Duke Systems CPS 110 210 310 Introduction to

Duke Systems CPS 110 210 310 Introduction to Operating Systems Fall 2013 Jeff Chase Duke University

Resources to know about • Course Web – http: //www. cs. duke. edu/~chase/cps 310 – Or other links through CS department – All powerpoints, policies, reading, schedule, lab (project) instructions are posted there. • Piazza – Announcements – Chatter. “Maybe even anonymous posting. ” • Sakai – Minimal use, e. g. , mainly for disseminating grades

Meetings • “Lectures”: – MW 3: 05 – 4: 20 – ~25 lectures total • Recitations – Fri 3: 05, Bio Sci 111 – TA: Balakrishnan Chandrasekaran • Two midterms – 10/4 (recit) and 11/6 (in class) • “Light” final exam (1. 5 x) – 12/15 from 2 -5 PM “Bio Sci”

What is this course about? • Programs • Platforms • Performance • … User Applications Operating System Substrate / Architecture “The system is all the code your program uses that you didn’t have to write. ”

http: //steve-yegge. blogspot. com/2008/03/get-that-job-at-google. html Steve Yegge

Course goals • • Learn to think about systems holistically. Sound mastery of structures and principles. Reinforce with practical, concrete examples. Minimize “unknowns”. 2003

OS Platform: A Model Applications/services. May interact and serve one another. Libraries/frameworks: packaged code used by multiple applications OS platform: same for all applications on a system E, g, , classical OS kernel OS platform mediates access to shared resources. [RAD Lab]

“Software Architecture” User Applications Software architecture Physics stops here. Computer architecture Operating System(s) Substrate / Architecture Comparative architecture: what works Reusable / recurring design patterns • Used in OS • Supported by OS

Platform abstractions • Platforms provide “building blocks”… • …and APIs to use them to construct software. – Instantiate/create/allocate – Manipulate/configure – Attach/detach – Combine in uniform ways – Release/destroy • Abstractions are layered. – What to expose? What to hide? The choice of abstractions reflects a philosophy of how to build and organize software systems.

Managing Complexity System Component System Environment Component Systems are built from components. Operating systems define styles of software components and how they interact. OS maps components onto the underlying machine. …and makes it all work together.

Comparative software architecture Large, long-lived software systems are like buildings. They are built by workers using standard design patterns. They depend on some underlying infrastructure. But they can evolve and are not limited by the laws of physics.

Watch it! Computer systems is a liberal arts discipline. Just because someone will pay you to do it doesn’t mean it’s not liberal arts.

Course prerequisites • Basic data structures and programming – Lists, stacks, queues, graphs, DAGs, trees – Abstract data types (ADTs), classes, objects – Dynamic data structures • Basic architecture – CPU context: registers – Execution: runtime stack and frames – Memory and L 1/L 2/L 3 caches, DMA I/O – Virtual addressing and memory layout • Basic discrete math and probability

Dynamic data structures

A simple module • A set of procedures/functions/methods. • An interface (API) that defines a template for how to call/invoke the procedures. • State (data) maintained and accessed by the procedures. • A module may be a class that defines a template (type) for a data structure, which may have multiple instances (objects). state P 1() P 2() P 3() P 4() Abstract Data Type (ADT): the module’s state is manipulated only through its API (Application Programming Interface).

Code: instructions in memory _p 1: pushq movl movq popq ret %rbp %rsp, %rbp $1, %eax %rdi, -8(%rbp) %rbp load add store _x, R 2, 1, R 2, _x ; load global variable x ; increment: x = x + 1 ; store global variable x

A Peek Inside a Running Program CPU core 0 common runtime x your program code library your data R 0 heap Rn PC SP x y registers y stack high “memory” address space (virtual or physical) e. g. , a virtual memory for a running program (process)

Data in memory 64 bytes: 3 ways Memory is “fungible”. p + 0 x 0 int p[] int* p char p[] char *p 0 x 1 f p 0 x 0 char* p[] char** p 0 x 1 f Pointers (addresses) are 8 bytes on a 64 -bit machine. 0 x 1 f

Heap: dynamic memory The “heap” is an ADT in a runtime library: the code to maintain the heap is a heap manager. It allocates a contiguous slab of virtual memory from the OS kernel, then “carves it up” as needed. It enables the programming language environment, to store dynamic objects. E. g. , with Unix malloc and free library calls. Allocated heap blocks for structs or objects. Align! Free block

Read it on the course web

But Java programs are interpreted They run on an “abstract machine” (e. g. , JVM) implemented in software. ”bytecode” http: //www. media-art-online. org/java/help/how-it-works. html

Platforms are layered/nested

Grades: CPS 210 Fall 2012 4 A+ 8 A 11 A 13 B+ 8 B 7 B 9 C* or lower

Cumulative Distribution Function CPS 2/310 Spring 2013 Probability that a random student’s score is X or below A* C* B* Total score X

Cumulative Distribution Function (CDF) 80% of the requests have response time R with x 1 < R < x 2. “Tail” of 10% of requests with response time R > x 2. 90% quantile What’s the mean R? 50% (median) A few requests have very long response times. median value 10% quantile x 1 x 2 Understand how the mean (average) can be misleading, e. g. if tail is heavy.

What is this course about? • Programs • Platforms • Sharing • Concurrency • Storage • Protection and trust • Resource management • Virtualization • Scale and performance • Abstractions User Applications Operating System Substrate / Architecture

Reading • Course notes and slides • External sources on every topic – OS in Three Easy Pieces – A few academic papers and web readings – Yes, even a “comic book” We’ll look at these with varying levels of scrutiny.

New! $10! Web/Saa. S/cloud http: //saasbook. info New! $75! http: //csapp. cs. cmu. edu a classic No text, but these may be useful. Saltzer/Kaashoek Very MIT Do not buy kindle edition.

Workload: projects 1. Dynamic heap memory (malloc/free) 2. Unix shell (“Devil Shell”) 3. Java concurrency: multi-threaded programming (“Elevator”) 4. Key/value store (“Devil Filer”) 5. Performance evaluation of storage server

Collaboration • OK among groups: – General discussion of course concepts and programming environment. – “What does this part of the handout mean? ” • Not OK among groups – Design/writing of another’s program – “How do I do this part of the handout? ” • Definitely not OK: – Using code from a previous semester. • If in doubt, ask me.

Thoughts on cheating Cheating is a form of laziness. Cheating happens at those other schools. Duke students work hard and don’t cut corners. Your work is your own: if in doubt, ask. Listen to what shame tells you.

Extra slides The point of the remaining slides is: • We take a broad view of “operating systems” encompassing a variety of application platforms. • We start with Unix, a canonical/classical OS. • Unix has continuing relevance: it continues to thrive deep inside the rich platforms we use today: knowing about the Unix kernel helps to understand how they work. • Hardware and application demands change rapidly. Operating system kernels evolve slowly, but we often add more code around them to adapt to change. • You’ll see these slides again.

What is this course about? • “Greater Unix” – Classical OS abstractions and structure – Systems programming with C and Unix • Networked systems – Sockets and servers, smartphones to clouds – Elementary cryptosystems – Distributed systems topics • Managing concurrency – Threads, multi-threaded Java • Managing storage and data – Files, caches, disks, recovery, content delivery

Some lessons of history • At the time it was created, Unix was the “simplest multi-user OS people could imagine. ” – It’s in the name: Unix vs. Multics • Simple abstractions can deliver a lot of power. – Many people have been inspired by the power of Unix. • The community spent four decades making Unix complex again. . but the essence is unchanged. • Unix is a simple context to study core issues for classical OS design. “It’s in there. ” • Unix variants continue to be in wide use. • They serve as a foundation for advances.

Virtual Machine (JVM) “Classical OS” Reloaded. [http: //www. android. com]

End-to-end application delivery Where is your application? Where is your data? Where is your OS? Cloud and Software-as-a-Service (Saa. S) Rapid evolution, no user upgrade, no user data management. Agile/elastic deployment on virtual infrastructure.

Saa. S platform elements browser [wiki. eeng. dcu. ie] container “Classical OS”

Open. Stack, the Cloud Operating System Management Layer That Adds Automation & Control [Anthony Young @ Rackspace]

EC 2 The canonical public cloud Virtual Appliance Image

Canonical OS Example: “Classical OS” • Unix/Linux, Windows, OS-X • Research systems – Multics – Mach – Minix – …

Drivers of Change Exponential growth Increasing diversity User Applications Operating System Substrate / Architecture Aggregation Composition Orchestration Backward compatibility Broad view: smartphones to servers, web, and cloud.

Moore’s Law and CPU Performance 3 X From Hennessy and Patterson, Computer Architecture: A Quantitative Approach, 4 th edition, 2006 Sea change in chip design: multiple “cores” or processors per chip Uniprocessor Performance (SPECint)