Insegnamento a.a. 2020-2021

20732 - COMPUTING INFRASTRUCTURES

Cross-institutional study L. Bocconi - Politecnico Milano

Course taught in English
Go to class group/s: 31
CYBER (6 credits - II sem. - OP  |  ING-INF/05)
Course Director:
GIANLUCA PALERMO

Classes: 31 (II sem.)
Instructors:
Class 31: GIANLUCA PALERMO


Mission & Content Summary

MISSION

Modern large-scale datacenters require the seamless integration of different components - applications, computation nodes, storage devices, and networks - into one computing infrastructure. The course covers the basics of current datacenters architectures, ranging from the analysis of the single components to the global infrastructure. The focus is on the foundations required to understand the design of computing infrastructures that are scalable, available, and flexible at the same time. Virtualization, container-based technology, cloud computing and storage systems are analyzed in depth to show how they can be used to support challenging tasks such as big-data applications and high-performance computing.

CONTENT SUMMARY

  • Reliability and availability of datacenters: definitions, fundamental laws, reliability block diagranms
  • Scalability and performance of datacenters: definitions, fundamental laws, queuing network theory basics
  • Hw infrastructure: Basic components, Rack structure, Cooling
  • Storage systems: Storage Area Networks and RAID architectures
  • Virtualization: basic concepts, technologies, hypervisors and containers
  • Cloud Computing: definitions and basic concepts

Intended Learning Outcomes (ILO)

KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • analyze and discuss on the trade-offs between reliability, performance and costs of different hardware and software technologies
  • Identify the basic elements that are part of a scalable Datacenter
  • discuss the role of virtualization and software technologies that are the base of cloud systems.
  • explain the main computing architectures and service models used in complex computing systems

APPLYING KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • design both computational and storage components of a data center, to satisfy specific service-level requirements
  • extend performance and reliability analysis to other types of components in a data center
  • apply performance and reliability analysis to other complex systems, even outside the computer engineering domain

Teaching methods

  • Face-to-face lectures
  • Exercises (exercises, database, software etc.)
  • Interactive class activities (role playing, business game, simulation, online forum, instant polls)

DETAILS

Exercises to apply the knowledge in simple examples or to more complicated scenarios will be used especially considering the parts related to reliability, storage system design, and performance analysis.

 

Instant Polls will be used to have a continuous feeling of the knowledge acquired by the students during the course period. During some of the more critical lectures, some moments will be dedicated to query the students in the room in an anonymous way. Tools like Quizzez, PollEverywhere, MSForms can be used as the base for this type of activity.

Assessment methods

  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
     x

ATTENDING STUDENTS

The evaluation consists of a written exam on the topics covered in the course. The exam will include both theoretical questions and numerical problems.

More in detail the written exam includes:

• Close-ended questions on course topics to verify the capacity to recognize the basic concept behind the design of a large scale computing infrastructure;

• Open-ended theoretical questions on course topics to verify the capacity to describe the key concepts related to the design of a large scale computing infrastructure;

• Numerical problem resolutions regarding analysis and design of datacenter and datacenter components, virtualization, storage systems, dependability, and performance modeling.

NOT ATTENDING STUDENTS

The evaluation consists of a written exam on the topics covered in the course. The exam will include both theoretical questions and numerical problems.

More in detail the written exam includes:

• Close-ended questions on course topics to verify the capacity to recognize the basic concept behind the design of a large scale computing infrastructure;

• Open-ended theoretical questions on course topics to verify the capacity to describe the key concepts related to the design of a large scale computing infrastructure;

• Numerical problem resolutions regarding analysis and design of datacenter and datacenter components, virtualization, storage systems, dependability, and performance modeling.

Teaching materials


ATTENDING STUDENTS

Edward D. Lazowska, John Zahorjan,G. Scott Graham, Kenneth C. Sevcik

Quantitative System Performance: Computer System Analysis Using Queueing Network Models (Open Access Book) (chapters 1-4)

 

Luiz André Barroso and Urs Hölzle

The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines

 

James Smith,  Ravi Nair

"Virtual Machines" Versatile Platforms for Systems and Processes

 

Other teaching materials will be announced before the start of the course

NOT ATTENDING STUDENTS

In addition to those suggested for the students attending the lectures, the next book is kidnly suggested.

 

  • Caesar Wu and Rajkumar Buyya - Cloud Data Centers and Cost Modeling
Last change 14/07/2020 15:39