Category: Spring (2016)

In this quarter project, we are asked to do a detailed analysis for an operating system in different aspects. For CPU and scheduling, we need to estimate the overheads for procedure calls and system calls, task creation time, and context switch time. For memory, we have to calculate Random Access Memory (RAM) access time, RAM

Continue Reading “Operating System Quarter Project” →

For the last homework, I am asked about not only the motivation of using scheduler activations, but also some details about Log-Structured File System (LFS), including what the assumptions LFS have and how data reading, writing, and segment cleaning are done in LFS.

In the first part of the homework, I elaborate the implementation details of Global Memory System (GMS). Later on, I am asked to compare the tradeoff between transparency and optimization across a few operating systems, including Sprite, Xen, and Grapevine. At the end, I compare the lazy evaluation policy between Mach, Exokernel, Xen, and VAX/VMS.

There are three parts in this homework. In the first part, I need to compare the details between different systems, including Hydra, Multics, Unix, and Pilot. Last, I am asked to provide an operating system example that takes advantage of specialized hardware. Lastly, the question is about the reason for existence of multi-user timesharing system,

Continue Reading “Operating System Homework 1” →

It is a prerequisite homework for one wants to enroll in this class. Problems relate to privileged instructions, synchronization — thread-safe coding , virtual memory — Translation Lookaside Buffer (TLB), and file system — number of disk reads needed for different file access operations.

In this project, we want to do some research on restaurant rating system with temporal dynamics. For the experiment dataset, we directly adapt Yelp Competition Dataset for restaurants. After some analysis, we find out there is a quite significant pattern for both restaurant ratings and user ratings over months every year. At the end, we

Continue Reading “Latent Variable Final Project” →

There are three parts in this homework. Firstly, I work on Markov Random Field and derive the update rules with evidence lower bound (ELBO). Secondly, I use the conclusion from previous derivations and implement Gibbs Sampling and Mean Field Algorithm, both of who take a noisy picture as input and output a denoised picture. Lastly,

Continue Reading “Latent Variable Homework 4” →

In the beginning of this homework, I work on some basic properties of Gaussian variables, including calculating the expectation and convolution of a mixture of `K` Gaussian variables. Later, I am asked to model a problem in terms of PGM and figure out its update. rules. Details of training stage and testing stage are also

Continue Reading “Latent Variable Homework 3” →

This homework is about Metropolis-Hastings, Gibbs Sampling, derivation of update rules, modeling a given problem in terms of Probabilistic Graphical Model (PGM), and practically implementing a program to calculate the update step-by-step. Codes are included in the report.

In the first homework, I am given some problems related to basic probabilities and machine learning, including conditional independent, Bayesian rules, optimization, and practice of deriving the formula of exponential family.