Parallel programming: how new language features help

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In these presentation I talk about Parallel Programming, its necessities, challenges. Then I talk about how the syntax of languages like C# advances to improve the expressiveness of parallel programming.

Technology

Mehran Davoudi
Head of Development Department,
Carane Resource Planning Systems
http://ir.linkedin.com/in/mehrandvd/

Parallel Programming
Towards Efficient Cloud Computing

Presentation Overview

?
• Why to move
towards
parallel
programming?

• What’s the
most concerns
successful
applications to
implement
parallel?

• How to
handle
challenges
using new
coming
technologies

The Moore’s Law


The number of transistors on integrated
circuits doubles approximately every two
years.

2x every 2 year!

Cloud Hardware Infrastructure
Are they really
used?

Or just one part
is doing the
job!?

Why is it so hard?

Debugging
Error
Management

Cancellation

Continuation
Shared
Memory

Shared Memory
The most famous problem in parallel computing
Makes everything very complicated

Heard about them at the university
Very important but not the topic of this
presentation

Debugging
Single
Current
Statement

Multiple
Current
Statements

Error Management

100 threads are working
In the middle, 3 of them fail
What to do now!?
Continue?

Throw
Exception?

What about
remained
threads?

Cancellation
100 threads are working
30 done, 20 doing, 50 waiting
User cancels! What to do now!?

Finish
doings?

Cut the
doings?

Don’t allow
to cancel!?

How the technology helps to manage

Async/Await
Immutable
collections

Lambdas

Tasks
Aggregated
Exceptions

Threads
Isolated
Types

Task instead of Thread
A better abstraction
• Task hides most of unnecessary complicated
details of threads

Managed by .NET
• Thread pooling, resource management and many
others are controlled by the framework

A well shaped API
• It has a Fluent API
• Well integrated with Lambdas

TPL, PLINQ

TPL (Task Parallel
Library)
Cancellation

Continuation

Error
Management

Cancellation
Token

Next line is
not the next!

Aggregate
Exception

PLINQ
High level
parallelizing
tools

Based on the
famous LINQ

Parallel.For()

Enumerable
.AsParallel()

Async/Await: A real magic!

TPL

Native
Threads

Debugging Tools

Parallel
Stack

Parallel
Watch

A totally different thinking style
A totally different terminology for
developers
Next statement ≠ Next Line

It takes about 6 months to teach and
prepare a professional development team

Resources


Andres Heijlsberg conference on BUILD



Patterns of Parallel Programming, Stephen Toub, 2010



Erik Meyer and Joe Duffy talk on Chanel 9



Eric Lippert weblog on Parallel Programming



Joseph Albahari weblog on Parallel Programming



Wikipedia page of Moore’s Law

Thanks

QUESTIONS!?


Also you can contact me at:
 Mail:

Mehran.Davoudi@Hotmail.com

 LinkedIn:

http://ir.linkedin.com/in/mehrandvd

 Facebook:

www.facebook.com/mehrandvd

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Parallel programming: how new language features help

1. Mehran Davoudi Head of Development Department, Carane Resource Planning Systems http://ir.linkedin.com/in/mehrandvd/ Parallel Programming Towards Efficient Cloud Computing

2. Presentation Overview ? • Why to move towards parallel programming? • What’s the most concerns successful applications to implement parallel? • How to handle challenges using new coming technologies

3. The Moore’s Law  The number of transistors on integrated circuits doubles approximately every two years. 2x every 2 year!

4. Cloud Hardware Infrastructure Are they really used? Or just one part is doing the job!?

5. Why is it so hard? Debugging Error Management Cancellation Continuation Shared Memory

6. Shared Memory The most famous problem in parallel computing Makes everything very complicated Heard about them at the university Very important but not the topic of this presentation

7. Debugging Single Current Statement Multiple Current Statements

8. Error Management 100 threads are working In the middle, 3 of them fail What to do now!? Continue? Throw Exception? What about remained threads?

9. Cancellation 100 threads are working 30 done, 20 doing, 50 waiting User cancels! What to do now!? Finish doings? Cut the doings? Don’t allow to cancel!?

10. How the technology helps to manage Async/Await Immutable collections Lambdas Tasks Aggregated Exceptions Threads Isolated Types

11. Task instead of Thread A better abstraction • Task hides most of unnecessary complicated details of threads Managed by .NET • Thread pooling, resource management and many others are controlled by the framework A well shaped API • It has a Fluent API • Well integrated with Lambdas

12. TPL, PLINQ TPL (Task Parallel Library) Cancellation Continuation Error Management Cancellation Token Next line is not the next! Aggregate Exception PLINQ High level parallelizing tools Based on the famous LINQ Parallel.For() Enumerable .AsParallel()

13. Async/Await: A real magic! TPL Native Threads

14. Debugging Tools Parallel Stack Parallel Watch

15. A totally different thinking style A totally different terminology for developers Next statement ≠ Next Line It takes about 6 months to teach and prepare a professional development team

16. Resources  Andres Heijlsberg conference on BUILD  Patterns of Parallel Programming, Stephen Toub, 2010  Erik Meyer and Joe Duffy talk on Chanel 9  Eric Lippert weblog on Parallel Programming  Joseph Albahari weblog on Parallel Programming  Wikipedia page of Moore’s Law

17. Thanks QUESTIONS!?  Also you can contact me at:  Mail: Mehran.Davoudi@Hotmail.com  LinkedIn: http://ir.linkedin.com/in/mehrandvd  Facebook: www.facebook.com/mehrandvd

Editor's Notes

این پرزنتیشن بیشتر در مورد ساختار نرم‌افزارهایی است که در کلود باید استفاده شود.
محاسبات سنگین، تعداد تراکنش‌های بالا در ثانیهاگر اینطور نباشد این غول با یک کامپیوتر معمولی فرقی ندارد! شاید بدتر هم باشد!پلی استیشن ۳
برنامه نویسی موازی سختهاولین نکته: این آقا موهاش ریخته!یه کتاب به این کلفتی فقط برای توضیح ۱۰ تا دستور و کلاس؟!
بیشترین حجم مطالب درسی دانشگاه در برنامه نویسی موازی در مورد این قسمتهدر این ارائه قرار نیست روی این موارد زیاد صبحت کنیم. قبلا به اندازه کافی صحبت شده.هر چند که هر چقدر صبحت شه بازم کمه.
الان دکمهF10 چکار می‌کنه!؟و اینجاس که برنامه نویس میگه واااای!
و اینجاس که الگوریتم‌ها پیچیده می‌شه برنامه نویس میگه واااای!محاسبات سنگین = بیشتر از ۴۰۰ms
۲۰ تای در حال انجام کنسل شن؟ خطرناکمنتظر بمونیم: انتظار!
آدمای زیادی روی این قضیه کار می‌کننطراحی مناسبزبان‌ها.به نظرتون کیا بیشتر درگیر قسمت‌های موازی بودن؟ اون دو سه تایی که بیشتر موهاشون ریخته!
یک مفهوم قدرتمند که حاصل حدود ۱۰ سال کار یک تیم قوی است.
این دو تکنولوژی تقریبا تمام مشکلات رو پوشش می‌دن.

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Editor's Notes