OS, Base & Bounds, Virtual Memory IntroInstructor: Steven Ho

Review

• Warehouse Scale Computers– Supports many of the applications we have come to

depend on– Software must cope with failure, load variation, and

latency/bandwidth limitations– Hardware sensitive to cost and energy efficiency

• Request Level Parallelism– High request volume, each largely independent– Replication for better throughput, availability

• MapReduce– Convenient data-level parallelism on large dataset across

large number of machines– Spark is a framework for executing MapReduce algorithms

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Word Count in Spark’s Python API// RDD: primary abstraction of a distributed collection of items

file = sc.textFile(“hdfs://…”)

// Two kinds of operations:

// Actions: RDD → Value

// Transformations: RDD → RDD

// e.g. flatMap, Map, reduceByKey

file.flatMap(lambda line: line.split())

.map(lambda word: (word, 1))

.reduceByKey(lambda a, b: a + b)

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MapReduce Word Count Example• Map phase: (doc name, doc contents) → list(word, count)

// “I do I learn”” → [(“I”,1),(“do”,1),(“I”,1),(“learn”,1)]

map(key, value):

for each word w in value:

emit(w, 1)

• Reduce phase: (word, list(count)) → (word, count_sum)// (“I”, [1,1]) → (“I”,2)

reduce(key, values):

result = 0

for each v in values:

result += v

emit(key, result)

47/30/2018 CS61C Su18 - Lecture 22

Word Count in Spark’s Python API// RDD: primary abstraction of a distributed collection of items

file = sc.textFile(“hdfs://…”)

// Two kinds of operations:

// Actions: RDD → Value

// Transformations: RDD → RDD

// e.g. flatMap, Map, reduceByKey

file.flatMap(lambda line: line.split())

.map(lambda word: (word, 1))

.reduceByKey(lambda a, b: a + b)

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MapReduce Word Count Example• Map phase: (doc name, doc contents) → list(word, count)

// “I do I learn”” → [(“I”,1),(“do”,1),(“I”,1),(“learn”,1)]

map(key, value):

for each word w in value:

emit(w, 1)

• Reduce phase: (word, list(count)) → (word, count_sum)// (“I”, [1,1]) → (“I”,2)

reduce(key, values):

result = 0

for each v in values:

result += v

emit(key, result)

67/30/2018 CS61C Su18 - Lecture 22

Word Count in Spark’s Python API// RDD: primary abstraction of a distributed collection of items

file = sc.textFile(“hdfs://…”)

// Two kinds of operations:

// Actions: RDD → Value

// Transformations: RDD → RDD

// e.g. flatMap, Map, reduceByKey

file.flatMap(lambda line: line.split())

.map(lambda word: (word, 1))

.reduceByKey(lambda a, b: a + b)

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MapReduce Word Count Example• Map phase: (doc name, doc contents) → list(word, count)

// “I do I learn”” → [(“I”,1),(“do”,1),(“I”,1),(“learn”,1)]

map(key, value):

for each word w in value:

emit(w, 1)

• Reduce phase: (word, list(count)) → (word, count_sum)// (“I”, [1,1]) → (“I”,2)

reduce(key, values):

result = 0

for each v in values:

result += v

emit(key, result)

87/30/2018 CS61C Su18 - Lecture 22

a b

Agenda

• OS Intro

• Administrivia

• OS Boot Sequence and Operation

• Multiprogramming/time-sharing

• Introduction to Virtual Memory

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CS61C so far…

10

CPU

Caches

Memory

RISC-V Assembly

C Programs#include <stdlib.h>

int fib(int n) { return fib(n-1) + fib(n-2);}

.foolw t0, 4(s0)addi t1, t0, 3beq t1, t2, foonop

Project 1Project 2Labs

Project 3

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So how is this any different?

11

Keyboard

Screen

Storage

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Adding I/O

12

I/O (Input/Output)

Screen Keyboard Storage

CPU

Caches

Memory

RISC-V Assembly

C Programs#include <stdlib.h>

int fib(int n) { return fib(n-1) + fib(n-2);}

Project 1Project 2

Project 3

7/30/2018 CS61C Su18 - Lecture 22

.foolw t0, 4(s0)addi t1, t0, 3beq t1, t2, foonop

Raspberry Pi ($40 on Amazon)

13

CPU+$s, etc.

MemoryStorage I/O(Micro SD Card)

Serial I/O(USB)

Network I/O(Ethernet)Screen I/O

(HDMI)

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It’s a real computer!

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But wait…• That’s not the same! When we run Venus, it

only executes one program and then stops.

• When I switch on my computer, I get this:

15

Yes, but that’s just software! The Operating System (OS)7/30/2018 CS61C Su18 - Lecture 22

Well, “just software”

• The biggest piece of software on your machine?

• How many lines of code? These are guesstimates:

16

Codebases (in millions of lines of code). CC BY-NC 3.0 — David McCandless © 2015http://www.informationisbeautiful.net/visualizations/million-lines-of-code/

84 million lines of code!

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What does the OS do?• One of the first things that runs when your

computer starts (right after firmware/bootloader)

• Loads, runs and manages programs:– Multiple programs at the same time (time-sharing)

– Isolate programs from each other (isolation)

– Multiplex resources between applications (e.g., devices)

• Services: File System, Network stack, etc.

• Finds and controls all the devices in the machine in a general way (using “device drivers”)

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Agenda

• OS Intro

• Administrivia

• OS Boot Sequence and Operation

• Multiprogramming/time-sharing

• Introduction to Virtual Memory

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Administrivia

• Proj4 due on Friday (8/03)– Project Party tonight, Soda 405/411, 4-6pm

• HW6 due tonight, HW7 released• Guerilla Session on Wed. @Cory 540AB• The final will be 8/09 7-10PM @VLSB

2040/2060!• We’re almost there! :D

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Agenda

• OS Intro

• Administrivia

• OS Boot Sequence and Operation

• Multiprogramming/time-sharing

• Introduction to Virtual Memory

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What happens at boot?• When the computer switches on, it does the

same as Venus: the CPU executes instructions from some start address (stored in Flash ROM)

21

CPU

PC = 0x2000 (some default value) Address Space

0x2000:addi t0, x0, 0x1000lw t0, 4(s0)…

(Code to copy firmware into regular memory and jump into it)

Memory mapped

7/30/2018 CS61C Su18 - Lecture 22

What happens at boot?• When the computer switches on, it does the

same as Venus: the CPU executes instructions from some start address (stored in Flash ROM)

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1. BIOS: Find a storagedevice and load first sector (block of data)

2. Bootloader (stored on, e.g., disk): Load the OS kernel from disk into a location in memory and jump into it.

3. OS Boot: Initialize services, drivers, etc.

4. Init: Launch an application that waits for input in loop (e.g., Terminal/Desktop/...

7/30/2018 CS61C Su18 - Lecture 22

Launching Applications• Applications are called “processes” in most OSs.• Created by another process calling into an OS

routine (using a “syscall”, more details later).– Depends on OS, but Linux uses fork (see OpenMP

threads) to create a new process, and execve to load application.

• Loads executable file from disk (using the file system service) and puts instructions & data into memory (.text, .data sections), prepare stack and heap.

• Set argc and argv, jump into the main function.

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Supervisor Mode• If something goes wrong in an application, it can

crash the entire machine. What about malware, etc.?

• The OS may need to enforce resource constraints to applications (e.g., access to devices).

• To protect the OS from the application, CPUs have a supervisor mode bit (also need isolation, more later).– You can only access a subset of instructions and

(physical) memory when not in supervisor mode (user mode).

– You can change out of supervisor mode using a special instruction, but not into it (unless there is an interrupt).

247/30/2018 CS61C Su18 - Lecture 22

Syscalls• How to switch back to OS? OS sets timer

interrupt, when interrupts trigger, drop into supervisor mode.

• What if we want to call into an OS routine? (e.g., to read a file, launch a new process, send data, etc.)– Need to perform a syscall: set up function arguments

in registers, and then raise software interrupt– OS will perform the operation and return to user

mode

• This way, the OS can mediate access to all resources, including devices, the CPU itself, etc.

257/30/2018 CS61C Su18 - Lecture 22

Syscalls in Venus• Venus provides many simple syscalls using the ecall RISC-V instruction

• How to issue a syscall?– Place the syscall number in a0– Place arguments to the syscall in the a1 register– Issue the ecall instruction

• This is how your RISC-V code has been able to produce output all along

• ecall details depend on the ABI (Application Binary Interface)

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Example Syscall

• Let’s say we want to print an integer stored in s3:

Print integer is syscall #1

li a0, 1add a1, s3, x0ecall

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Venus’s Environmental Calls

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Agenda

• OS Intro

• Administrivia

• OS Boot Sequence and Operation

• Multiprogramming/time-sharing

• Introduction to Virtual Memory

297/30/2018 CS61C Su18 - Lecture 22

Multiprogramming• OS runs multiple applications at the same time.

• But not really (unless have a core per process)

• Switches between processes very quickly. This is called a “context switch”.

• When jumping into process, set timer interrupt.– When it expires, store PC, registers, etc. (process

state).

– Pick a different process to run and load its state.

– Set timer, change to user mode, jump to the new PC.

• Deciding what process to run is called scheduling.

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Protection, Translation, Paging• Supervisor mode does not fully isolate

applications from each other or from the OS.– Application could overwrite another application’s

memory.– Remember the linker in CALL: application assumes

that code is in certain location. How to prevent overlaps?

– May want to address more memory than we actually have (e.g., for sparse data structures).

• Solution: Virtual Memory. Give each process the illusion of a full memory address space that it has completely to itself.

317/30/2018 CS61C Su18 - Lecture 22

Meet the

Staff

6/21/2018 CS61C Su18 - Lecture 4 32

Emaan Sruthi SeanTrash TV Show

Judge JudyBachelor in

ParadiseDr. Phil

Favorite Plot Twist

Breaking Bad Arrival Memento

Best Bathroom in Cal

7th Floor Soda Stanley HallBottom Floor of

Cory

Best Study Spot

1st Floor MoffittThe VLSB

LibraryUpper Floor of

East Asian

Agenda

• OS Intro

• Administrivia

• OS Boot Sequence and Operation

• Multiprogramming/time-sharing

• Introduction to Virtual Memory

337/30/2018 CS61C Su18 - Lecture 22

Adding Disks to Hierarchy• Use VM as a mechanism to “connect” memory

and disk in the memory hierarchy

7/30/2018 CS61C Su18 - Lecture 22 34

Regs

L2 Cache

Memory

Disk

Tape

Instr Operands

Blocks

Pages

Files

Upper Level

Lower Level

Faster

Larger

L1 CacheBlocks

Memory Hierarchy

7/30/2018 CS61C Su18 - Lecture 22 35

Now:Virtual

Memory

Earlier:Caches

Virtual Memory Goals

• Allow multiple processes to simultaneously occupy memory and provide protection: Don’t let programs read/write each other’s memory

• Give each program the illusion that it has its own private address space– Suppose code starts at address 0x00400000, then

different processes each think their code resides at that same address!

– Each program must have a different view of memory

7/30/2018 CS61C Su18 - Lecture 22 36

Virtual Memory Goals

• Next level in the memory hierarchy:– Provides program with illusion of a very large main

memory:– Working set of “pages” reside in main memory - others

reside on disk.

• Also allows OS to share memory, protect programs from each other

• Today, more important for protection vs. just another level of memory hierarchy

• Each process thinks it has all the memory to itself• (Historically, it predates caches)

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Virtual to Physical Address Translation

• Each program operates in its own virtual address space; ~only program running

• Each is protected from the other• OS can decide where each goes in memory• Hardware gives virtual physical mapping

38

Dynamic Address Translation

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Location-independent programsProgramming and storage management ease ⇒ need for a base register

ProtectionIndependent programs should not affecteach other inadvertently ⇒ need for a bound register

Multiprogramming drives requirement for resident supervisor (OS) software to manage context switches between multiple programs

prog1

prog2

Phys

ical

Mem

ory

OS

Modern Virtual Memory Systems Illusion of a large, private, uniform store

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Protectionseveral programs, each with their private address space and one or more shared address spaces

Demand PagingProvides the ability to run programs larger than the primary memory

Hides differences in machine configurations

The price is address translation on each memory reference

OS

progi

PrimaryMemory

SwappingStore

VA PAmappingTLB

Analogy: Shopping at IKEA• Furniture name like virtual address• Actual warehouse location like physical

address• IKEA shopping list like page table—you write

mappings from furniture name to location• On shopping list, whether the item is sold out

like valid bit indicating in main memory vs. on disk

• Whether you can flop on a bed, draw on chalk board, turn lights off/onlike access rights

41

Simple Example: Base and Bound Reg

42

Simple Base and Bound Translation

7/30/2018 CS61C Su18 - Lecture 22 43

Load X

ProgramAddress Space

BoundRegister

BoundsViolation?

Phys

ical

Mem

ory

currentsegment

BaseRegister

+

PhysicalAddressLogical

Address

Base and bounds registers are visible/accessible only when processor is running in supervisor mode

Base Physical Address

Segment Length

≤

Separate Areas for Program and Data

7/30/2018 CS61C Su18 - Lecture 22 44

Physical Address

Physical Address

Load X

ProgramAddressSpace

Mai

n M

emo

ry

datasegment

Data Bound Register

Mem. Address Register

Data Base Register

≤

+

BoundsViolation?

Program Bound Register

Program Counter

Program Base Register

≤

+

BoundsViolation?

programsegment

Logical Address

Logical Address

What is an advantage of this separation?

(Scheme used on all Cray vector supercomputers prior to X1, 2002)

“Bare” 5-Stage Pipeline

• In a bare machine, the only kind of address is a physical address

7/30/2018 CS61C Su18 - Lecture 22 45

PC

Inst. Cache D Decode E M

Data Cache W+

Main Memory (DRAM)

Memory Controller

Physical Address

Physical Address

Physical Address

Physical Address

Physical Address

Base and Bound Machine

7/30/2018 CS61C Su18 - Lecture 22 46

PC

Inst. Cache D Decode E M

Data Cache W+

Main Memory (DRAM)

Memory Controller

Physical Address

Physical Address

Physical Address

Physical Address

Data Bound Register

Data Base Register

≤

+

Logical Address

Bounds Violation?

Physical Address

Prog. Bound Register

Program Base Register

≤

+

Logical Address

Bounds Violation?

As programs start and end, memory becomes fragmented. Therefore, if we ever need a large chunk of memory, programs will need to be moved.

Memory Fragmentation

7/30/2018 CS61C Su18 - Lecture 22 47

What if we want to run process 6, and we need 32K of space?!

OSSpace

16K24K

24K

32K

24K

prog 1prog 2

prog 3

OSSpace

24K16K

32K

24K

prog 1prog 2

prog 3

prog 5

prog 48K

Programs 4 & 5 start

Programs 2 & 5end OS

Space

16K24K16K

32K

24K

prog 1

prog 48K

prog 3

free

16KBIG IDEA:USE RAM AS $$

FOR DISK

Direct Mapped, write back/write allocate(A)

Direct Mapped, write through/no write allocate

(B)

Fully Associative, write back/write allocate(C)

Fully Associative, write thorugh/no write allocate

(D)

48

Question: What kind of cache should memory be?

Direct Mapped, write back/write allocate(A)

Direct Mapped, write through/no write allocate

(B)

Fully Associative, write back/write allocate(C)

Fully Associative, write through/no write allocate

(D)

49

Question: What kind of cache should memory be?

Summary

• The role of the Operating System– Booting a computer: BIOS, bootloader, OS boot,

initialization

• Base and bounds for multiple processes– Simple, but doesn’t give us everything we want

• Virtual memory bridges memory and disk– Provides illusion of independent address spaces to

processes and protects them from each other

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