Algorithms for VLSI

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Credits
6
Types
Specialization complementary (Advanced Computing)
Requirements
This subject has not requirements
Department
CS
Most of the design flow of an integrated circuit is automated, starting from the specifications using Hardware Description Languages until reaching the physical layout. The flow goes through through different synthesis and analysis phases: behavioral synthesis, logic synthesis, floorplanning, placement, routing, timing analysis, formal verification, etc. This course will review the most important algorithmic aspects in design automation of electronic circuits. A significant part of the course will be devoted to algorithms for minimization of Boolean functions and representation with logic gates. The algorithms for physical design (floorplanning, placement and routing) will be mostly based on solving problems with graph models.

Course Syllabus (summary). Circuit design flow: from specification to layout. Minimization of logic circuits: algorithms for two-level and multi-level logic synthesis.
Technology mapping. Algorithms for physical synthesis: floorplanning, placement and routing. Formal verification: equivalence and model checking.

Teachers

Person in charge

  • Jordi Cortadella Fortuny ( )

Weekly hours

Theory
2
Problems
1
Laboratory
0
Guided learning
0
Autonomous learning
4

Competences

Technical Competences of each Specialization

Advanced computing

  • CEE3.1 - Capability to identify computational barriers and to analyze the complexity of computational problems in different areas of science and technology as well as to represent high complexity problems in mathematical structures which can be treated effectively with algorithmic schemes.
  • CEE3.2 - Capability to use a wide and varied spectrum of algorithmic resources to solve high difficulty algorithmic problems.
  • CEE3.3 - Capability to understand the computational requirements of problems from non-informatics disciplines and to make significant contributions in multidisciplinary teams that use computing.

Generic Technical Competences

Generic

  • CG1 - Capability to apply the scientific method to study and analyse of phenomena and systems in any area of Computer Science, and in the conception, design and implementation of innovative and original solutions.
  • CG3 - Capacity for mathematical modeling, calculation and experimental designing in technology and companies engineering centers, particularly in research and innovation in all areas of Computer Science.

Transversal Competences

Reasoning

  • CTR6 - Capacity for critical, logical and mathematical reasoning. Capability to solve problems in their area of study. Capacity for abstraction: the capability to create and use models that reflect real situations. Capability to design and implement simple experiments, and analyze and interpret their results. Capacity for analysis, synthesis and evaluation.

Basic

  • CB6 - Ability to apply the acquired knowledge and capacity for solving problems in new or unknown environments within broader (or multidisciplinary) contexts related to their area of study.
  • CB8 - Capability to communicate their conclusions, and the knowledge and rationale underpinning these, to both skilled and unskilled public in a clear and unambiguous way.
  • CB9 - Possession of the learning skills that enable the students to continue studying in a way that will be mainly self-directed or autonomous.

Contents

  1. Introduction.
    Integrated circuit fabrication. Layout layers and design rules. VLSI design flow. VLSI design styles.
  2. Two-level logic synthesis
    Boolean Algebras. Representation of Boolean functions. Quine-McCluskey algorithm. Heuristic logic minimization: Espresso.
  3. Multi-level logic synthesis.
    Kernel-based algebraic decomposition. AIG-based decomposition. Technology mapping for standard cells and FPGAs.
  4. Formal verification
    Binary Decision Diagrams. Combinational equivalence checking. Sequential equivalence checking. Model checking with temporal logic.
  5. Partitioning and Floorplanning
    Partitioning algorithms. Representation of floorplans. Slicing floorplans. Floorplanning algorithms.
  6. Placement
    Optimization objectives. Algorithms for global placement. Algorithms for legalization and detailed placement.
  7. Global routing
    Representation of routing regions. Algorithms for single-net and full-net routing.
  8. Detailed routing
    Horizontal and vertical constraint graphs. Channel routing. Switchbox routing. Over-the-cell routing.

Activities

Activity Evaluation act


Learning the design flow of a VLSI circuit



Theory
2h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
2h

Learning of algorithms for logic synthesis



Theory
10h
Problems
4h
Laboratory
0h
Guided learning
0h
Autonomous learning
20h

Learning of techniques for formal verification of circuits



Theory
6h
Problems
4h
Laboratory
0h
Guided learning
0h
Autonomous learning
14h

Learning of techniques for circuit floorplanning and placement



Theory
8h
Problems
4h
Laboratory
0h
Guided learning
0h
Autonomous learning
20h

Learning of routing algorithms



Theory
10h
Problems
6h
Laboratory
0h
Guided learning
0h
Autonomous learning
16h

Teaching methodology

The theoretical content of the course is taught in the theory lectures. During the practical classes, practical examples are solved and different types of problems are proposed. These problems will have to be solved during the time of autonomous learning. An algorithmic project will also be proposed during the course. Students will have to solve and implement it during their time of autonomous learning.

Evaluation methodology

Grade = 35% FP + 35% FT + 30% EX

FP = Final Project (graded from 0 to 10) in which each participant is required to develop a project on some algorithmic problem related to Electronic Design Automation, either proposed by the professor or by the student. The results of the project will have to be presented in class. The source code of the software will have to be delivered in some form such that the results of the project can be easily generated by executing the application.

FT = Final Test graded from (0 to 10) covering the contents of the course.

EX = Exercises assigned to the student and solved during the Autonomous Learning time. Two assignments will be delivered during the course (15% of the grade each one).

Bibliography

Basic: