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#time

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Okay, it's time for the big #ntp and #ptp wrap-up post. My week-long timing project spiraled out of control and turned into a two month monster, complete with 7 (ish?) GPS timing devices, 14 different test NICs, and a dozen different test systems.

What'd I learn along the way? See scottstuff.net/posts/2025/06/1 for the full list (and links to measurements and experimental results), but the top few are:

1. It's *absolutely* possible to get single-digit nanosecond time syncing with NTP between a pair of Linux systems with Chrony in a carefully-constructed test environment. Outside of a lab, 100-500 ns is probably more reasonable with NTP on a real network, and even that requires carefully selected NICs. But single-digit nanoseconds *are* possible. NTP isn't just for millisecond-scale time syncing.
2. Generally, PTP on the same hardware shows similar performance to NTP in a lab setting, with a bit less jitter. I'd expect it to scale *much* better in a real network, though. However, PTP mostly requires higher-end hardware (especially switches) and a bit more engineering work. Plus many older NICs just aren't very good at PTP (especially ConnectX-3s).
3. Intel's NICs, *especially* the E810 and to a lesser extent the i210 are very good at time accuracy. Unfortunately their X710 isn't as good, and the i226 is mixed. Mellanox is less accurate in my tests, with 200ns of skew, but still far better than Realtek and other consumer NICs.
4. GPS receivers aren't really *that* accurate. Even good receivers "wander" around 5-30 ns from second to second.
5. Antennas are critical. The cheap, flat window ones aren't a good choice for timing work. (Also, they're not actually supposed to be used in windows, they generally want a ground plane).
6. Your network probably has more paths with asymmetrical timing in it than you'd have expected. ECMP, LACP, and 2.5G/5G/10Gbase-T probably all negatively impact your ability to get extremely accurate time.

Anyway, it's been a fun journey. I had a good #time.

scottstuff.net · Timing ConclusionsThis is the 13th article that I’ve written lately on NTP and PTP timing with Linux. I set out to answer a couple questions for myself and ended up spending two months swimming in an ocean of nanosecond-scale measurements. When I started, I saw a lot of misinformation about NTP and PTP online. Things like: Conventional wisdom said that NTP was good for millisecond-scale timing accuracy. I expected that to be rather pessimistic, and expected to see low microsecond to high nanosecond-range syncing with Chrony, at least under controlled circumstances.In a lab environment, it’s possible to get single-digit nanosecond time skew out of Chrony. With a less-contrived setup, 500 ns is probably a better goal. In any case “milliseconds” is grossly underselling what’s possible. Conventional wisdom also said that PTP was better than NTP when you really cared about time, but that it was more difficult to use and made more requirements on hardware.You know, conventional wisdom is actually right sometimes. PTP is somewhat more difficult to set up and really wants to have hardware support from every switch and every NIC, but once you have that it’s pretty solid. Along the way I tested NTP and PTP “in the wild” on my network, built a few new GPS-backed NTP (and PTP) servers, collected a list of all known NICs with timing features,Specifically GNSS modules or PPS inputs. built a testing environment for measuring time-syncing accuracy to within a few nanoseconds, tested the impact of various Chrony polling settings, tested 14 different NICs for time accuracy, and tested how much added latency PTP-aware switches add. I ran into problems with PTP on Mellanox/nVidia ConnectX-4 and Intel X710 NICs.Weird stuff. The X710 doesn’t seem to like PTP v2.1, and it doesn’t like it when you ask it to timestamp packets too frequently. I fought with Raspberry Pis. I tested NICs until my head hurt. I fought with statistics. This little project that I’d expected to last most of a week has now dragged on for two months. It’s finally time to summarize what I’ve learned and celebrate The End Of Time.
Continued thread

You Need Much Less #Memory than #Time

“Just as I was complaining that we haven't seen many surprising breakthroughs in complexity recently, we get an earthquake of a result to start the year, showing that all #algorithms can be simulated using considerable less memory than the time of the original algorithm. You can #reuse space (#memory) but you can't reuse time, and this new result from #RyanWilliams in an upcoming #STOC paper provides the first stark difference”

<blog.computationalcomplexity.o>

blog.computationalcomplexity.orgYou Need Much Less Memory than TimeJust as I was complaining that we haven't seen many surprising breakthroughs in complexity recently, we get an earthquake of a result to st...

Let's try this again because not everyone's votes were being registered the first time around.

I was just noticing all the clocks that could potentially be used in my home: The microwave, the stove, thermostat, computers, mobile devices, watches, coffee maker, bedroom alarm clocks, wall clocks, radios, etc. There are clocks everywhere, but I don't use most of them for the time. Heck, I don't even bother to set some of them.

#Poll #Time #Clock

→ If nothing is curated, how do we find things?
tadaima.bearblog.dev/if-nothin

“I always felt like social media creates an illusion of convenience. Think of how much time it takes to stay on top of things. To stay on top of music or film. Think of how much time it takes these days, how much hunting you have to do. Although technology has made information vast and reachable, it's also turned the entire #internet into a sludge pile.”

Tadaima.If nothing is curated, how do we find things?Bjork is currently promoting a new concert film being released called . She's been releasing new photoshoots and interviews almost every day for the past two...
#find#social#media

Proud and excited to say that the @tcdh will be present at #DH2025 @dh2025 with no less than nine contributions! Hope to meet many of you there!

Topics and issues include #collaboration, #wikidata, #FAIR, #multilingualism, #stylometry, #FrenchNovel, #Keyness, #Time, #LinkedOpenData, #Poetry #ChatGPT, #WineLabels, @CLSinfra and much more!

Check out the list here: tcdh.uni-trier.de/en/event/dh2

@cndukeli @MariaHinzmann @dudarjulia @jojoweis #DigitalHumanities