Hardware Is Boring

 Upgrading my home internet connection from 100 to 600Mbit didn't make as much of a difference as I expected. speedtest.net reported barely over 300Mbit on ethernet or WiFi. Connecting directly through the modem (some Huawei) gave the expected speeds. Turns out, the Asus RT-AC68U has a setting in Advanced Settings / LAN: "NAT Acceleration" was disabled and setting it to "Auto" (the only other option) enabled "CTF (Cut Through Forwarding)". This was all that was needed to get the same speeds through the RT-AC68U as directly from the modem.

Main installation went smoothly, I installed gnome 3 and xfce, at boot it defaults to gnome. No sudo The installation process prompts for a root and user password and without thinking much, I set both. This resulted in my default user not being allowed to run commands with sudo. Add the default user to the sudoers group: # log as root, as the user is not allowed to use sudo yet $ su # add user to the sudo group $ /sbin/usermod -a -G sudo <username> It is necessary to log out for changes to take effect. No sound My Asus Xonar is supported on Linux (as of early 2019), however the installation default sets the card to stereo and probably uses a different output plug. In my case, this is easily solved by running alsamixer and changing the analog out settings to multichannel. Then store the settings:  $ /sbin/alsactl --file ~/.config/asound.state store and I make it the system default:  $ sudo cp ~/.config/asound.state /var/lib/alsa/asound.state After reboot, so

I've just got a Nikkor 105mm f/2.8G micro lens and can finally try out how the Z7 performs with the FTZ adapter. Picture quality is great - no concerns whatsoever. Not everything is perfect, though. With the smaller body of the Nikon mirrorless, the tripod plate (Manfrotto) extends out of the body and gets in the way of the adapter. I think Nikon wants us to put the tripod plate on the FTZ adapter instead of the camera body. This is inconvenient if you'd like to have the tripod plate installed with all lenses. I use the Peak Design wrist strap, which attaches to the tripod plate. I'd like to keep the wrist strap always on camera, since it makes the camera much more comfortable to hold. Now whenever I'm switching lenses from native to adapted, I have to unscrew the tripod plate and put it back on with the new lens What used to be a couple seconds swap, turns to a minute of messing around. I could buy a second plate and keep it on the FTZ adapter, but that only solves h

Pairing with a Pixel 2 XL was more complicated than should have been. Use the snapbridge app, don't pair in settings Try different order of approvals - approve on phone first, then 1 second later on the camera (if it doesn't work, try the other way round). Approving pairing on both at the same time doesn't work, the pairing fails. Wifi pairing worked immediately, however you lose location tagging, which for me is the main/only reason for pairing the camera to the phone.

As mentioned in the z440 post , the workstation comes with a NVIDIA Quadro K5200. I've been a happy user of AMD hardware since Radeon HD 4850 (upgraded 5870 and R9 390 later). Unfortunately, tensorflow only supports Cuda - possibly due to missing OpenCL support in Eigen . Is it worth switching just for that? I did a few experiments: CPU (8core Xeon E5-1680v3) real 8m24.991s user 104m13.048s sys  0m38.772s All CPUs ~80% usage GPU (NVIDIA Quadro K5200) real 2m12.990s user 2m47.136s sys  0m30.500s All CPUs ~20% usage I think it's worth it - about 4x improvement by using the GPU vs a high end 8 core Xeon. And this GPU is 2 generations back - a GTX 1080 or newer will probably give an even higher benefit. So for now, I'll stick with NVIDIA.

After years of self-built computers, I decided to get a workstation at home. I got a HP z440 - the 2015 single socket HP workstation. From their workstation line, it's the entry-level; the z640 and z840 are dual socket and allow for more expansion and PCIe cards. It's plenty fast; the E5 1680v3  CPU has 8 cores at 3.2GHz, up to 3.8GHz with turbo. You can get faster per-core performance with a high-clocked i7, but 8 cores are great when encoding video or compiling code. I think ECC memory makes sense. Memory errors are not very frequent, but given the small premium paid, it's well worth it. Even Google, who started with as-cheap-as-possible servers in their datacenters now uses ECC memory in their servers : The conclusion we draw is that error correcting codes are crucial for reducing the large number of memory errors to a manageable number of uncorrectable errors. Only 2 out of 8 slots are filled, which looks weird - after all it comes with 32GB. I don't think I