cs6210

This class is a graduate-level course that addresses a broad range of topics in operating system design and implementation.

Here is the official course webpage.

Pdfs

In the ./pdfs folder you'll find all of the papers that were covered in this course, ./pdfs/papers.zip, paper summaries that I completed for two of the papers in this course, ./pdfs/paper_summaries, and my notebook for the course , ./pdfs/cs6210.pdf.

Projects

I worked on each project for this course in a separate repository. Each project is added to this repository as a submodule. The submodules in this repository are private to uphold the Georgia Institute of Technology Academic Honor Code.

Project 1

This project is an exercise in designing and implementing applications that interface with a hypervisor to monitor and manage the resources of virtual machines. The student is tasked with implementing a virtual CPU scheduler that evenly balances the affinity, mapping, and workload of virtual CPUs to physical CPUs. The student is also tasked with implementing a memory coordinator that evenly balances the memory requirements of multiple virtual macchines.

The entire project is written in C. In this project, I learned how to use qemu and libvirt to:

• Acquire statistics for a host machine's physical CPUs
• Acquire statistics for multiple virtual machine CPUs managed by a hypervisor
• Balance virtual CPU affinity and load on physical CPUs
• Acquire statistics for a host machine's memory usage
• Acquire statistics for multiple virtual machine's memory usage
• Balance virtual machine memory allocation based upon usage statistics

Project 2

This project requires students to implement several barrier synchronization algorithms presented in the paper, "Algorithms for Scalable Synchronization on Shared-Memory Multiprocessors", by Mellor-Crummey and Scott.

The entire project is written in C. In this project, I learned how use the OpenMP API to implement the synchronization barriers/algorithms described in the paper above in a shared memory environment. I then adapted the algorithms so that they would work in a distributed memory environment using Open MPI. I also learned how to:

• Align shared memory data structures to cache lines to prevent false sharing
• Utilize atomic builtins to implement synchronization primitives
• Test and evaluate algorithms to acquire performance statistics
• Use gnuplot to graph data and make determinations about algorithm performance

Project 3

This project requires students to implement a distributed service that resembles an online store. The store application will query the prices for a product on behalf of a client from a number of different registered vendors. The store leverages a threadpool to concurrently handle multiple client requests and makes asynchronous gRPC calls, collating the prices for the requested product across all registered vendors. The store service returns this data to the client.

The entire project is written in C++. In this project I learned about:

• Multithreaded programming in C++
• C++ lambda expressions
• C++ futures
• C++ templates
• C++ class constructors and destructors
• Creating and handling asynchronous gRPC calls
• Structuring projects with the CMake build system
• Using the vcpkg package manager

Project 4

In this project, students implement the MapReduce framework described in this paper.

The entire project is written in C++. In this project I learned how to:

• Shard data to spread processing load across a distributed system
• Handle exceptions in C++
• Use advanced file system operations in C++
• Read configuration files with C++
• Conduct input validation in C++
• Leverage C++ inheritance
• Use C++ virtual functions
• Implement robust C++ applications that create and handle asynchronous gRPC calls and recover from failures and timeouts
• Architect large C++ projects
• Execute map reduction on a large corpus of data