Wandering Thoughts archives

2018-10-28

Link: HiDPI on dual 4K monitors with Linux

Vincent Bernat's article HiDPI on dual 4K monitors with Linux (via) is about what you'd expect it to be about and is, as they say, relevant to my interests. Especially relevant to me is the section on HiDPI support on Linux with X11, which runs down a collection of issues and contains a very useful chart about what is supported in what application and toolkit, which added some information that I hadn't known.

Note that Bernat's experience with xterm and rxvt don't match mine, perhaps because we're setting the X-level DPI information in somewhat different ways. My experience, as covered here, is that plain X applications using XFT fonts scale them appropriately once you get the DPI set everywhere (ie, if you tell xterm to use Monospace-12, you will get an actual 12 point size on your HiDPI monitor, not 12 points at 96 DPI and thus tiny fonts). If you use bitmap fonts, though, you're in trouble and unfortunately xterm still uses those by default for some things, like its popup menus.

(It's the nature of these articles to become out of date over time as HiDPI support improves and changes, but it's still a useful snapshot and some of these applications will probably never change.)

HiDPIOnDualMonitors written at 16:17:29; Add Comment

2018-10-18

Link: Vectorized Emulation [of CPUs and virtual machines]

Vectorized Emulation: Hardware accelerated taint tracking at 2 trillion instructions per second (via) is about, well, let me quote from the introduction rather than try to further summarize it:

In this blog I’m going to introduce you to a concept I’ve been working on for almost 2 years now. Vectorized emulation. The goal is to take standard applications and JIT them to their AVX-512 equivalent such that we can fuzz 16 VMs at a time per thread. The net result of this work allows for high performance fuzzing (approx 40 billion to 120 billion instructions per second [the 2 trillion clickbait number is theoretical maximum]) depending on the target, while gathering differential coverage on code, register, and memory state.

Naturally you need to do all sorts of interesting tricks to make this work. The entry is an overview, and the author is going to write more entries later on the details of various aspects of it, which I'm certainly looking forward to even if I'm not necessarily going to fully follow the details.

I found this interesting both by itself and for giving me some more insight into modern SIMD instructions and what goes into using them. SIMD and GPU computing feel like something that I should understand some day.

(I find SIMD kind of mind bending and I've never really dug into how modern x86 machines do this sort of stuff and what you use it for.)

VectorizedEmulation written at 20:06:28; Add Comment


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