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Understanding Parallel Computing: Amdahl’s Law

More cores mean better performance, right? That's not what Amdahl says. Learn one of the foundations of parallel computing in "Amdahl's Law." Prepare yourself for math. And lawn mowing.

Comments on "Understanding Parallel Computing: Amdahl’s Law"

bruce384

The blackboard in part 1 was too far away and blurry to be any use.
bruce384

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    bryanjrichard

    @bruce384 It’s an issue, we know. Whiteboard resolution is something that will be improved in future videos.

    Reply
    geira

    Viewing the Flash video in full screen makes the whiteboard eminently readable. However there seems to be no discernible difference between 360p and 720p(HD). Conversion error during upload? Otherwise, nice presentation.

    Reply
mbergandi

Or even better, why don’t you look into a digital approach and stop scratching on cave walls all together :)

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fher98

Mmmm seems no one has ever been on a class room with a white board, sitting at the end of the class. Just pay attention and you know whats written.

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bazik

lol , process boy !!.
Well, this can become a good basic course on parallel programming if the author continues and goes deeper talking about real issues that makes Amdahl’s law, encountered in the case of shared and distributed memory ( problem size, communication,..),
Keep going ;-)

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justlikeef

The possible resource contention that is generated by parallel processing is often overlooked as a reason that something that appears to be able to run in parallel cannot. While the processes may be able to execute in parallel by definnition (as in, one is not dependent on the output of another for execution, and can therefore run at the same time), they still may require access to the same resources to complete their task.

This is often a cause of problems in the database world where multiple clients may be executing queries on desparent data. While the queries may not even have the same rows in their result sets, one process may have a block of the database locked that another is trying to read, and the second not only has to block for that query, but for all other sheduled operations until it can get access to the data it needs.

The same situation exists in system memory. While two executing tasks may not depend on each other and may therefore be run on different cores, only one core can access a specific block of memory at a time. The second will have to block not only the running task, but those scheduled for it until the block is freed by the first core.

Amdahl’s law does not model these variables, nor is it easy to do so. more cores != more speed

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marcegarba

Thanks for the videos. Very enjoyable, and I like Dr. Eadline’s relaxed style of teaching.

Even more, kudos to LM for their senior staff. We have a lot to learn from them.

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aekarahan

Thanks, for this very nice explanation especially for well choosen lawn mower example. I enjoyed a lot.

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rajiravi

Thanks for the videos. Good explanation with really easy example.

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usmanusb

Thanks Doc for good explanation… Looking forward for more stuff…

//usman sarwar

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d1g1t4Lnrg

Process Boy = LMAO
Good video series on this. Thanks for the information on why these situations provide diminishing returns

Have a great day!

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okupion

Wow. What better place to have an introductory crash course in Parallel computing than here at LM, and what better person to deliver the course!! Thanks Doug.

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