ACCU 2012: Go, D, C++ and The Multicore Revolution

Copyright © 2011–2012 Russel Winder 1

Go, D, C++ and theMulticore Revolution

Russel Winder

email: [email protected]: [email protected]

twitter: russel_winder

mailto:[email protected]


Aims, Goals and Objects

● Show that shared memory multi-threading should return to being an operating systems development technique and not continue to be pushed as an applications programming technique.

● Show, possibly, that the C++11 standard may, perhaps, have saved C++ from the dustbin of obscurity.


Structure

A beginning.

A middle.

An end.


Protocol

● Questions or short comments during the session are entirely in order.

● Let me know you have an interjection by raising your hand, and when I come to an appropriate pause, I'll pass you the token.

Questions, answers, comments, etc. appearingto get too long as interjections may get stackedto be unstacked at a break.


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A Beginning


It is no longer contentious thatThe Multicore Revolution

is well underway.


Quad core laptops and phones.

Eight and twelve core workstations.

Servers with “zillions” of cores.


Software technologyis now lagging

hardware technologyby decades.


Operating systems manage coreswith kernel threads.

Operating systems are fundamentally shared memory multi-threaded systems.

Operating systems rightly use all the lock, semaphore, monitor, etc. technologies.


Operating systems really rather needto be native code systems.


Constructive dichotomies…


Native code languages.

vs.

Virtual machine based languages.


Statically typed languages.

vs.

Dynamically typed languages.


Compiled languages.

vs.

Scripting languages languages.


Imperative languages.

vs.

Declarative languages.


Sequential.

vs.

Parallel.


Computationally intensive.

vs.

I/O intensive.


Batch flow.

vs.

Event driven.


Monolithic systems.

vs.

Cooperating subsystems.


Computationally intensive systems orsubsystems definitely have to be parallel.

Other systems likely use concurrencybut not parallelism.


Concurrency is a design tool.

Parallelism is a tool to improvecomputational performance.


Static vs. Dynamic

● Fortran● C● C++● D● Go● Rust● Java● Scala● Ceylon● Kotlin

● Python, Jython

● Lisp, Clojure

● Ruby, JRuby

● Groovy

● JavaScript

● Dart

COBOL


A Middle


It's all about controllingconcurrency with tools that programmers find usable.


Shared memory multi-threading is an operating system technique.


Applications and tools programmersneed computational models with

integrated synchronization.


ActorsIndependent processes communicating via asynchronous exchange of messages

CSPSequential processes connected by channels using synchronous message exchange (rendezvous).

DataflowOperators connected by channels with activity triggered by arrival of data on the channels.


ActorsIndependent processes communicating via asynchronous exchange of messages


DataflowOperators connected by channels with activity triggered by arrival of data on the channels.


CSPSequential processes connected by channels using synchronous message exchange (rendezvous).


Need examples.


What is the Value of ?

● Easy, it's known exactly, it's (obviously).

It's simples

Александр Орлов 2009


Approximating

● What is it's value represented as a floating point number?● We can only obtain an approximation.● A plethora of possible algorithms to choose from, a

popular one is to employ the following integral equation.

4=∫0

1 1

1x2dx


One Possible Algorithm

● Use quadrature to estimate the value of the integral – which is the area under the curve.

=4n∑i=1

n 1

1i−0.5n

2

With n = 3 not much to do, but potentially lots of error. Use n = 107 or n = 109?

Embarrassingly parallel.


Scatter – Gather

map reduce


Code!


Need another example.


The Sleeping Barber Problem


The Sleeping Barber Problem

● The barber's shop has a single cutting chair and a row of waiting seats.

● The barber sleeps in the cutting chair unless trimming a customer.

● Customers arrive at the shop at intervals.

● If the barber is asleep, the customer wakes the barber takes the cutting chair and gets a trim.

● If the barber is cutting, a new customer checks to see if there is a free waiting seat.

● If there is join the queue to be trimmed.

● If there isn't leave disgruntled.

Problem originally dueto Edsgar Dijkstra.


A new customer enters the shop,check to see if they can go straightto the cutting chair, if not can theytake a waiting chair, if not leave.

The waiting chairs

The cutting chair.

The barber's shop.


Wikipedia article presents the classic operating systems approach using locks and semaphores.

http://en.wikipedia.org/wiki/Sleeping_barber_problem

http://en.wikipedia.org/wiki/Sleeping_barber_problem


More code!


Note to Self:

Did you, in fact, show all the examples in:

● C● D● Go● C++● Python


An End


Native code language are just asmuch scripting languages asvirtual machine languages

and interpreted ones.


Virtual machine languages arejust as fast as native code

languages when using JITs.


Multicore and multiprocessorare now the norm,not the exception.


Parallelism only mattersif computational

performance matters.


Unstructured synchronizationof concurrent systems

is not a feasible approach.


Actors, CSP and Datafloware the future of

applications structure.


Passing messages betweenprocesses is the way forward.


Shared memory concurrencyis a dead end for applications.


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The End


Go, D, C++ and theMulticore Revolution

Russel Winder

email: [email protected]: [email protected]

twitter: russel_winder

mailto:[email protected]

ACCU 2012: Go, D, C++ and The Multicore Revolution

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Transcript of ACCU 2012: Go, D, C++ and The Multicore Revolution