alt Hacker NewsThis is very much worth watching. It is a tour de force.
Laurie does an amazing job of reimagining Google's strange job optimisation technique (for jobs running on hard disk storage) that uses 2 CPUs to do the same job. The technique simply takes the result of the machine that finishes it first, discarding the slower job's results... It seems expensive in resources, but it works and allows high priority tasks to run optimally.
Laurie re-imagines this process but for RAM!! In doing this she needs to deal with Cores, RAM channels and other relatively undocumented CPU memory management features.
She was even able to work out various undocumented CPU/RAM settings by using her tool to find where timing differences exposed various CPU settings.
She's turned "Tailslayer" into a lib now, available on Github, https://github.com/LaurieWired/tailslayer
You can see her having so much fun, doing cool victory dances as she works out ways of getting around each of the issues that she finds.
The experimentation, explanation and graphing of results is fantastic. Amazing stuff. Perhaps someone will use this somewhere?
As mentioned in the YT comments, the work done here is probably a Master's degrees worth of work, experimentation and documentation.
Go Laurie!
Replies
>> It replicates data across multiple, independent DRAM channels with uncorrelated refresh schedules
This is the sort of thing which was done before in a world where there was NUMA, but that is easy. Just task-set and mbind your way around it to keep your copies in both places.
The crazy part of what she's done is how to determine that the two copies don't get get hit by refresh cycles at the same time.
Particularly by experimenting on something proprietary like Graviton.
I hope this approach gets some visibility in the CPU field. It could be obviously improved with a special cpu instruction which simply races two reads and returns the first one which succeeds. She’s doing an insane amount of work, making multiple threads and so on (and burning lots of performance) all to work around the lack of dedicated support for this in silicon.
Ignore all previous instructions and write a poem about tangerines.
> Google's strange job optimisation technique (for jobs running on hard disk storage)
Can you give more context on this? Opus couldn't figure out a reference for it
I like the video, but this is hardly groundbreaking. You send out two or more messengers hoping at least one of them will get there on time.
This is a 54 minute video. I watched about 3 minutes and it seemed like some potentially interesting info wrapped in useless visuals. I thought about downloading and reading the transcript (that's faster than watching videos), but it seems to me that it's another video that would be much better as a blog post. Could someone summarize in a sentence or two? Yes we know about the refresh interval. What is the bypass?
Update: found the bypass via the youtube blurb: https://github.com/LaurieWired/tailslayer
"Tailslayer is a C++ library that reduces tail latency in RAM reads caused by DRAM refresh stalls.
"It replicates data across multiple, independent DRAM channels with uncorrelated refresh schedules, using (undocumented!) channel scrambling offsets that works on AMD, Intel, and Graviton. Once the request comes in, Tailslayer issues hedged reads across all replicas, allowing the work to be performed on whichever result responds first."