[HN Gopher] KML: A machine learning framework for operating syst...
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KML: A machine learning framework for operating systems and storage
systems
Author : i_umit
Score : 32 points
Date : 2021-11-23 06:34 UTC (1 days ago)
(HTM) web link (github.com)
(TXT) w3m dump (github.com)
| gigalord wrote:
| Whenever I see buzz around "ML for Computer Systems" my first
| question is always "how debuggable is this?"
|
| A major benefit of the sophisticated heuristics and algorithms
| that power modern systems is the legion of experts who deeply
| understand how they work. When we see poor performance, a bit of
| digging and asking around will usually unearth some principled
| reasoning about how we can modify our programs to work well with
| the existing heuristics (think branch prediction).
|
| Unless we are careful, we lose this with an ML-based approach
| Q6T46nT668w6i3m wrote:
| For sure, I agree that interpretation is critical for computing
| systems like operating systems and compilers. I have been
| extremely pleased that most of the recent popular SysML
| research readily trades correctness for understandability.
| Likewise, I have also been pleased that correctness is often
| traded for performance.
| servytor wrote:
| Eh. I remember reading the furor about the Linux scheduler[0],
| and that was by the hands of man, my man.
|
| [0]:
| https://people.ece.ubc.ca/sasha/papers/eurosys16-final29.pdf
| omneity wrote:
| Remember, Skynet is Genisys.
|
| Joke aside, I'm not sure whether the tradeoff between
| "automatically tune parameters" and "nightmare to debug" is worth
| it.
|
| On the other hand it seems patterns like this are already
| deployed in hardware so maybe it will work out fine.
| i_umit wrote:
| You can find the related paper in arxiv:
| https://arxiv.org/abs/2111.11554
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