Adaptive Hardware and Systems (2V, 1U; 4 LP ECTS)

Course number in SS 2017: L.079.05809
Lecturer: Dr. Paul Kaufmann
Office: O3.116

News

11.07.2017 Final lab grades the lecture outline are online
11.07.2017 Lecture slides on CGP and EHW are online


04.07.2017 Lecture slides on MOEAs and DSE are online
20.06.2017 Lecture slides on ES, PSO, ACO, and GP are online
13.06.2017 4 weeks for solving Lab 4 (submission date: 10th of July)
13.06.2017 Two lectures at June, 27th
06.06.2017 Slides on Evolutionary Algorithms online


29.05.2017 Lab 3 online, Schedule for the last two lectures changes.
23.05.2017 Floorplanning and Quizzy 1 slides are online
19.05.2017 Updated iRace files (development environment, qga.c, qga parameters files, and target-runner script)
17.05.2017 Lab 2 online. Solutions for Lab 1 online. Updated score sheet.
12.05.2017 Exam Bonus Scores online at sciebo
12.05.2017 New rooms for Lab 2 and Lab 3: please see table below
09.05.2017 Slides for second lecture online; slides of first lecture updated; Quizzy 1 online
28.04.2017 VirtualBox Appliance for code development online
28.04.2017 Slides updated, Lab 1 online
25.04.2017 Slides "Introduction to Adaptive Hardware and Systems" and "Introduction to Optimization Algorithms" online
First lecture: Tuesday, 25th of April, 14:15-15:45, in room O1.258

Description

Adaptation reflects the capability of a system to maintain or improve its performance in the context of internal or external changes, changes in the operational environment, incidental or intentional interference, or trade-offs between performance requirements and available resources.

This lecture focuses on adaptive hardware systems. After a short introduction to analog and digital reconfigurable hardware the lecture focuses on algorithms from the Computational Intelligence (CI) domain for the implementation of the adaptation and optimization mechanisms.

The labs include the implementation of learning strategies for run-time adaptable hardware signal classifiers, evolution of adaptable processor caches, and optimization of chip designs.

Lecture content

  • Reconfigurable digital and analog hardware
  • The basic notion of Optimization and Computational Intelligence
  • Statistical analysis of non-deterministic algorithms
  • Gradient / Steepest Descent and Hill Climbing
  • The Metropolis Algorithm, Simulated Annealing, Tabu Search, Variable Neighborhood Search
  • Genetic Algorithms, Evolutionary Strategies, Genetic Programming
  • Particle Swarm Optimization, Ant Colony Optimization
  • Multi-objective Evolutionary Algorithms

Lab content / Exercises

  • Floorplanning
  • Placement
  • Evolution of hardware signal classifiers and processor caches
  • High Level Synthesis Design Space Exploration

Schedule and Materials

The course is held on Tuesday, 14:15-15:45, in room O1.258. The labs are held on every second Tuesday, 16:00-17:30, in room O3.219. The course materials can be downloaded here.

DateContentLab
25.04. Introduction to Adaptive Hardware and Systemsno lab
02.05.Introduction to OptimizationLab 1: TSP
09.05.Introduction to Optimization II & Algorithm Evaluationno lab
16.05.Algorithm Evaluation IIRoom O4.267. Discussion of Lab 1: TSP; Lab 2: Algorithm Comparison + iRace
23.05.Algorithm Evaluation III + Floorplanningno lab
30.05.Floorplanning IIRoom O3.267. Discussion of Lab 2;
06.06.Genetic Algorithmsno lab
13.06.Genetic Algorithms IIDiscussion of Lab 3
20.06.Genetic Algorithms IIIno lab
27.06.Evolutionary Strategies, Particle Swarm Optimization, Ant Colony OptimizationGenetic Programming
04.07.Multi-objective Optimizationno lab
11.07.Multi-Objective Optimization II, Evolvable HardwareDiscussion of Lab 4
18.07.no lectureno lab
25.07.no lectureno lab