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I think this paper amazing because it solves a complex problem with a simple solution. How do you create a hash function that adjust to the varying number of underlying buckets ? Solution: hash to a circle.
Chord: http://nms.lcs.mit.edu/papers/chord.pdf I think this paper amazing because it solves a complex problem with a simple solution. How do you create a hash function that adjust to the varying number of underlying buckets ? Solution: hash to a circle.
I highly recommend people give this paper a read. I think it points the way to a radical redesign of fundamental parts of the system stack over the next 5-10 years. If you work in systems and you aren’t thinking about this stuff, you’re about to be lapped. The Case for Learned Index Structures: https://arxiv.org/pdf/1712.01208v1.pdf
Besides HN how can one find great papers like this? How did you find out about it?
The bitcoin white paper ( https://bitcoin.org/bitcoin.pdf )
Does anyone have any suggestions on finding CS papers worth reading beyond those papers listed here?
What topics are you interested in? Following the top ACM and IEEE conferences in that area is a good start! For example, I'm interested in human-computer interaction so I read CHI and UIST papers each year, and for software engineering I read ICSE and FSE.
I highly recommend people give this paper a read. I think it points the way to a radical redesign of fundamental parts of the system stack over the next 5-10 years. If you work in systems and you aren’t thinking about this stuff, you’re about to be lapped. The Case for Learned Index Structures: https://arxiv.org/pdf/1712.01208v1.pdf
https://www.sigarch.org/the-unreasonable-ineffectiveness-of-...
However, it's certainly possible that the time for this idea has come. Google is probably in the best position to apply it.
I will say that after having worked at Google for over a decade, some of it on data center performance, there are plenty of inefficiencies that have nothing to do with algorithms or code, but have more to do with very coarse-grained resource allocation. In other words, they are "boring management problems" rather than sexy CS problems.
I should also add that you're expanding the claims made in the paper, which appears to be a common mistake. If you look at the related work and citations, you'll see that it's mostly about B-Trees, bloom filters, and indices. But I have seen people generalizing this to "a revolution in systems research", which I don't believe is justified.
Indexed data structures are important but a revolution in them is not going to cause a revolution in all of systems. Off the top of my head, the general area of "scheduling" (in time and space) is probably more important and more potentially impactful.
Does anyone have any suggestions on finding CS papers worth reading beyond those papers listed here?
* What Developers Want and Need from Program Analysis - An Empirical Study * Weird machines, exploitability, and provable unexploitability * What You Corrupt Is Not What You Crash: Challenges in Fuzzing Embedded Devices
* What Developers ...: http://ieeexplore.ieee.org/document/7582770 (Sorry, no open version seems to be available) * Weird ...: http://ieeexplore.ieee.org/document/8226852 * What You ...: http://s3.eurecom.fr/docs/ndss18_muench.pdf
https://www.microsoft.com/en-us/research/wp-content/uploads/...
obtained by pasting the title into scholar.google.com
Earlier quoted context omitted.
What topics are you interested in? Following the top ACM and IEEE conferences in that area is a good start! For example, I'm interested in human-computer interaction so I read CHI and UIST papers each year, and for software engineering I read ICSE and FSE.
Ah, if only CHI and UIST had good papers these days. :/