Distributed ML

The Internet

Classical synchronization

Concurrency

Time Synchronization

Distributed Mutual Exclusion

Remote Procedure Call (RPC)

Distributed File Systems

Concurrency Control

Logging and Crash Recovery

Fault Tolerance

RAID (Redundant Array of Inexpensive Disks)

Distributed Replication

Distributed Databases

Spanner

Google File System (GFS)

Apache Hadoop Distributed File System (HDFS)

Data-Intensive Computing

MapReduce

Hadoop

In-memory cluster compute

Apache Spark

Internet Content Delivery

DNS (Domain Name System)

Content Delivery Network (CDN)

Publish-Subscribe

Kafka

Virtualization

3-tier Web Service Architecture

Security Protocols

Byzantine Fault Tolerance

P2P Network

Distributed Ledgers

Blockchain

 15-440 Distributed Systems Carnegie Mellon University Fall 2020 A course offering both theoretical understanding and practical experience in distributed systems. Key themes include concurrency, scheduling, network communication, and security. Real-world protocols and paradigms like distributed filesystems, RPC, MapReduce are studied. Course utilizes C and Go programming languages. Most software is now distributed in some sense. This course is meant to serve as an introduction to distributed systems, emphasizing techniques for creating functional, usable, and high-performance distributed systems.

This course aims to: (1) provide students with an understanding of the principles and techniques behind the design of distributed systems, such as locking, concurrency, scheduling, and communication across the network. (2) provide students with practical experience designing, implementing, and debugging real distributed systems.

Major themes covered in this course include scarcity, scheduling, concurrency and concurrent programming, naming, abstraction and modularity, imperfect communication and other types of failure, protection from accidental and malicious harm, optimism, and the use of instrumentation and monitoring and debugging tools in problem solving. As the creation and management of software systems is a fundamental goal of any undergraduate systems course, students will design, implement, and debug large programming projects. After this course, students will have learned to…

- Implement and structure distributed systems programs.
- Write programs that can interoperate using well-defined protocols.
- Debug highly concurrent code that spans multiple programs running on multiple cores and machines.
- Reason about distributed algorithms for locking, synchronization and concurrency, scheduling, and replication.
- Use standard network communication primitives such as UDP and TCP.
- Understand the general properties of networked communication necessary for distributed systems programming in clusters and on the Internet.
- Employ and create common paradigms for easing the task of distributed systems programming, such as distributed filesystems, RPC, and MapReduce. Be able to clearly elucidate their benefits, drawbacks, and limitations.
- Identify the security challenges faced by distributed systems programs.
- Be able to select appropriate security solutions to meet the needs of commonly encountered distributed programming scenarios. Because this course has a big project component, you must be proficient in C and programming on UNIX systems. We will use the [Go programming language](https://golang.org/) throughout the term. It is required that you have taken 15-213 and gotten a “C-“ or higher since many of the programming skills you will need are taught in that course. **However, if you received a C in 15-213, you must meet with your academic advisor to discuss your background before taking 15-440/640, perhaps taking an additional course to sharpen your systems skills. Your advisor must email us approval and an explanation of why you have sufficient background to take 15-440/640.** 

 15-440 Distributed Systems

Parallelism and Distributed Systems

Distributed ML

1 courses cover this concept

15-440 Distributed Systems