1. D u k e S y s t e m s 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 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 “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 (1.5x) – 12/15 from 2-5 PM “Bio Sci”

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

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

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 Environment System Component 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.

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 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). P1() P2() P3() P4() 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 addR2, 1, R2; increment: x = x + 1 storeR2, _x; store global variable x

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

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

19. Heap: dynamic memory Allocated heap blocks for structs or objects. Align! 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. Free block

20. Read it on the course web

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

23. Platforms are layered/nested

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

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

26. 10% quantile 90% quantile median value 80% of the requests have response time R with x1 < R < x2. x1x2 “Tail” of 10% of requests with response time R > x2. What’s the mean R? Understand how the mean (average) can be misleading, e.g. if tail is heavy. A few requests have very long response times. 50% (median) Cumulative Distribution Function (CDF)

27. 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

28. 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.

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

30. 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

31. 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.

32. 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.

33. 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.

34. 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

35. 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.

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

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

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

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

40. EC2 The canonical public cloud Virtual Appliance Image

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

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

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