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It is one thing to run short benchmark on laptop. Other thing to sustain load 24/7 with demand spikes and hw failures.



In the spirit of the article:

If you can write it so that it runs in 1/100th the time, do you even have to worry about it running for 24/7?


This is absolutely true! However, I'm not aware of anybody doing this for the graph processing systems being discussed in the post. Nor am I sure what that would mean. Admittedly if something takes 100 times longer to run on multiple machines than it does on a single laptop (as in the previous COST post [1]) then you might care about fault tolerance, but this is a contrived problem if you could achieve the same results faster on yor laptop.

[1] http://www.frankmcsherry.org/graph/scalability/cost/2015/01/...


I was answering parent questions. There are usually good reasons for clustering and big iron.


can't help but feel that maybe you missed the point. The point is that an inexpensive single computer, programmed properly, can be seen to blow away gigantic, extremely expensive "big data"-programmed clusters.

if you wanted to run this same algorithm on a 'real' single computer with ecc and high-performance cores, nothing would stop you, and it would get even faster, and still be radically less expensive in every dimension than the "big data" clusters, for this problem set.


Didn't miss the point at all. Lamenting lack of reliable laptops. Well, at least with reliable memory. You can buy a laptop with ECC RAM in the display adapter, but not as main memory! Sigh.

Luckily networking is getting so good that remote desktops feel almost like local most of the time.


So true. If you can't accept the risk of random bit flip in memory, laptops are only good for using a real computer remotely. Memory errors do happen all too often on laptops. Have had it happening in the middle of a AES CBC encrypted data file... How hard would it be to get ECC RAM on laptops for better reliability?




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