduction == | == Introduction == | ||
− | + | Deep neural networks usually require huge computational resources to deliver their statistical power. | |
+ | However, in many applications where latency and data privacy are important constraints, it might be necessary to execute these models on resource-constrained computing systems such as embedded, mobile, or edge devices. | ||
Line 9: | Line 10: | ||
− | == Competences == | + | == Competences and project character == |
+ | |||
+ | === Competences === | ||
Required: | Required: | ||
Line 22: | Line 25: | ||
* Knowledge of digital arithmetic (e.g., two's complement, overflow, wraparound) | * Knowledge of digital arithmetic (e.g., two's complement, overflow, wraparound) | ||
+ | === Project character === | ||
− | + | * 20% Theory | |
+ | * 40% C/C++ and Python coding | ||
+ | * 40% Deep learning | ||
− | + | ||
− | + | == Logistics == | |
− | + | ||
+ | The student and the advisor will meet on a weekly basis to check the progress of the project, clarify doubts, and decide the next steps. | ||
+ | The schedule of this weekly update meeting will be agreed at the beginning of the project by both parties. | ||
+ | Of course, additional meetings can be organised to address urgent issues. | ||
+ | |||
+ | At the end of the project, you will have to present your work during a 20 minutes talk in front of the IIS team and defend it during the following 5 minutes discussion. | ||
Line 35: | Line 46: | ||
− | + | == Status: Available == | |
We are looking for 1 Master student. | We are looking for 1 Master student. | ||
It is possible to complete the project either as a Semester Project or a Master Thesis. | It is possible to complete the project either as a Semester Project or a Master Thesis. | ||
− | Supervisors: [[:User:spmatteo | Matteo Spallanzani]][mailto:spmatteo@iis.ee.ethz.ch spmatteo@iis.ee.ethz.ch], [[:User:andrire | Renzo Andri (Huawei RC Zurich)]] | + | Supervisors: [[:User:spmatteo | Matteo Spallanzani]] [mailto:spmatteo@iis.ee.ethz.ch spmatteo@iis.ee.ethz.ch], [[:User:andrire | Renzo Andri (Huawei RC Zurich)]] |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
Revision as of 20:00, 24 September 2021
Contents
Introduction
Deep neural networks usually require huge computational resources to deliver their statistical power. However, in many applications where latency and data privacy are important constraints, it might be necessary to execute these models on resource-constrained computing systems such as embedded, mobile, or edge devices.
Project description
Competences and project character
Competences
Required:
- Fundamental concepts of deep learning (convolutional neural networks, backpropagation, computational graphs)
- Numerical representation formats (integer, floating-point)
- Numerical analysis
- Python programming
- C/C++ programming
Optional:
- Knowledge of the PyTorch deep learning framework
- Knowledge of digital arithmetic (e.g., two's complement, overflow, wraparound)
Project character
- 20% Theory
- 40% C/C++ and Python coding
- 40% Deep learning
Logistics
The student and the advisor will meet on a weekly basis to check the progress of the project, clarify doubts, and decide the next steps. The schedule of this weekly update meeting will be agreed at the beginning of the project by both parties. Of course, additional meetings can be organised to address urgent issues.
At the end of the project, you will have to present your work during a 20 minutes talk in front of the IIS team and defend it during the following 5 minutes discussion.
Professor
Status: Available
We are looking for 1 Master student. It is possible to complete the project either as a Semester Project or a Master Thesis.
Supervisors: Matteo Spallanzani spmatteo@iis.ee.ethz.ch, Renzo Andri (Huawei RC Zurich)