Prima di Memmo, i miei appunti erano sparsi tra mille PDF. Ora uno spazio di lavoro raccoglie tutto in un unico posto, e vedo esattamente cosa mi resta da studiare.
This textbook intends to be a comprehensive and substantially self-contained two-volume book covering performance, reliability, and availability evaluation subjects. The volumes focus on computing systems, although the methods may also be applied to other systems. The first volume covers Chapter 1 to Chapter 14, whose subtitle is ``Performance Modeling and Background". The second volume encompasses Chapter 15 to Chapter 25 and has the subtitle ``Reliability and Availability Modeling, Measuring and Workload, and Lifetime Data Analysis".
This text is helpful for computer performance professionals for supporting planning, design, configuring, and tuning the performance, reliability, and availability of computing systems. Such professionals may use these volumes to get acquainted with specific subjects by looking at the particular chapters. Many examples in the textbook on computing systems will help them understand the concepts covered in each chapter. The text may also be helpful for the instructor who teaches performance, reliability, and availability evaluation subjects. Many possible threads could be configured according to the interest of the audience and the duration of the course. Chapter 1 presents a good number of possible courses programs that could be organized using this text.
Volume I is composed of the first two parts, besides Chapter 1. Part I gives the knowledge required for the subsequent parts of the text. This part includes six chapters. It covers an introduction to probability, descriptive statistics and exploratory data analysis, random variables, moments, covariance, some helpful discrete and continuous random variables, Taylor series, inference methods, distribution fitting, regression, interpolation, data scaling, distance measures, and some clustering methods. Part II presents methods for performance evaluation modeling, such as operational analysis, Discrete-Time Markov Chains (DTMC), and Continuous Time Markov Chains (CTMC), Markovian queues, Stochastic Petri nets (SPN), and discrete event simulation.
Prima di Memmo, i miei appunti erano sparsi tra mille PDF. Ora uno spazio di lavoro raccoglie tutto in un unico posto, e vedo esattamente cosa mi resta da studiare.
I riassunti di Memmo sono oro puro prima degli esami. Non devo rileggere 800 pagine due settimane prima, solo le parti importanti.
La chat AI mi ha salvato più di una volta la sera prima di un esame. Continuo a chiedere finché non capisco, senza aspettare risposte da un gruppo di studio.
I quiz colpiscono esattamente ciò che devo sapere. Memmo tiene traccia di dove mi blocco, così mi esercito solo su ciò che conta davvero.
Le flashcard con ripetizione spaziata sono magia pura. Memmo sa quando sto per dimenticare qualcosa e me lo ripropone.
I podcast AI sono i miei preferiti. Li ascolto mentre vado a scuola e ripasso senza stare davanti al computer.
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