cmpt 886: special topics in operating systems and computer architecture

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Systems Networking and Architecture Group

CMPT 886: Special Topics in Operating Systems and

Computer Architecture

Dr. Alexandra FedorovaSchool of Computing Science

SFU

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Meet the Instructor• Ph.D. in Computer Science from Harvard, 2006• Dissertation on operating system design for multicore processors• Concurrently with Ph.D., an intern at Sun Labs (3 years)• 9 US patent applications• First semester at SFU: Spring 2007• Industrial partnership with Sun Microsystems

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Course Topic• Multicore processors– New type of computer architecture– Dominates new processor market– Desktops, servers, mobile devices, etc. – Almost all chips will be multicore soon

• Many research problems to solve– How to design software for these chips? – How to design the chips themselves?– How to structure hardware/software interaction?

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Today

• Introduction to multicore processors• Examples of research problems• Overview of the course

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Conventional vs. Multicore

Core 0

L2 cache

L1 cache

Conventional processor• Single core• Dedicated caches• One thread at a time

Core 0 Core 1

L2 cache

L1 cache L1 cache

Multicore processors• At least two cores• Shared caches• Many threads simultaneously

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The Multicore Revolution• Most new processors are multicore• intel.com: Most processors shipped are multicore:– 2006: 75% for desktops, 85% for servers– 2007: 90% for desktop and mobile, 100% for servers

• Everyone’s doing it– Sun Microsystems Rock, Niagara 1, Niagara 2– IBM Power4, Power5, Power6, Cell– AMD Quad Core (Barcelona)– Embedded: ARM

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Why Multicore?

• Power consumption is a huge problem• Multicore chips potentially produce a lot more

computation per unit of power• Example:

Reduce CPU clock frequency by 20%Power consumption reduces by 50%!Put two 0.8 frequency cores on the same chipGet 1.6 times the computation at the same power consumption

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Superior Performance/Watt• Example:– Reduce CPU clock frequency by 20%– Power consumption reduces by 50%!

Core 0 Core 1

L2 cache

L1 cache L1 cache

0.8x frequency 0.8x frequency

• Put two 0.8 frequency cores on the same chip

• Get 1.6 times the computation at the same power consumption

0.5x power 0.5x power

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Why Multicore?

• Increasing processor clock speed (GHz) is inefficient– Increase clock speed by 20%– Power increases by ≈75%– How much does performance increase?

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Multicore vs. Unicore

• Multicore:– 1.6x throughput increase– No power consumption increase

• Single-core:– 1.2x throughput increase– 1.75x power increase

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Source: Sutter, The Free Lunch is over

Transistor density still

rising

Clock speed isn’t

Transistors are used for

parallelism: multicore processors

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Multicore Potential

• Multicores offer potential to compute more efficiently

• Applications and systems are not ready to realize that potential

• What needs to be done? – A fundamental shift to parallel programming– New ways to manage resources in the operating

system

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What’s Important to Remember?

Core 0 Core 1

L2 cache

L1 cache L1 cache

Massive parallelismGood or bad?• Good: We can use processor

more efficiently• Bad: We don’t know how to

make the most out of it.

Shared resources• Execution: functional units, queues, register

files• Memory: L1 cache, L2 cache, interconnects

Good or bad?• Good: More efficient resource

utilization (the reason for multicore)

• Bad: Contention for resources

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Problems Addressed in Research

• How to manage resource allocation?– Operating system solutions– Architectural (hardware solution)

• How to take advantage of parallelism? – Make concurrent programming easier (languages,

performance tools, etc.)– Make concurrent programming automatic (automatic

parallelization)

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Managing Resource Allocation

• New OS structures• Extensions to hardware architecture• Analytical performance modeling • New ways to write applications: can the

application tell the OS how it uses resources?• New algorithms (attention, theoreticians and

AI researchers!)

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Operating Systems for Multicore Processors

• Threads running concurrently compete for resources • Degree of contention depends on what the threads are doing

Core 0 Core 1

L2 cache

L1 cache L1 cache

A B C• A is a database application

(needs lots of L1 cache)• B is a web server

(needs lots of L1 cache)• C is a cryptographic thread

(needs little L1 cache)

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Challenges

• How to find out threads’ resource requirements?

• How to find out if threads will compete?

Core 0 Core 1

L2 cache

L1 cache L1 cache

A B C

• How to find out the degree of contention on performance?

• What is the best way to schedule threads?

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Problems Addressed in Research

• How to manage resource allocation?– Operating system solutions– Architectural (hardware solution)

• How to take advantage of parallelism? – Make concurrent programming easier (languages,

performance tools, etc.)– Make concurrent programming automatic (automatic

parallelization)

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Support for Concurrent Programming

• Writing parallel code is difficult• Most people think serially• Deciding how to divide the work between

threads is not always trivial• Parallel entities need to synchronize or

communicate• A new paradigm for synchronization

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Synchronization Hurts Performance

If lock is not available, threads waitExecution becomes serialized

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Coarse vs. Fine Synchronization

int update_shared_counters(int *counters, int n_counters) {

int i;

coarse_lock_acquire(counters_lock);for (i=0; i<n_counters; i++) {fine_lock_acquire(counter_locks[i]);counters[i]++;fine_lock_release(counter_locks[i]);}coarse_lock_release(counters_lock);

}

Coarse locks are easy to programBut perform poorly

Fine locks perform wellBut are difficult to program

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Transactional Memory To the Rescue!

• Can we have the best of both worlds?– Good performance– Ease of programming

• The answer is: – Transactional Memory (TM)

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Transactional Memory (TM)

• Programming model:– Extension to the language– Runtime and/or hardware support

• Lets you do synchronization without locks• Performance of fine grained locks• Ease of programming of coarse grained locks

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Transactional Memory vs. Locks

int update_shared_counters(int *counters, int n_counters) {

int i;ATOMIC_BEGIN(); coarse_lock_acquire(counters_lock);for (i=0; i<n_counters; i++) {fine_lock_acquire(counter_locks[i]);counters[i]++;fine_lock_release(counter_locks[i]);}coarse_lock_release(counters_lock);ATOMIC_END();

}

Transactional section• Looks like

coarse grained lock• Acts like fine

grained lock• Performance degrades

only if there is conflict

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The Backend of TM

read Awrite Bread Bwrite Awrite D

read Cwrite Cread Ewrite Eread D

Abort!

restart

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State of TM

• Still evolving– More work needed to make it usable and well

performing• It is very real– Sun’s new Rock processor has TM support– Intel is very active

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Summary

• Multicore systems– They are everywhere: servers, desktops, small

devices– Must understand them

• Plenty of research on multicore systems– System software (OS, compilers, runtimes)– Architecture– Analytical modeling– Applications

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Break for introductions…

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Class Structure• Learn about multicore research– Read and critique papers – Paper summaries, presentations

• Learn how to do multicore research– Discuss papers, think about new ideas– Analyze papers– Learn how to use research tools (2 homeworks)

• Do multicore research– A research project

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Research Project

• A unique experience: getting a project done from start to end

• Goal: generate a publication• Last year: two publications out of four projects• Gives you confidence as a grad student• Improves your resume• Challenging! You will learn a lot!

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Your Expectations

• Expect to work hard– But you’ll be glad you did this later

• Papers will be difficult to read at first (3-5 hours/paper)– Will get easy later

• Reward: You will be comfortable at leading your own research in this area

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Final Project

• You can create your own topic• Or choose from a list of existing topics• Some projects are very well specified (like an

undergraduate course project)• Others are more open-ended (hint: an

opportunity to be creative)• We have systems and tools you’ll need for the

project

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Final Project (cont.)

• Submit a project proposal in early February• Complete the project by early April• You have only two months• Have to work hard!• Expect to dedicate ≈15-20 hrs/week

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Will I Succeed in this Course?

• You have to work independently!• Take full responsibility for your project• I will help, but I cannot do it for you• I do not have all the answers• You will succeed, if you are prepared to work hard• What you can or cannot do now does not matter• The course is designed to train you

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Course Web Site

• Syllabus• Wiki• Multicore portal• Technical documentation