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Postgraduate Studies
Courses Catalogue

Course details

Code

CS-647

Name

Modern Storage Systems

Program

Postgraduate

Areas

Databases, information and knowledge management

Computer systems, parallel and high performance computing

(Parallel and Distributed Systems)

Description

This course discusses storage systems with emphasis on the design and implementation of modern key value stores that host the data for big data analytics applications. The course examines the fundamental aspects in the design of key-value stores and covers the path from the point a request is created in a client until the request is served from the storage device in a storage server. While developing the main techniques for key-value stores that have been (and are currently being) proposed, it also discusses the characteristics of more traditional storage systems and future storage trends, especially for device storage technologies. The course includes lectures, research paper reading/discussion, assignments, and a student-proposed project.

LEARNING OUTCOMES
Having attended and succeeded in the course, the student is able to achieve:
1. Knowledge:

Storage device technology trends. I/O operations and associated overheads in modern datacenter servers.
The evolution of storage systems and the key benefits and characteristics of modern key-value stores.
The main characteristics and techniques for designing key-value stores covering:
- Data and metadata organization in memory and on storage devices
- Data access path and operations for reads, writes, updates, scans
- Memory, storage capacity, and CPU performance overheads
- Recovery and availability
- Networked systems
- In-memory vs. persistent approaches

2. Understanding:

Of the principles for the design and implementation of modern storage systems.

3. Application:

Of existing storage system designs to address application requirements.

4. Analysis:

The requirements of modern and future workloads and the system principles that can satisfy these requirements.

5. Synthesis:

Of principles from storage systems to design new systems that will be able to satisfy future workloads and applications.

6. Evaluation:
Of performance for modern and future storage systems and application I/O requirements.

STUDENT PERFORMANCE EVALUATION
The course for the mark will be computed from the assignments, class participation, and a final project.

Class participation: 15%
Assignments: 55% = 15% + 15% + 15% + 10%

Project: 30%

ECTS

Prerequisites

CS-345

Course website

http://www.csd.uoc.gr/~hy647

Course email

hy647 AT csd DOT uoc DOT grShow email

Courses catalog

A+

A-

Offered Postgraduate Cousres
Code	Course Name	ECTS(ΔΜ)	Prerequisites	Suggested	Areas
CS-500	Introduction to Research	2	--
CS-508	Technical Writing in English	4	--
CS-523	Digital Systems CAD Laboratory	6	CS-220, CS-225		A, A1
CS-527	Parallel Computer Architecture	6	CS-345, CS-425		A, A1, A2, Γ
CS-529	Multicore Architecture Programming	6	CS-345, HY425		A, A2, B1, B2, Γ
CS-531	Topics in Information theory	6	N/A		B, B2, B4
CS-533	Introduction to Research on Computer Networks	6	CS-335		A3, A4, B
CS-534	Packet Switch Architecture	6	CS-225, CS-335		A, A1, A4, B
CS-539	Advanced Topics on Wireless Networks and Mobile Systems	6	CS-335, CS-345		A4, B, Γ
CS-540	Advanced Topics in Programming Languages Development	6	CS-340		B1, B3, Z, Δ
CS-541	Wireless Sensor Networks	6	CS-335, CS-215		B, C1, Θ
CS-543	Software Systems and Technologies for Big Data Applications	6	CS-360, CS-252,or instructor permission.		B2, B4, Γ, Δ
CS-546	Types and Programming Languages	6	CS-255, CS-280		A2, B1, B3, Z, Γ, Δ
CS-548	Cloud-native Software Architectures	6	CS-335, CS-345		A2, Γ
CS-553	Interactive Computer Graphics	6	CS-358		C3, E, Δ, Θ
CS-558	Internet Technologies and Systems	6	CS-345		A3, A4, B, Γ, Δ
CS-559	Infrastructure Technologies for Large-Scale Service-Oriented Systems	6	CS-345, CS-360		A2, A3, B2, H, Γ, Δ
CS-561	Web Data Management	6	CS-460		B2, C3, Δ
CS-562	Advanced Database Topics	6	CS-360		B2, Δ
CS-563	Advanced Topics in Information Retrieval Systems	6	CS-463		B2, B4, Δ
CS-565	Process Management Systems	6	CS-360	CS-460	A3, A4, B1, H, Δ, Θ
CS-567	Knowledge Representation and Reasoning	6	CS-380, CS-387		B2, B4, Δ, Θ
CS-569	Human – Computer Confluence	6	CS-364	CS-359, CS-469	C3, H, Δ, Θ
CS-570	Statistical Signal Processing	6	CS-370, CS-217		B, B4, C1, C2, E, Θ
CS-573	Optimization Methods	6	CS-110, CS-119		B4, C2, E, Z
CS-575	Robotic Navigation Laboratory	6	CS-475		C2, E
CS-577	Machine Learning	6	CS-150, CS-217, CS-380		B4, C1, C2, C4, E, H, Z, Δ
CS-578	Voice Processing	6	CS-370		B, C1, Θ
CS-580	Topics in Algorithm Design	6	CS-240, CS-280, CS-380		B1, C4, Z
CS-583	Graph Algorithms	6	CS-240, CS-380		B1, C4, Z
CS-586	Distributed Computing	6	CS-380		A3, B1, Z, Γ
CS-587	Neural Networks and Learning of Hierarchical Representation	6	CS-217, CS-119 or Μ-105		B4, C1, C2, C4, Z
CS-588	Brain Network Analysis and Modeling	6	CS-217, CS-215, CS-240		B, B4, C4, H
CS-590.31	IoT for Smart Cities	6	CS-335, CS-150		A4, B, B2, Δ
CS-590.45	Modern Topics in Scalable Storage Systems	6	CS-345, CS-360		A3, B2, Γ
CS-590.72	Introduction to Bioinformatics for Computer Scientists	3	Basic knowledge in the areas of theoretical computer science (algorithms, data structures) and technical computer science (sequential optimization in C or C++, computer architectures, parallel programming, vector processors) is required.		C4, H
CS-590.73	Seminar in Reproducibility in Bioinformatics	3	CS-590.72		C4, H
CS-647	Modern Storage Systems	6	CS-345		A2, B2, Γ
CS-672	Advanced Topics in Computational Vision	6	CS-472		B4, C2, C3, E
CS-673	Introduction to Deep Generative Modelling	6	CS-217, CS-119		B4, C2, E, Z, Θ
CS-690.1-4	Teaching Assistantship	3	--
CS-693	Introduction to Game Theory	6			B, B1, B4, Z
CS-695	Supervised Personal Study	3	--
CS-697	Bibliographic Search	15
CS-698	Assessment of Research Direction and Development of a Research Plan	15
CS-699	Research for M.Sc. Thesis	30
CS-700	Seminar Courses	3	--