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CPS 110 210 310 Introduction to Operating Systems Fall 2013

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/cps310 Or other links through CS department

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CPS 110 210 310 Introduction to Operating Systems Fall 2013

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

  2. Resources to know about • Course Web • http://www.cs.duke.edu/~chase/cps310 • 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

  3. Meetings “Bio Sci” • “Lectures”: • MW 3:05 – 4:20 • ~25 lectures total • Recitations • Fri 3:05, Bio Sci 111 • TA: BalakrishnanChandrasekaran • Two midterms • 10/4 (recit) and 11/6 (in class) • “Light” final exam (1.5x) • 12/15 from 2-5 PM

  4. 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.”

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

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

  7. 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]

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

  9. 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.

  10. Managing Complexity System 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. Component Component Component Component System Environment

  11. 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.

  12. 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.

  13. 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 L1/L2/L3 caches, DMA I/O • Virtual addressing and memory layout • Basic discrete math and probability

  14. Dynamic data structures

  15. A simple module P1() P2() P3() P4() • 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 Abstract Data Type (ADT): the module’s state is manipulated only through its API (Application Programming Interface).

  16. Code: instructions in memory _p1: pushq %rbp movq %rsp, %rbp movl $1, %eax movq %rdi, -8(%rbp) popq %rbp ret load _x, R2 ; load global variable x add R2, 1, R2 ; increment: x = x + 1 store R2, _x ; store global variable x

  17. A Peek Inside a Running Program 0 CPU core common runtime your program x code library address space (virtual or physical) e.g., a virtual memory for a running program (process) your data R0 heap Rn x PC y SP registers stack y high “memory”

  18. Data in memory64 bytes: 3 ways p + 0x0 Memory is “fungible”. 0x0 int p[] int* p char p[] char *p 0x1f p char* p[] char** p 0x0 0x1f Pointers (addresses) are 8 bytes on a 64-bit machine. 0x1f

  19. 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. Allocated heap blocks for structs or objects. Align! Free block It enables the programming language environment, to store dynamic objects. E.g., with Unix mallocand free library calls.

  20. Read it on the course web

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

  22. Platforms are layered/nested

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

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

  25. Cumulative Distribution Function (CDF) “Tail” of 10% of requests with response time R > x2. 80% of the requests have response time R with x1 < R < x2. 90% quantile A few requests have very long response times. What’s the mean R? 50% (median) median value 10% quantile x1 x2 Understand how the mean (average) can be misleading, e.g. if tail is heavy.

  26. 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

  27. 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.

  28. New! $10! Web/SaaS/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.

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

  30. 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.

  31. 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.

  32. 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.

  33. 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

  34. 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.

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

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

  37. SaaS platform elements container browser “Classical OS” [wiki.eeng.dcu.ie]

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

  39. EC2 The canonical public cloud Virtual Appliance Image

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

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

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

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