More from Tony Finch's blog
I have added syntax highlighting to my blog using tree-sitter. Here are some notes about what I learned, with some complaining. static site generator markdown ingestion highlighting incompatible?! highlight names class names styling code results future work frontmatter templates feed style highlight quality static site generator I moved my blog to my own web site a few years ago. It is produced using a scruffy Rust program that converts a bunch of Markdown files to HTML using pulldown-cmark, and produces complete pages from Handlebars templates. Why did I write another static site generator? Well, partly as an exercise when learning Rust. Partly, since I wrote my own page templates, I’m not going to benefit from a library of existing templates. On the contrary, it’s harder to create new templates that work with a general-purpose SSG than write my own simpler site-specific SSG. It’s miserable to write programs in template languages. My SSG can keep the logic in the templates to a minimum, and do all the fiddly stuff in Rust. (Which is not very fiddly, because my site doesn’t have complicated navigation – compared to the multilevel menus on www.dns.cam.ac.uk for instance.) markdown ingestion There are a few things to do to each Markdown file: split off and deserialize the YAML frontmatter find the <cut> or <toc> marker that indicates the end of the teaser / where the table of contents should be inserted augment headings with self-linking anchors (which are also used by the ToC) Before this work I was using regexes to do all these jobs, because that allowed me to treat pulldown-cmark as a black box: Markdown in, HTML out. But for syntax highlighting I had to be able to find fenced code blocks. It was time to put some code into the pipeline between pulldown-cmark’s parser and renderer. And if I’m using a proper parser I can get rid of a few regexes: after some hacking, now only the YAML frontmatter is handled with a regex. Sub-heading linkification and ToC construction are fiddly and more complicated than they were before. But they are also less buggy: markup in headings actually works now! Compared to the ToC, it’s fairly simple to detect code blocks and pass them through a highlighter. You can look at my Markdown munger here. (I am not very happy with the way it uses state, but it works.) highlighting As well as the tree-sitter-highlight documentation I used femark as an example implementation. I encountered a few problems. incompatible?! I could not get the latest tree-sitter-highlight to work as described in its documentation. I thought the current tree-sitter crates were incompatible with each other! For a while I downgraded to an earlier version, but eventually I solved the problem. Where the docs say, let javascript_language = tree_sitter_javascript::language(); They should say: let javascript_language = tree_sitter::Language::new( tree_sitter_javascript::LANGUAGE ); highlight names I was offended that tree-sitter-highlight seems to expect me to hardcode a list of highlight names, without explaining where they come from or what they mean. I was doubly offended that there’s an array of STANDARD_CAPTURE_NAMES but it isn’t exported, and doesn’t match the list in the docs. You mean I have to copy and paste it? Which one?! There’s some discussion of highlight names in the tree-sitter manual’s “syntax highlighting” chapter, but that is aimed at people who are writing a tree-sitter grammar, not people who are using one. Eventually I worked out that tree_sitter_javascript::HIGHLIGHT_QUERY in the tree-sitter-highlight example corresponds to the contents of a highlights.scm file. Each @name in highlights.scm is a highlight name that I might be interested in. In principle I guess different tree-sitter grammars should use similar highlight names in their highlights.scm files? (Only to a limited extent, it turns out.) I decided the obviously correct list of highlight names is the list of every name defined in the HIGHLIGHT_QUERY. The query is just a string so I can throw a regex at it and build an array of the matches. This should make the highlighter produce <span> wrappers for as many tokens as possible in my code, which might be more than necessary but I don’t have to style them all. class names The tree-sitter-highlight crate comes with a lightly-documented HtmlRenderer, which does much of the job fairly straightforwardly. The fun part is the attribute_callback. When the HtmlRenderer is wrapping a token, it emits the start of a <span then expects the callback to append whatever HTML attributes it thinks might be appropriate. Uh, I guess I want a class="..." here? Well, the highlight names work a little bit like class names: they have dot-separated parts which tree-sitter-highlight can match more or less specifically. (However I am telling it to match all of them.) So I decided to turn each dot-separated highlight name into a space-separated class attribute. The nice thing about this is that my Rust code doesn’t need to know anything about a language’s tree-sitter grammar or its highlight query. The grammar’s highlight names become CSS class names automatically. styling code Now I can write some simple CSS to add some colours to my code. I can make type names green, code span.hilite.type { color: #aca; } If I decide builtin types should be cyan like keywords I can write, code span.hilite.type.builtin, code span.hilite.keyword { color: #9cc; } results You can look at my tree-sitter-highlight wrapper here. Getting it to work required a bit more creativity than I would have preferred, but it turned out OK. I can add support for a new language by adding a crate to Cargo.toml and a couple of lines to hilite.rs – and maybe some CSS if I have not yet covered its highlight names. (Like I just did to highlight the CSS above!) future work While writing this blog post I found myself complaining about things that I really ought to fix instead. frontmatter I might simplify the per-page source format knob so that I can use pulldown-cmark’s support for YAML frontmatter instead of a separate regex pass. This change will be easier if I can treat the html pages as Markdown without mangling them too much (is Markdown even supposed to be idempotent?). More tricky are a couple of special case pages whose source is Handlebars instead of Markdown. templates I’m not entirely happy with Handlebars. It’s a more powerful language than I need – I chose Handlebars instead of Mustache because Handlebars works neatly with serde. But it has a dynamic type system that makes the templates more error-prone than I would like. Perhaps I can find a more static Rust template system that takes advantage of the close coupling between my templates and the data structure that describes the web site. However, I like my templates to be primarily HTML with a sprinkling of insertions, not something weird that’s neither HTML nor Rust. feed style There’s no CSS in my Atom feed, so code blocks there will remain unstyled. I don’t know if feed readers accept <style> tags or if it has to be inline styles. (That would make a mess of my neat setup!) highlight quality I’m not entirely satisfied with the level of detail and consistency provided by the tree-sitter language grammars and highlight queries. For instance, in the CSS above the class names and property names have the same colour because the CSS highlights.scm gives them the same highlight name. The C grammar is good at identifying variables, but the Rust grammar is not. Oh well, I guess it’s good enough for now. At least it doesn’t involve Javascript.
One of the neat things about the PCG random number generator by Melissa O’Neill is its use of instruction-level parallelism: the PCG state update can run in parallel with its output permutation. However, PCG only has a limited amount of ILP, about 3 instructions. Its overall speed is limited by the rate at which a CPU can run a sequence where the output of one multiply-add feeds into the next multiply-add. … Or is it? With some linear algebra and some AVX512, I can generate random numbers from a single instance of pcg32 at 200 Gbit/s on a single core. This is the same sequence of random numbers generated in the same order as normal pcg32, but more than 4x faster. You can look at the benchmark in my pcg-dxsm repository. skip ahead the insight multipliers trying it out results skip ahead One of the slightly weird features that PCG gets from its underlying linear congruential generator is “seekability”: you can skip ahead k steps in the stream of random numbers in log(k) time. The PCG paper (in section 4.3.1) cites Forrest Brown’s paper, random numbers with arbitrary strides, which explains that the skip-ahead feature is useful for reproducibility of monte carlo simulations. But what caught my eye is the skip-ahead formula. Rephrased in programmer style, state[n+k] = state[n] * pow(MUL, k) + inc * (pow(MUL, k) - 1) / (MUL - 1) the insight The skip-ahead formula says that we can calculate a future state using a couple of multiplications. The skip-ahead multipliers depend only on the LCG multiplier, not on the variable state, nor on the configurable increment. That means that for a fixed skip ahead, we can precalculate the multipliers before compile time. The skip-ahead formula allows us to unroll the PCG data dependency chain. Normally, four iterations of the PCG state update look like, state0 = rng->state state1 = state0 * MUL + rng->inc state2 = state1 * MUL + rng->inc state3 = state2 * MUL + rng->inc state4 = state3 * MUL + rng->inc rng->state = state4 With the skip-ahead multipliers it looks like, state0 = rng->state state1 = state0 * MULs1 + rng->inc * MULi1 state2 = state0 * MULs2 + rng->inc * MULi2 state3 = state0 * MULs3 + rng->inc * MULi3 state4 = state0 * MULs4 + rng->inc * MULi4 rng->state = state4 These state calculations can be done in parallel using NEON or AVX vector instructions. The disadvantage is that calculating future states in parallel requires more multiplications than doing so in series, but that’s OK because modern CPUs have lots of ALUs. multipliers The skip-ahead formula is useful for jumping ahead long distances, because (as Forrest Brown explained) you can do the exponentiation in log(k) time using repeated squaring. (The same technique is used in for modexp in RSA.) But I’m only interested in the first few skip-ahead multipliers. I’ll define the linear congruential generator as: lcg(s, inc) = s * MUL + inc Which is used in PCG’s normal state update like: rng->state = lcg(rng->state, rng->inc) To precalculate the first few skip-ahead multipliers, we iterate the LCG starting from zero and one, like this: MULs0 = 1 MULs1 = lcg(MULs0, 0) MULs2 = lcg(MULs1, 0) MULi0 = 0 MULi1 = lcg(MULi0, 1) MULi2 = lcg(MULi1, 1) My benchmark code’s commentary includes a proof by induction, which I wrote to convince myself that these multipliers are correct. trying it out To explore how well this skip-ahead idea works, I have written a couple of variants of my pcg32_bytes() function, which simply iterates pcg32 and writes the results to a byte array. The variants have an adjustable amount of parallelism. One variant is written as scalar code in a loop that has been unrolled by hand a few times. I wanted to see if standard C gets a decent speedup, perhaps from autovectorization. The other variant uses the GNU C portable vector extensions to calculate pcg32 in an explicitly parallel manner. The benchmark also ensures the output from every variant matches the baseline pcg32_bytes(). results The output from the benchmark harness lists: the function variant either the baseline version or uN for a scalar loop unrolled N times or xN for vector code with N lanes its speed in bytes per nanosecond (aka gigabytes per second) its performance relative to the baseline There are small differences in style between the baseline and u1 functions, but their performance ought to be basically the same. Apple clang 16, Macbook Pro M1 Pro. This compiler is eager and fairly effective at autovectorizing. ARM NEON isn’t big enough to get a speedup from 8 lanes of parallelism. __ 3.66 bytes/ns x 1.00 u1 3.90 bytes/ns x 1.07 u2 6.40 bytes/ns x 1.75 u3 7.66 bytes/ns x 2.09 u4 8.52 bytes/ns x 2.33 x2 7.59 bytes/ns x 2.08 x4 10.49 bytes/ns x 2.87 x8 10.40 bytes/ns x 2.84 The following results were from my AMD Ryzen 9 7950X running Debian 12 “bookworm”, comparing gcc vs clang, and AVX2 vs AVX512. gcc is less keen to autovectorize so it doesn’t do very well with the unrolled loops. (Dunno why u1 is so much slower than the baseline.) gcc 12.2 -march=x86-64-v3 __ 5.57 bytes/ns x 1.00 u1 5.13 bytes/ns x 0.92 u2 5.03 bytes/ns x 0.90 u3 7.01 bytes/ns x 1.26 u4 6.83 bytes/ns x 1.23 x2 3.96 bytes/ns x 0.71 x4 8.00 bytes/ns x 1.44 x8 12.35 bytes/ns x 2.22 clang 16.0 -march=x86-64-v3 __ 4.89 bytes/ns x 1.00 u1 4.08 bytes/ns x 0.83 u2 8.76 bytes/ns x 1.79 u3 10.43 bytes/ns x 2.13 u4 10.81 bytes/ns x 2.21 x2 6.67 bytes/ns x 1.36 x4 12.67 bytes/ns x 2.59 x8 15.27 bytes/ns x 3.12 gcc 12.2 -march=x86-64-v4 __ 5.53 bytes/ns x 1.00 u1 5.53 bytes/ns x 1.00 u2 5.55 bytes/ns x 1.00 u3 6.99 bytes/ns x 1.26 u4 6.79 bytes/ns x 1.23 x2 4.75 bytes/ns x 0.86 x4 17.14 bytes/ns x 3.10 x8 20.90 bytes/ns x 3.78 clang 16.0 -march=x86-64-v4 __ 5.53 bytes/ns x 1.00 u1 4.25 bytes/ns x 0.77 u2 7.94 bytes/ns x 1.44 u3 9.31 bytes/ns x 1.68 u4 15.33 bytes/ns x 2.77 x2 9.07 bytes/ns x 1.64 x4 21.74 bytes/ns x 3.93 x8 26.34 bytes/ns x 4.76 That last result is pcg32 generating random numbers at 200 Gbit/s.
The International Obfuscated C Code Contest has a newly revamped web site, and the Judges have announced the 28th contest, to coincide with its 40th anniversary. (Or 41st?) The Judges have also updated the archive of past winners so that as many of them as possible work on modern systems. Accordingly, I took a look at my 1998 winner to see how much damage time hath wrought. When it is built, my program needs to go through the C preprocessor twice. There are a few reasons: It’s part of coercing the C compiler into compiling OFL, an obfuscated functional language. OFL has keywords l and b, short for let and be, so for example the function for constructing a pair is defined as l pair b (BB (B (B K)) C CI) In a less awful language that might be written let pair = λx λy λf λg (f x y) Anyway, the first pass of the C preprocessor turns a l (let) declaration into a macro #define pair b (BB (B (B K)) C CI) And the second pass expands the macros. (There’s a joke in the README that the OFL compiler has one optimization, function inlining (which is actually implemented by cpp macro expansion) but in fact inlining harms the performance of OFL.) The smaller the OFL interpreter, the more space there is for the program written in OFL. In the 1998 IOCCC rules, #define cost 7 characters, whereas l cost only one. I think the modern rules don’t count C or cpp keywords so there’s less reason to use this stupid trick to save space. Running the program through cpp twice is a horrible abuse of C and therefore just the kind of joke that the IOCCC encourages. (In fact the Makefile sends the program through cpp three times, twice explicitly and once as part of compiling to machine code. This is deliberately gratuitous, INABIAF.) There were a couple of ways this silliness caused problems. Modern headers are sensitive to which version of the C standard is in effect, wrt things like restrict keywords in standard library function declarations. The extra preprocessor invocations needed to be fixed to use consistent -std= options so that the final compilation doesn’t encounter language features from the future. Newer gcc emits #line directives around macro expansions. This caused problems for the declaration l ef E(EOF) which defines ef as a primitive value equal to EOF. After preprocessing this became #define ef E( #line 1213 "stdio.h" (-1) #line 69 "fanf.c" ) so the macro definition got truncated. The fix was to process the #include directives in the second preprocessor pass rather than the first. I vaguely remember some indecision when writing the program about whether to #include in the first or second pass, in particular whether preprocessing the headers twice would lead to trouble. First pass #include seemed to work and was shorter so that was what the original submission did. There’s one further change. The IOCCC Judges are trying to avoid compiler warnings about nonstandard arguments to main. To save a few characters, my entry had int main(int c) { ... } but the argument c isn’t used so I just removed it. The build commands still print “This may take some time to complete”, because in the 1990s if you tried to compile with optimization you would have been waiting a long time, if it completed at all. The revamped Makefile uses -O3, which takes gcc over 30 seconds and half a gigabyte of RAM. Quite a lot for less than 2.5 KiB of C!
D’oh, I lost track of a bug report that should have been fixed in nsnotifyd-2.2. Thus, hot on the heels of [the previous release][prev], here’s nsnotifyd-2.3. Sorry for causing extra work to my uncountably many users! The nsnotifyd daemon monitors a set of DNS zones and runs a command when any of them change. It listens for DNS NOTIFY messages so it can respond to changes promptly. It also uses each zone’s SOA refresh and retry parameters to poll for updates if nsnotifyd does not receive NOTIFY messages more frequently. It comes with a client program nsnotify for sending notify messages. This nsnotifyd-2.3 release includes some bug fixes: When nsnotifyd receives a SIGINT or SIGTERM while running the command, it failed to handle it correctly. Now it exits promptly. Many thanks to Athanasius for reporting the bug! Miscellaneous minor code cleanup and compiler warning suppression. Thanks also to Dan Langille who sent me a lovely appreciation: Now that I think of it, nsnotifyd is in my favorite group of software. That group is software I forget I’m running, because they just run and do the work. For years. I haven’t touched, modified, or configured nsnotifyd and it just keeps doing the job.
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Picasso got it right: Great artists steal. Even if he didn’t actually say it, and we all just repeat the quote because Steve Jobs used it. Because it strikes at the heart of creativity: None of it happens in a vacuum. Everything is inspired by something. The best ideas, angles, techniques, and tones are stolen to build everything that comes after the original. Furthermore, the way to learn originality is to set it aside while you learn to perfect a copy. You learn to draw by imitating the masters. I learned photography by attempting to recreate great compositions. I learned to program by aping the Ruby standard library. Stealing good ideas isn’t a detour on the way to becoming a master — it’s the straight route. And it’s nothing to be ashamed of. This, by the way, doesn’t just apply to art but to the economy as well. Japan became an economic superpower in the 80s by first poorly copying Western electronics in the decades prior. China is now following exactly the same playbook to even greater effect. You start with a cheap copy, then you learn how to make a good copy, and then you don’t need to copy at all. AI has sped through the phase of cheap copies. It’s now firmly established in the realm of good copies. You’re a fool if you don’t believe originality is a likely next step. In all likelihood, it’s a matter of when, not if. (And we already have plenty of early indications that it’s actually already here, on the edges.) Now, whether that’s good is a different question. Whether we want AI to become truly creative is a fair question — albeit a theoretical or, at best, moral one. Because it’s going to happen if it can happen, and it almost certainly can (or even has). Ironically, I think the peanut gallery disparaging recent advances — like the Ghibli fever — over minor details in the copying effort will only accelerate the quest toward true creativity. AI builders, like the Japanese and Chinese economies before them, eager to demonstrate an ability to exceed. All that is to say that AI is in the "Good Copy" phase of its creative evolution. Expect "The Great Artist" to emerge at any moment.