Can someone familiar with performance of LLMs please tell me how important this is to the overall perf? I'm interested in looking into optimizing tokenizers, and have not yet run the measurements. I would have assumed that the cost is generally dominated by matmuls but am encouraged by the reception of this post in the comments.
Readit Newssuperlopuh commented on Show HN: TokenDagger – A tokenizer faster than OpenAI's Tiktoken github.com/M4THYOU/TokenD... · Posted by u/matthewolfe
superlopuh commented on The Zed Debugger Is Here zed.dev/blog/debugger... · Posted by u/SupremumLimit
I really want to switch to Zed from Cursor but the battery usage for my Python project with Pyright is unjustifiable. There are issues for this on GitHub and I'm just sad that the team isn't prioritising this more.
$ traceroute bad.horse --resolve-hostnames
traceroute to bad.horse (162.252.205.157), 64 hops max
1 192.168.218.150 (_gateway) 0.483ms 0.580ms 0.548ms
2 * * *
3 172.24.41.146 (172.24.41.146) 35.920ms 29.950ms 30.014ms
4 * * *
5 172.24.195.1 (172.24.195.1) 30.097ms 24.669ms 28.539ms
6 172.24.195.10 (172.24.195.10) 30.086ms 40.166ms 31.028ms
7 80.233.113.58 (80.233.113.58) 29.500ms 23.967ms 43.113ms
8 185.6.36.58 (3ireland.ipv4.sw01.inex.ie) 33.895ms 24.975ms 34.959ms
9 185.6.36.86 (inex-01.ixp.dubie.as8220.net) 22.309ms 19.770ms 19.886ms
10 217.163.150.193 (1-1-c21-1.ear2.Dublin6.Level3.net) 36.257ms 41.033ms 39.510ms
11 4.69.218.54 (ae1.8.bar4.Toronto1.net.lumen.tech) 113.272ms 112.558ms 126.953ms
12 4.16.51.30 (level3-gw.core02.tor1.prioritycolo.com) 115.108ms 123.140ms 109.593ms
13 67.223.96.90 (67.223.96.90) 121.502ms 119.570ms 121.227ms
14 162.252.205.130 (bad.horse) 113.161ms 116.657ms 133.119ms
15 162.252.205.131 (bad.horse) 119.704ms 128.309ms 116.360ms
16 162.252.205.132 (bad.horse) 125.646ms 125.660ms 130.224ms
17 162.252.205.133 (bad.horse) 132.803ms 122.749ms 126.137ms
18 162.252.205.134 (he.rides.across.the.nation) 133.363ms 132.422ms 145.895ms
19 162.252.205.135 (the.thoroughbred.of.sin) 154.954ms 136.148ms 142.345ms
20 162.252.205.136 (he.got.the.application) 158.392ms 151.055ms 148.331ms
21 162.252.205.137 (that.you.just.sent.in) 156.020ms 146.436ms 159.945ms
22 162.252.205.138 (it.needs.evaluation) 167.918ms 157.544ms 171.169ms
23 162.252.205.139 (so.let.the.games.begin) 161.076ms 173.227ms 162.558ms
24 162.252.205.140 (a.heinous.crime) 182.682ms 175.853ms 167.833ms
25 162.252.205.141 (a.show.of.force) 186.703ms 222.181ms 590.896ms
26 162.252.205.142 (a.murder.would.be.nice.of.course) 602.997ms 175.406ms 179.810ms
27 162.252.205.143 (bad.horse) 196.847ms 187.985ms 190.071ms
28 162.252.205.144 (bad.horse) 193.553ms 184.281ms 196.659ms
29 162.252.205.145 (bad.horse) 187.502ms 195.218ms 194.829ms
30 162.252.205.146 (he-s.bad) 207.271ms 194.007ms 200.673ms
31 162.252.205.147 (the.evil.league.of.evil) 204.942ms 200.672ms 199.780ms
32 162.252.205.148 (is.watching.so.beware) 202.099ms 214.924ms 213.818ms
33 162.252.205.149 (the.grade.that.you.receive) 233.816ms 220.345ms 207.857ms
34 162.252.205.150 (will.be.your.last.we.swear) 229.135ms 224.107ms 221.103ms
35 162.252.205.151 (so.make.the.bad.horse.gleeful) 272.907ms 241.476ms 222.392ms
36 162.252.205.152 (or.he-ll.make.you.his.mare) 250.987ms 224.407ms 223.308ms
37 162.252.205.153 (o_o) 246.874ms 234.844ms 234.278ms
38 162.252.205.154 (you-re.saddled.up) 269.535ms 241.234ms 238.331ms
39 162.252.205.155 (there-s.no.recourse) 243.611ms 244.293ms 236.522ms
40 162.252.205.156 (it-s.hi-ho.silver) 241.793ms 268.596ms 281.158ms
41 162.252.205.157 (signed.bad.horse) 286.400ms 267.379ms 280.296msBeautiful
superlopuh commented on Solving LinkedIn Queens with SMT buttondown.com/hillelwayn... · Posted by u/azhenley
I tried to write a programming language that compiles to SAT many years ago: https://sentient-lang.org/
I love that language and frequently show it to people. I'm sad to see that my local install doesn't work any more. I actually used it to solve a puzzle in Evoland 2 that I'm relatively sure was added as a joke, and is not solvable in a reasonable time without a solver. I'm actually doing a PhD in compilers right now, and would love to chat about sentient if you have the time. My email is sasha@lopoukhine.com.
traceroute bad.horse
I just get a bunch of stars.
superlopuh commented on Solving a “Layton Puzzle” with Prolog buttondown.com/hillelwayn... · Posted by u/Tomte
I once used Sentient[0] to solve a similar puzzle in a different game that I think made a puzzle that required a constraint solver as a joke on the player. I'm a bit saddened to see that the repo hasn't been updated in 6 years, and a node update broke the binary installed on my computer, I find it a much more ergonomic environment than Prolog, hopefully someone else will pick up the mantle.
Deleted Comment
superlopuh commented on Roc rewrites the compiler in Zig gist.github.com/rtfeldman... · Posted by u/todsacerdoti
I wanted to like Rust (memory safety and performance - what's not to like?) but both of my experiments with it ended in frustration. It seemed a way too complex language for what I needed.
Recently, a coworker of mine made a great observation that made everything clear to me. I was looking for a replacement for C, but Rust is actually a replacement for C++. Totally different beast - powerful but complex. I need to see if Zig is any closer to C in spirit.
My experience with Zig is that it's also a plausible replacement for C++
I wonder if this question can attract any MLIR people to answer my question:
From Chris Lattner's descriptions of LLVM vs MLIR in various podcasts, it seems like LLVM is often used as a backend for MLIR, but only because so much work has been put into optimizing in LLVM. It also seems like MLIR is strictly a superset of LLVM in terms of capabilities.
Here's my question: It seems inevitable that people will eventually port all LLVM's smarts directly into MLIR, and remove the need to shift between the two. Is that right?
I know of a few projects looking in that direction, each optimising for different things, and none getting near the capability of LLVM, which is going to take some time. I spoke with some of the core MLIR developers about this, and they're generally open to the notion, but it's going to take a lot of volunteer effort to get there, and it's not clear who the sherpa will be, especially given the major sponsors of the LLVM project aren't in a particular hurry. If you're interested in this feel free to look our paper up in a week or two, we've had a bit of trouble uploading it to arxiv but should be ready soon.
https://2025.cgo.org/details/cgo-2025-papers/39/A-Multi-Leve...
Here's a quick pres from the last dev meeting on how this can be leveraged to compile NNs to a RISC-V-based accelerator core: https://www.youtube.com/watch?v=RSTjn_wA16A&t=1s