Reti Logiche Esercitazioni

website·Indexed 29 days ago

https://rzippo.github.io/nancy/

A collection of exercises and documentation for logic networks, focusing on Verilog Hardware Description Language and x86 Assembly language. The materials include step-by-step solutions for exam and homework exercises, guides on combinational and synchronized network synthesis, testbench construction, x86 architecture registers, and GDB debugging techniques for academic years 2024-25 and 2025-26.

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What's inside Reti Logiche Esercitazioni

  1. Overview of SuperAdditiveCurve class

    The SuperAdditiveCurve class is used to represent curves that are known to be super-additive. It inherits from Curve and implements IStableHashCode, IToCodeString, and IToMppgString.
    public class SuperAdditiveCurve : Unipi.Nancy.MinPlusAlgebra.Curve, Unipi.Nancy.Utility.IStableHashCode, Unipi.Nancy.MinPlusAlgebra.IToCodeString, Unipi.Nancy.MinPlusAlgebra.IToMppgString
  2. Overview of Raffaele Zippo's Research and Expertise

    Raffaele Zippo, PhD, is a Postdoctoral Researcher at the University of Pisa, specifically within the Networking and Cloud Computing Lab. His research focuses on performance analysis and Quality of Service (QoS) in computer architectures. He holds a PhD in Smart Computing from the Universities of Firenze and Pisa and an MSc in Computer Engineering from the University of Pisa.
  3. Overview of SubAdditiveCurve class

    The SubAdditiveCurve class represents curves that are known to be sub-additive where f(0) = 0. This specific property (regular sub-additivity) is used to optimize computations, particularly for convolution algorithms. While sub-additivity can be stable on addition and convolution without f(0) = 0, the SubAdditiveCurve type specifically requires f(0) = 0 to maintain a simplified type system for common Deterministic Network Calculus (DNC) cases.
    public class SubAdditiveCurve : Unipi.Nancy.MinPlusAlgebra.Curve, Unipi.Nancy.Utility.IStableHashCode, Unipi.Nancy.MinPlusAlgebra.IToCodeString, Unipi.Nancy.MinPlusAlgebra.IToMppgString
  4. Overview of DelayServiceCurve

    The DelayServiceCurve class models a pure delay service model. For a given delay $\tau$, the service function $f(t)$ is defined as: $f(t) = 0$ if $t \le \tau$, and $f(t) = +\infty$ otherwise. It inherits from SuperAdditiveCurve and implements IStableHashCode, IToCodeString, and IToMppgString.
    public class DelayServiceCurve : SuperAdditiveCurve, Unipi.Nancy.Utility.IStableHashCode, Unipi.Nancy.MinPlusAlgebra.IToCodeString, Unipi.Nancy.MinPlusAlgebra.IToMppgString
  5. Overview of the Nancy Network Calculus library

    Nancy is a C# library designed for Network Calculus computations. It provides implementations for min-plus and max-plus operators and is capable of handling ultimately pseudo-periodic piecewise affine curves. It can be used for writing, computing, and plotting Network Calculus expressions or as a performant engine for larger analysis tools. The library is released under the MIT license.
  6. Overview of the Curve class

    The Curve class represents functions that are piecewise affine and ultimately pseudo-periodic. A function is pseudo-periodic if $f(t+d) = f(t) + c$, where $c$ is the step gained after each pseudo-period. It is 'ultimately' pseudo-periodic if this property holds for all $t \ge T$. This class implements IStableHashCode, IToCodeString, and IToMppgString.
    public class Curve : Unipi.Nancy.Utility.IStableHashCode, IToCodeString, IToMppgString
  7. Overview of the Nancy Network Calculus library

    Nancy is a library designed for writing and computing min-plus and max-plus expressions. It is built for high performance and scalability, utilizing immutable objects and independent operations to support parallel execution across multiple CPU cores. It is suitable for learning Network Calculus, conducting research without modeling restrictions, and implementing high-performance applications.
  8. Overview of Nancy Network Calculus Library

    Nancy is an efficient parallel library designed for Network Calculus, specifically focusing on (min, +) and (max, +) algebra. It is used for the computationally efficient worst-case analysis of flow-controlled networks and real-time systems.