AGRA | Lehrveranstaltungen

Die AGRA bietet folgende Lehrveranstaltungen für das aktuelle Semester an:

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Wintersemester 2023/2024

G | 03-IMVP-DLS

(in englischer Sprache)

In this course the students are going to be introduced to the methods used for Digital Logic Synthesis, i.e., to take the design represented at various levels of abstraction down to basic digital gates. The key aspect of this course is to make them aware of the usefulness of abstraction in digital logic synthesis and to optimize the digital circuit for the given set of constraints. This will enable students to not only understand the state of the art optimization techniques but the learning from this course can be used in emerging domains for efficient logic synthesis. Given the complexity of the digital systems in the modern world, automation is key in making the problem of digital logic synthesis feasible. The basic intuition behind optimization will be developed using linear programming and integer linear programming. The first optimization will be at the architectural level. The study at this level deals with capturing the behavior from a macroscopic viewpoint represented in the form of data flow graphs. The optimization of these graphs in terms of resource and time constraints will be done. Scheduling and Binding will be discussed at depth to perform optimizations at the architectural level. Next, we will move at the lower level of abstraction, logic level. The basics of Boolean logic representation and manipulation for digital logic synthesis will be discussed. The next part of the course deals with the two level logic minimization. We will discuss in brief about the Exact minimization algorithms but will discuss in detail about the heuristic based methods for two level logic optimization. Lastly, we will discuss the multilevel logic optimization techniques.

Introduction Lecture

Personal Introduction / Research Interests
Logistics of the course time, assignments, exams
Outline of the course will be discussed
Y-Chart

References for the Course

“Synthesis and Optimization of Digital Circuits”, by Giovanni De Micheli
“Logic Synthesis and Verification Algorithms”,by Gary D. Hachtel and Fabio Somenzi

Introduction to Optimization

What is optimization
Optimization using single variable
Optimization using multiple variable
Online Libraries to perform optimizations

Architectural Synthesis - I

Basics of Architectural Scheduling
Data flow graphs and sequencing graphs
Scheduling - ASAP, ALAP
Hierarchical Sequencing Graphs
Resource Constrained Scheduling

Architectural Synthesis - II

ILP formulation of Scheduling
Resource Constrained
Latency Constrained
Heuristic Based Scheduling - LIST Scheduling

Architectural Synthesis - III

Binding Preliminaries
Resource Sharing
Register Binding
ILP formulation for Binding

Boolean Algebra - I

Basics of Boolean Algebra
Tabular Representation
Graph based Representations

Boolean Algebra - II

Cost abstraction in terms of area and delay
Preliminaries and Terminologies
Exact Minimization Techniques (Quine McCluskey)

Heuristic Based Optimizations - I

Unateness
Operators for Boolean Algebra
Matrix Representations
Cofactor Computations
Tautology conditions

Heuristic Based Optimizations - II

Recursive Tautology
Operations on Logic covers
Containment and Complementation

Heuristic Based Optimizations - III

Espresso Minimization
Expand
Reduce
Reshape
Irredundant

MultiLevel Logic Minimization - I

Comparison between single valued and multi valued logic optimization
Elimination
Decomposition
Simplification
Extraction

MultiLevel Logic Minimization - II

Algebraic Model for Optimization of Multi level Logic
Algebraic Division

Lecture on Practical Logic Synthesis using Industry Standard/ Academic Tools

Take the design in High Level Synthesis
Synthesize it to generate Verilog
Technology Independent Optimizations
Technology Dependent Optimization
Synthesized gate level Netlist.

Prof. Dr. Rolf Drechsler

Ort & Zeit:

MZH 1450

Introduction to Reversible and Quantum Computing

G | 03-IMAT-IRQ

(in englischer Sprache)

Quantum Computing is an emerging technology that exploits the quantum mechanical properties to solve certain problems which are considered complex for classical computers. The emergence of quantum computers in recent times has motivated researchers to investigate and develop algorithms and CAD tools for compiling quantum circuits to such platforms. This course introduces students to the recent topics in quantum computing. This course will also cover Qiskit Software, which is an open-source software development kit for creating and running programs and algorithms.
The lectures are logically split in five modules:

Module 1 introduces some mathematical background and formalisms that would help the students in grasping the concepts of the other modules that follows.

Module 2 provides a general introduction to reversible and quantum computing, with particular emphasis on reversible and quantum gates.

Module 3 focuses on synthesis and optimization techniques for reversible circuits, which are considered as the stepping-stone to compiling applications for quantum computers. Various existing methods in this regard shall be discussed.

Module 4 deals with some in-depth study of well-known quantum algorithms, and some of the necessary backgrounds of quantum computing. Some of the well known quantum algorithms like Shor’s factoring algorithm, Grover’s algorithm, Quantum Phase Estimation algorithm, Deutsch Jozsa’s algorithm etc will be discussed in this module.

Finally, Module 5 deals with various approaches for compiling quantum circuits, and some important applications of quantum computing.

Reference Books:

Quantum computing for computer scientists, Mirco A. Mannucci and Noson S. Yanofsky, Cambridge University Press, 2008.
Quantum computation and quantum information, Michael A. Nielsen and Isaac L. Chuang, Cambridge University Press 2010.
Quantum computing explained, David McMahon, Wiley-interscience, John Wiley Sons, Inc. Publication 2008.
Introduction to Quantum Mechanics, 2nd Edition, David J. Griffiths, Prentice Hall New Jersey 1995.
Quantum Computer Science By Marco Lanzagorta, Jeffrey Uhlmann
An Introduction to Quantum Computing By Phillip Kaye, Raymond Laflamme, Michele Mosca.

Veranstalter: Prof. Dr. Rolf Drechsler, Kamalika Datta, Dr. Abhoy Kole
Ort & Zeit:

Vorlesung Mo 12-14 Uhr MZH 1090
Übung Mi 16-18 Uhr MZH 1090

Rechnerarchitektur und Eingebettete Systeme (in englischer Sprache)

G | 03-IBAP-RA

In Vorlesung und Übung wird eine Einführung in grundlegende Fragen, Methoden, und Techniken der Rechnerarchitektur gegeben und der Entwurf digitaler Systeme vermittelt.

Inhalte:

Hardwareentwurf

Abstraktionsebenen
Hardwarebeschreibungssprachen (HDLs)

VHDL
SystemC

HDL-Synthese
Verdrahtung
Test und Verifikation

Aufbau eines Rechners

Maschinensprachen
Datenpfad und Kontrollpfad
Pipelining

Systementwurf - Modelle und Methoden

Zielarchitekturen für HW/SW-Systeme
Allokation, Bindung, Ablaufplanung
Partitionierung

Software-Entwurf

Compiler
Codegenerierung
Registerallokation

Schätzung der Entwurfsqualität

Ziele:

Detaillierte Kenntnis des Aufbaus moderner Rechner
Verständnis für den modernen Systementwurf
Grundlegende Kenntnisse von Compilern und Codegenerierung
Kenntnisse von Syntheseansätzen für Hardware
Beurteilung der Qualität von Systementwürfen
Eigenständige Präsentation von Lösungen (in den wöchentlichen Tutorien)
Selbstständiges Erkennen der Probleme beim Entwurf eines komplexen Systems

Veranstalter: Prof. Dr. Rolf Drechsler, Dr. Muhammad Hassan
Ort & Zeit:
Vorlesung Mo 10:00 - 12:00 Uhr MZH 5500
Übung Di 08:00 - 10:00 Uhr MZH 6200

Test von Schaltungen und Systemen

H | 03-IMAP-TSS-03

In der Vorlesung wird eine Einführung in grundlegende Fragen, Methoden und Techniken des Hardware-Tests gegeben.

Inhalte:
1. Physikalische Fehlerursachen
2. Abstraktion von der physikalischen Ebene, Fehlermodelle
3. Algorithmen zur Berechnung von Signalwahrscheinlichkeiten
4. Techniken zur Manipulation Boolescher Funktionen
5. Algorithmen zur Fehlersimulation
6. Algorithmen zur Testmustergenerierung
7. Nutzung strukturellen Wissens zur Effizienzsteigerung
8. Techniken zur Reduktion des Suchraumes,
Fehleräquivalenz u.-dominanz

Ziele:
1. Verständnis des Testproblems
2. Vermittlung des Testverlaufs für Schaltungen und Systeme
3. Kenntnis der klassischen und modernen Verfahren
im Testbereich
4. Kenntnis von Algorithmen auf (Schaltkreis-)Graphen
5. Wissen über die Komplexität der Verfahren

Veranstalter: Prof. Dr. Rolf Drechsler, Dr. Sebastian Huhn

Ort & Zeit:
Übung Mo 14:00 - 16:00 MZH 1450
Vorlesung Do 08:00 - 10:00 MZH 1110

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