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Software freedom isn't about licenses -- it's about power.

from On Life and Lisp [alt+shift+b] in programming

A restrictive end-user license agreement is one way a company can exert power over the user. When the free software movement was founded thirty years ago, these restrictive licenses were the primary user-hostile power dynamic, so permissive and copyleft licenses emerged as synonyms to software freedom. Licensing does matter; user autonomy is lost with subscription models, revocable licenses, binary-only software, and onerous legal clauses. Yet these issues pertinent to desktop software do not scratch the surface of today’s digital power dynamics. Today, companies exert power over their users by: tracking, selling data, psychological manipulation, intrusive advertising, planned obsolescence, and hostile Digital “Rights” Management (DRM) software. These issues affect every digital user, technically inclined or otherwise, on desktops and smartphones alike. The free software movement promised to right these wrongs via free licenses on the source code, with adherents arguing free licenses provide immunity to these forms of malware since users could modify the code. Unfortunately most users lack the resources to do so. While the most egregious violations of user freedom come from companies publishing proprietary software, these ills can remain unchecked even in open source programs, and not all proprietary software exhibits these issues. The modern browser is nominally free software containing the trifecta of telemetry, advertisement, and DRM; a retro video game is proprietary software but relatively harmless. As such, it’s not enough to look at the license. It’s not even enough to consider the license and a fixed set of issues endemic to proprietary software; the context matters. Software does not exist in a vacuum. Just as proprietary software tends to integrate with other proprietary software, free software tends to integrate with other free software. Software freedom in context demands a gentle nudge towards software in user interests, rather than corporate...
28th Mar 2021

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Dissecting the Apple M1 GPU, the end

In 2020, Apple released the M1 with a custom GPU. We got to work reverse-engineering the hardware and porting Linux. Today, you can run Linux on a range of M1 and M2 Macs, with almost all hardware working: wireless, audio, and full graphics acceleration. Our story begins in December 2020, when Hector Martin kicked off Asahi Linux. I was working for Collabora working on Panfrost, the open source Mesa3D driver for Arm Mali GPUs. Hector put out a public call for guidance from upstream open source maintainers, and I bit. I just intended to give some quick pointers. Instead, I bought myself a Christmas present and got to work. In between my university coursework and Collabora work, I poked at the shader instruction set. One thing led to another. Within a few weeks, I drew a triangle. In 3D graphics, once you can draw a triangle, you can do anything. Pretty soon, I started work on a shader compiler. After my final exams that semester, I took a few days off from Collabora to bring up an OpenGL driver capable of spinning gears with my new compiler. Over the next year, I kept reverse-engineering and improving the driver until it could run 3D games on macOS. Meanwhile, Asahi Lina wrote a kernel driver for the Apple GPU. My userspace OpenGL driver ran on macOS, leaving her kernel driver as the missing piece for an open source graphics stack. In December 2022, we shipped graphics acceleration in Asahi Linux. In January 2023, I started my final semester in my Computer Science program at the University of Toronto. For years I juggled my courses with my part-time job and my hobby driver. I faced the same question as my peers: what will I do after graduation? Maybe Panfrost? I started reverse-engineering of the Mali Midgard GPU back in 2017, when I was still in high school. That led to an internship at Collabora in 2019 once I graduated, turning into my job throughout four years of university. During that time, Panfrost grew from a kid’s pet project based on blackbox reverse-engineering, to a professional driver engineered by a team with Arm’s backing and hardware documentation. I did what I set out to do, and the project succeeded beyond my dreams. It was time to move on. What did I want to do next? Finish what I started with the M1. Ship a great driver. Bring full, conformant OpenGL drivers to the M1. Apple’s drivers are not conformant, but we should strive for the industry standard. Bring full, conformant Vulkan to Apple platforms, disproving the myth that Vulkan isn’t suitable for Apple hardware. Bring Proton gaming to Asahi Linux. Thanks to Valve’s work for the Steam Deck, Windows games can run better on Linux than even on Windows. Why not reap those benefits on the M1? Panfrost was my challenge until we “won”. My next challenge? Gaming on Linux on M1. Once I finished my coursework, I started full-time on gaming on Linux. Within a month, we shipped OpenGL 3.1 on Asahi Linux. A few weeks later, we passed official conformance for OpenGL ES 3.1. That put us at feature parity with Panfrost. I wanted to go further. OpenGL (ES) 3.2 requires geometry shaders, a legacy feature not supported by either Arm or Apple hardware. The proprietary OpenGL drivers emulate geometry shaders with compute, but there was no open source prior art to borrow. Even though multiple Mesa drivers need geometry/tessellation emulation, nobody did the work to get there. My early progress on OpenGL was fast thanks to the mature common code in Mesa. It was time to pay it forward. Over the rest of the year, I implemented geometry/tessellation shader emulation. And also the rest of the owl. In January 2024, I passed conformance for the full OpenGL 4.6 specification, finishing up OpenGL. Vulkan wasn’t too bad, either. I polished the OpenGL driver for a few months, but once I started typing a Vulkan driver, I passed 1.3 conformance in a few weeks. What remained was wiring up the geometry/tessellation emulation to my shiny new Vulkan driver, since those are required for Direct3D. Et voilà, Proton games. Along the way, Karol Herbst passed OpenCL 3.0 conformance on the M1, running my compiler atop his “rusticl” frontend. Meanwhile, when the Vulkan 1.4 specification was published, we were ready and shipped a conformant implementation on the same day. After that, I implemented sparse texture support, unlocking Direct3D 12 via Proton. …Now what? Ship a great driver? Check. Conformant OpenGL 4.6, OpenGL ES 3.2, and OpenCL 3.0? Check. Conformant Vulkan 1.4? Check. Proton gaming? Check. That’s a wrap. We’ve succeeded beyond my dreams. The challenges I chased, I have tackled. The drivers are fully upstream in Mesa. Performance isn’t too bad. With the Vulkan on Apple myth busted, conformant Vulkan is now coming to macOS via LunarG’s KosmicKrisp project building on my work. Satisfied, I am now stepping away from the Apple ecosystem. My friends in the Asahi Linux orbit will carry the torch from here. As for me? Onto the next challenge!

26th Aug 2025 • 44 votes
Vulkan 1.4 sur Asahi Linux

English version follows. Aujourd’hui, Khronos Group a sorti la spécification 1.4 de l’API graphique standard Vulkan. Le projet Asahi Linux est fier d’annoncer le premier pilote Vulkan 1.4 pour le matériel d’Apple. En effet, notre pilote graphique Honeykrisp est reconnu par Khronos comme conforme à cette nouvelle version dès aujourd’hui. Ce pilote est déjà disponible dans nos dépôts officiels. Après avoir installé Fedora Asahi Remix, executez dnf upgrade --refresh pour obtenir la dernière version du pilote. Vulkan 1.4 standardise plusieurs fonctionnalités importantes, y compris les horodatages et la lecture locale avec le rendu dynamique. L’industrie suppose que ces fonctionnalités devront être plus courantes, et nous y sommes préparés. Sortir un pilote conforme reflète notre engagement en faveur des standards graphiques et du logiciel libre. Asahi Linux est aussi compatible avec OpenGL 4.6, OpenGL ES 3.2, et OpenCL 3.0, tous conformes aux spécifications pertinentes. D’ailleurs, les notres sont les seules pilotes conformes pour le materiel d’Apple de n’importe quel standard graphique. Même si le pilote est sorti, il faut encore compiler une version expérimentale de Vulkan-Loader pour accéder à la nouvelle version de Vulkan. Toutes les nouvelles fonctionnalités sont néanmoins disponsibles comme extensions à notre pilote Vulkan 1.3 pour en profiter tout de suite. Pour plus d’informations, consultez l’article de blog de Khronos. Today, the Khronos Group released the 1.4 specification of Vulkan, the standard graphics API. The Asahi Linux project is proud to announce the first Vulkan 1.4 driver for Apple hardware. Our Honeykrisp driver is Khronos-recognized as conformant to the new version since day one. That driver is already available in our official repositories. After installing Fedora Asahi Remix, run dnf upgrade --refresh to get the latest drivers. Vulkan 1.4 standardizes several important features, including timestamps and dynamic rendering local read. The industry expects that these features will become more common, and we are prepared. Releasing a conformant driver reflects our commitment to graphics standards and software freedom. Asahi Linux is also compatible with OpenGL 4.6, OpenGL ES 3.2, and OpenCL 3.0, all conformant to the relevant specifications. For that matter, ours are the only conformant drivers on Apple hardware for any graphics standard graphics. Although the driver is released, you still need to build an experimental version of Vulkan-Loader to access the new Vulkan version. Nevertheless, you can immediately use all the new features as extensions in Vulkan 1.3 driver. For more information, see the Khronos blog post.

2nd Dec 2024 • 117 votes
AAA gaming on Asahi Linux

Gaming on Linux on M1 is here! We’re thrilled to release our Asahi game playing toolkit, which integrates our Vulkan 1.3 drivers with x86 emulation and Windows compatibility. Plus a bonus: conformant OpenCL 3.0. Asahi Linux now ships the only conformant OpenGL®, OpenCL™, and Vulkan® drivers for this hardware. As for gaming… while today’s release is an alpha, Control runs well! Installation First, install Fedora Asahi Remix. Once installed, get the latest drivers with dnf upgrade --refresh && reboot. Then just dnf install steam and play. While all M1/M2-series systems work, most games require 16GB of memory due to emulation overhead. The stack Games are typically x86 Windows binaries rendering with DirectX, while our target is Arm Linux with Vulkan. We need to handle each difference: FEX emulates x86 on Arm. Wine translates Windows to Linux. DXVK and vkd3d-proton translate DirectX to Vulkan. There’s one curveball: page size. Operating systems allocate memory in fixed size “pages”. If an application expects smaller pages than the system uses, they will break due to insufficient alignment of allocations. That’s a problem: x86 expects 4K pages but Apple systems use 16K pages. While Linux can’t mix page sizes between processes, it can virtualize another Arm Linux kernel with a different page size. So we run games inside a tiny virtual machine using muvm, passing through devices like the GPU and game controllers. The hardware is happy because the system is 16K, the game is happy because the virtual machine is 4K, and you’re happy because you can play Fallout 4. Vulkan The final piece is an adult-level Vulkan driver, since translating DirectX requires Vulkan 1.3 with many extensions. Back in April, I wrote Honeykrisp, the only Vulkan 1.3 driver for Apple hardware. I’ve since added DXVK support. Let’s look at some new features. Tessellation Tessellation enables games like The Witcher 3 to generate geometry. The M1 has hardware tessellation, but it is too limited for DirectX, Vulkan, or OpenGL. We must instead tessellate with arcane compute shaders, as detailed in today’s talk at XDC2024. Geometry shaders Geometry shaders are an older, cruder method to generate geometry. Like tessellation, the M1 lacks geometry shader hardware so we emulate with compute. Is that fast? No, but geometry shaders are slow even on desktop GPUs. They don’t need to be fast – just fast enough for games like Ghostrunner. Enhanced robustness “Robustness” permits an application’s shaders to access buffers out-of-bounds without crashing the hardware. In OpenGL and Vulkan, out-of-bounds loads may return arbitrary elements, and out-of-bounds stores may corrupt the buffer. Our OpenGL driver exploits this definition for efficient robustness on the M1. Some games require stronger guarantees. In DirectX, out-of-bounds loads return zero, and out-of-bounds stores are ignored. DXVK therefore requires VK_EXT_robustness2, a Vulkan extension strengthening robustness. Like before, we implement robustness with compare-and-select instructions. A naïve implementation would compare a loaded index with the buffer size and select a zero result if out-of-bounds. However, our GPU loads are vector while arithmetic is scalar. Even if we disabled page faults, we would need up to four compare-and-selects per load. load R, buffer, index * 16 ulesel R[0], index, size, R[0], 0 ulesel R[1], index, size, R[1], 0 ulesel R[2], index, size, R[2], 0 ulesel R[3], index, size, R[3], 0 There’s a trick: reserve 64 gigabytes of zeroes using virtual memory voodoo. Since every 32-bit index multiplied by 16 fits in 64 gigabytes, any index into this region loads zeroes. For out-of-bounds loads, we simply replace the buffer address with the reserved address while preserving the index. Replacing a 64-bit address costs just two 32-bit compare-and-selects. ulesel buffer.lo, index, size, buffer.lo, RESERVED.lo ulesel buffer.hi, index, size, buffer.hi, RESERVED.hi load R, buffer, index * 16 Two instructions, not four. Next steps Sparse texturing is next for Honeykrisp, which will unlock more DX12 games. The alpha already runs DX12 games that don’t require sparse, like Cyberpunk 2077. While many games are playable, newer AAA titles don’t hit 60fps yet. Correctness comes first. Performance improves next. Indie games like Hollow Knight do run full speed. Beyond gaming, we’re adding general purpose x86 emulation based on this stack. For more information, see the FAQ. Today’s alpha is a taste of what’s to come. Not the final form, but enough to enjoy Portal 2 while we work towards “1.0”. Acknowledgements This work has been years in the making with major contributions from… Alyssa Rosenzweig Asahi Lina chaos_princess Davide Cavalca Dougall Johnson Ella Stanforth Faith Ekstrand Janne Grunau Karol Herbst marcan Mary Guillemard Neal Gompa Sergio López TellowKrinkle Teoh Han Hui Rob Clark Ryan Houdek … Plus hundreds of developers whose work we build upon, spanning the Linux, Mesa, Wine, and FEX projects. Today’s release is thanks to the magic of open source. We hope you enjoy the magic. Happy gaming.

10th Oct 2024 • 104 votes
Vulkan 1.3 on the M1 in 1 month

u{text-decoration-thickness:0.09em;text-decoration-color:skyblue} Finally, conformant Vulkan for the M1! The new “Honeykrisp” driver is the first conformant Vulkan® for Apple hardware on any operating system, implementing the full 1.3 spec without “portability” waivers. Honeykrisp is not yet released for end users. We’re continuing to add features, improve performance, and port to more hardware. Source code is available for developers. HoloCure running on Honeykrisp ft. DXVK, FEX, and Proton. Honeykrisp is not based on prior M1 Vulkan efforts, but rather Faith Ekstrand’s open source NVK driver for NVIDIA GPUs. In her words: All Vulkan drivers in Mesa trace their lineage to the Intel Vulkan driver and started by copying+pasting from it. My hope is that NVK will eventually become the driver that everyone copies and pastes from. To that end, I’m building NVK with all the best practices we’ve developed for Vulkan drivers over the last 7.5 years and trying to keep the code-base clean and well-organized. Why spend years implementing features from scratch when we can reuse NVK? There will be friction starting out, given NVIDIA’s desktop architecture differs from the M1’s mobile roots. In exchange, we get a modern driver designed for desktop games. We’ll need to pass a half-million tests ensuring correctness, submit the results, and then we’ll become conformant after 30 days of industry review. Starting from NVK and our OpenGL 4.6 driver… can we write a driver passing the Vulkan 1.3 conformance test suite faster than the 30 day review period? It’s unprecedented… Challenge accepted. April 2 It begins with a text. Faith… I think I want to write a Vulkan driver. Her advice? Just start typing. Thre’s no copy-pasting yet – we just add M1 code to NVK and remove NVIDIA as we go. Since the kernel mediates our access to the hardware, we begin connecting “NVK” to Asahi Lina’s kernel driver using code shared with OpenGL. Then we plug in our shader compiler and hit the hay. April 3 To access resources, GPUs use “descriptors” containing the address, format, and size of a resource. Vulkan bundles descriptors into “sets” per the application’s “descriptor set layout”. When compiling shaders, the driver lowers descriptor accesses to marry the set layout with the hardware’s data structures. As our descriptors differ from NVIDIA’s, our next task is adapting NVK’s descriptor set lowering. We start with a simple but correct approach, deleting far more code than we add. April 4 With working descriptors, we can compile compute shaders. Now we program the fixed-function hardware to dispatch compute. We first add bookkeeping to map Vulkan command buffers to lists of M1 “control streams”, then we generate a compute control stream. We copy that code from our OpenGL driver, translate the GL into Vulkan, and compute works. That’s enough to move on to “copies” of buffers and images. We implement Vulkan’s copies with compute shaders, internally dispatched with Vulkan commands as if we were the application. The first copy test passes. April 5 Fleshing out yesterday’s code, all copy tests pass. April 6 We’re ready to tackle graphics. The novelty is handling graphics state like depth/stencil. That’s straightforward, but there’s a lot of state to handle. Faith’s code collects all “dynamic state” into a single structure, which we translate into hardware control words. As usual, we grab that translation from our OpenGL driver, blend with NVK, and move on. April 7 What makes state “dynamic”? Dynamic state can change without recompiling shaders. By contrast, static state is baked into shader binaries called “pipelines”. If games create all their pipelines during a loading screen, there is no compiler “stutter” during gameplay. The idea hasn’t quite panned out: many game developers don’t know their state ahead-of-time so cannot create pipelines early. In response, Vulkan has made ever more state dynamic, punctuated with the EXT_shader_object extension that makes pipelines optional. We want full dynamic state and shader objects. Unfortunately, the M1 bakes random state into shaders: vertex attributes, fragment outputs, blending, even linked interpolation qualifiers. Like most of the industry in the 2010s, the M1’s designers bet on pipelines. Faced with this hardware, a reasonable driver developer would double-down on pipelines. DXVK would stutter, but we’d pass conformance. I am not reasonable. To eliminate stuttering in OpenGL, we make state dynamic with four strategies: Conditional code. Precompiled variants. Indirection. Prologs and epilogs. Wait, what-a-logs? AMD also bakes state into shaders… with a twist. They divide the hardware binary into three parts: a prolog, the shader, and an epilog. Confining dynamic state to the periphery eliminates shader variants. They compile prologs and epilogs on the fly, but that’s fast and doesn’t stutter. Linking shader parts is a quick concatenation, or long jumps avoid linking altogether. This strategy works for the M1, too. For Honeykrisp, let’s follow NVK’s lead and treat all state as dynamic. No other Vulkan driver has implemented full dynamic state and shader objects this early on, but it avoids refactoring later. Today we add the code to build, compile, and cache prologs and epilogs. Putting it together, we get a (dynamic) triangle: April 8 Guided by the list of failing tests, we wire up the little bits missed along the way, like translating border colours. /* Translate an American VkBorderColor into a Canadian agx_border_colour */ enum agx_border_colour translate_border_color(VkBorderColor color) { switch (color) { case VK_BORDER_COLOR_INT_TRANSPARENT_BLACK: return AGX_BORDER_COLOUR_TRANSPARENT_BLACK; ... } } Test results are getting there. Pass: 149770, Fail: 7741, Crash: 2396 That’s good enough for vkQuake. April 9 Lots of little fixes bring us to a 99.6% pass rate… for Vulkan 1.1. Why stop there? NVK is 1.3 conformant, so let’s claim 1.3 and skip to the finish line. Pass: 255209, Fail: 3818, Crash: 599 98.3% pass rate for 1.3 on our 1 week anniversary. Not bad. April 10 SuperTuxKart has a Vulkan renderer. April 11 Zink works too. April 12 I tracked down some fails to a test bug, where an arbitrary verification threshold was too strict to pass on some devices. I filed a bug report, and it’s resolved within a few weeks. April 16 The tests for “descriptor indexing” revealed a compiler bug affecting subgroup shuffles in non-uniform control flow. The M1’s shuffle instruction is quirky, but it’s easy to workaround. Fixing that fixes the descriptor indexing tests. April 17 A few tests crash inside our register allocator. Their shaders contain a peculiar construction: if (condition) { while (true) { } } condition is always false, but the compiler doesn’t know that. Infinite loops are nominally invalid since shaders must terminate in finite time, but this shader is syntactically valid. “All loops contain a break” seems obvious for a shader, but it’s false. It’s straightforward to fix register allocation, but what a doozy. April 18 Remember copies? They’re slow, and every frame currently requires a copy to get on screen. For “zero copy” rendering, we need enough Linux window system integration to negotiate an efficient surface layout across process boundaries. Linux uses “modifiers” for this purpose, so we implement the EXT_image_drm_format_modifier extension. And by implement, I mean copy. Copies to avoid copies. April 20 “I’d like a 4K x86 Windows Direct3D PC game on a 16K arm64 Linux Vulkan Mac.” … “Ma’am, this is a Wendy’s.” April 22 As bug fixing slows down, we step back and check our driver architecture. Since we treat all state as dynamic, we don’t pre-pack control words during pipeline creation. That adds theoretical CPU overhead. Is that a problem? After some optimization, vkoverhead says we’re pushing 100 million draws per second. I think we’re okay. April 24 Time to light up YCbCr. If we don’t use special YCbCr hardware, this feature is “software-only”. However, it touches a lot of code. It touches so much code that Mohamed Ahmed spent an entire summer adding it to NVK. Which means he spent a summer adding it to Honeykrisp. Thanks, Mohamed ;-) April 25 Query copies are next. In Vulkan, the application can query the number of samples rendered, writing the result into an opaque “query pool”. The result can be copied from the query pool on the CPU or GPU. For the CPU, the driver maps the pool’s internal data structure and copies the result. This may require nontrivial repacking. For the GPU, we need to repack in a compute shader. That’s harder, because we can’t just run C code on the GPU, right? …Actually, we can. A little witchcraft makes GPU query copies as easy as C. void copy_query(struct params *p, int i) { uintptr_t dst = p->dest + i * p->stride; int query = p->first + i; if (p->available[query] || p->partial) { int q = p->index[query]; write_result(dst, p->_64, p->results[q]); } ... } April 26 The final boss: border colours, hard mode. Direct3D lets the application choose an arbitrary border colour when creating a sampler. By contrast, Vulkan only requires three border colours: (0, 0, 0, 0) – transparent black (0, 0, 0, 1) – opaque black (1, 1, 1, 1) – opaque white We handled these on April 8. Unfortunately, there are two problems. First, we need custom border colours for Direct3D compatibility. Both DXVK and vkd3d-proton require the EXT_custom_border_color extension. Second, there’s a subtle problem with our hardware, causing dozens of fails even without custom border colours. To understand the issue, let’s revisit texture descriptors, which contain a pixel format and a component reordering swizzle. Some formats are implicitly reordered. Common “BGRA” formats swap red and blue for historical reasons. The M1 does not directly support these formats. Instead, the driver composes the swizzle with the format’s reordering. If the application uses a BARB swizzle with a BGRA format, the driver uses an RABR swizzle with an RGBA format. There’s a catch: swizzles apply to the border colour, but formats do not. We need to undo the format reordering when programming the border colour for correct results after the hardware applies the composed swizzle. Our OpenGL driver implements border colours this way, because it knows the texture format when creating the sampler. Unfortunately, Vulkan doesn’t give us that information. Without custom border colour support, we “should” be okay. Swapping red and blue doesn’t change anything if the colour is white or black. There’s an even subtler catch. Vulkan mandates support for a packed 16-bit format with 4-bit components. The M1 supports a similar format… but with reversed “endianness”, swapping red and alpha. That still seems okay. For transparent black (all zero) and opaque white (all one), swapping components doesn’t change the result. The problem is opaque black: (0, 0, 0, 1). Swapping red and alpha gives (1, 0, 0, 0). Transparent red? Uh-oh. We’re stuck. No known hardware configuration implements correct Vulkan semantics. Is hope lost? Do we give up? A reasonable person would. I am not reasonable. Let’s jump into the deep end. If we implement custom border colours, opaque black becomes a special case. But how? The M1’s custom border colours entangle the texture format with the sampler. A reasonable person would skip Direct3D support. As you know, I am not reasonable. Although the hardware is unsuitable, we control software. Whenever a shader samples a texture, we’ll inject code to fix up the border colour. This emulation is simple, correct, and slow. We’ll use dirty driver tricks to speed it up later. For now, we eat the cost, advertise full custom border colours, and pass the opaque black tests. April 27 All that’s left is some last minute bug fixing, and… Pass: 686930, Fail: 0 Success. The future The next task is implementing everything that DXVK and vkd3d-proton require to layer Direct3D. That includes esoteric extensions like transform feedback. Then Wine and an open source x86 emulator will run Windows games on Asahi Linux. That’s getting ahead of ourselves. In the mean time, enjoy Linux games with our conformant OpenGL 4.6 drivers… and stay tuned. Baby Storm running on Honeykrisp ft. DXVK, FEX, and Proton.

5th Jun 2024 • 160 votes
Conformant OpenGL 4.6 on the M1

For years, the M1 has only supported OpenGL 4.1. That changes today – with our release of full OpenGL® 4.6 and OpenGL® ES 3.2! Install Fedora for the latest M1/M2-series drivers. Already installed? Just dnf –refresh upgrade. Unlike the vendor’s non-conformant 4.1 drivers, our open source Linux drivers are conformant to the latest OpenGL versions, finally promising broad compatibility with modern OpenGL workloads, like Blender, Ryujinx, and Citra. Conformant 4.6/3.2 drivers must pass over 100,000 tests to ensure correctness. The official list of conformant drivers now includes our OpenGL 4.6 and ES 3.2. While the vendor doesn’t yet support graphics standards like modern OpenGL, we do. For this Valentine’s Day, we want to profess our love for interoperable open standards. We want to free users and developers from lock-in, enabling applications to run anywhere the heart wants without special ports. For that, we need standards conformance. Six months ago, we became the first conformant driver for any standard graphics API for the M1 with the release of OpenGL ES 3.1 drivers. Today, we’ve finished OpenGL with the full 4.6… and we’re well on the road to Vulkan. Compared to 4.1, OpenGL 4.6 adds dozens of required features, including: Robustness SPIR-V Clip control Cull distance Compute shaders Upgraded transform feedback Regrettably, the M1 doesn’t map well to any graphics standard newer than OpenGL ES 3.1. While Vulkan makes some of these features optional, the missing features are required to layer DirectX and OpenGL on top. No existing solution on M1 gets past the OpenGL 4.1 feature set. How do we break the 4.1 barrier? Without hardware support, new features need new tricks. Geometry shaders, tessellation, and transform feedback become compute shaders. Cull distance becomes a transformed interpolated value. Clip control becomes a vertex shader epilogue. The list goes on. For a taste of the challenges we overcame, let’s look at robustness. Built for gaming, GPUs traditionally prioritize raw performance over safety. Invalid application code, like a shader that reads a buffer out-of-bounds, can trigger undefined behaviour. Drivers exploit that to maximize performance. For applications like web browsers, that trade-off is undesirable. Browsers handle untrusted shaders, which they must sanitize to ensure stability and security. Clicking a malicious link should not crash the browser. While some sanitization is necessary as graphics APIs are not security barriers, reducing undefined behaviour in the API can assist “defence in depth”. “Robustness” features can help. Without robustness, out-of-bounds buffer access in a shader can crash. With robustness, the application can opt for defined out-of-bounds behaviour, trading some performance for less attack surface. All modern cross-vendor APIs include robustness. Many games even (accidentally?) rely on robustness. Strangely, the vendor’s proprietary API omits buffer robustness. We must do better for conformance, correctness, and compatibility. Let’s first define the problem. Different APIs have different definitions of what an out-of-bounds load returns when robustness is enabled: Zero (Direct3D, Vulkan with robustBufferAccess2) Either zero or some data in the buffer (OpenGL, Vulkan with robustBufferAccess) Arbitrary values, but can’t crash (OpenGL ES) OpenGL uses the second definition: return zero or data from the buffer. One approach is to return the last element of the buffer for out-of-bounds access. Given the buffer size, we can calculate the last index. Now consider the minimum of the index being accessed and the last index. That equals the index being accessed if it is valid, and some other valid index otherwise. Loading the minimum index is safe and gives a spec-compliant result. As an example, a uniform buffer load without robustness might look like: load.i32 result, buffer, index Robustness adds a single unsigned minimum (umin) instruction: umin idx, index, last load.i32 result, buffer, idx Is the robust version slower? It can be. The difference should be small percentage-wise, as arithmetic is faster than memory. With thousands of threads running in parallel, the arithmetic cost may even be hidden by the load’s latency. There’s another trick that speeds up robust uniform buffers. Like other GPUs, the M1 supports “preambles”. The idea is simple: instead of calculating the same value in every thread, it’s faster to calculate once and reuse the result. The compiler identifies eligible calculations and moves them to a preamble executed before the main shader. These redundancies are common, so preambles provide a nice speed-up. We usually move uniform buffer loads to the preamble when every thread loads the same index. Since the size of a uniform buffer is fixed, extra robustness arithmetic is also moved to the preamble. The robustness is “free” for the main shader. For robust storage buffers, the clamping might move to the preamble even if the load or store cannot. Armed with robust uniform and storage buffers, let’s consider robust “vertex buffers”. In graphics APIs, the application can set vertex buffers with a base GPU address and a chosen layout of “attributes” within each buffer. Each attribute has an offset and a format, and the buffer has a “stride” indicating the number of bytes per vertex. The vertex shader can then read attributes, implicitly indexing by the vertex. To do so, the shader loads the address: Some hardware implements robust vertex fetch natively. Other hardware has bounds-checked buffers to accelerate robust software vertex fetch. Unfortunately, the M1 has neither. We need to implement vertex fetch with raw memory loads. One instruction set feature helps. In addition to a 64-bit base address, the M1 GPU’s memory loads also take an offset in elements. The hardware shifts the offset and adds to the 64-bit base to determine the address to fetch. Additionally, the M1 has a combined integer multiply-add instruction imad. Together, these features let us implement vertex loads in two instructions. For example, a 32-bit attribute load looks like: imad idx, stride/4, vertex, offset/4 load.i32 result, base, idx The hardware load can perform an additional small shift. Suppose our attribute is a vector of 4 32-bit values, densely packed into a buffer with no offset. We can load that attribute in one instruction: load.v4i32 result, base, vertex << 2 …with the hardware calculating the address: What about robustness? We want to implement robustness with a clamp, like we did for uniform buffers. The problem is that the vertex buffer size is given in bytes, while our optimized load takes an index in “vertices”. A single vertex buffer can contain multiple attributes with different formats and offsets, so we can’t convert the size in bytes to a size in “vertices”. Let’s handle the latter problem. We can rewrite the addressing equation as: That is: one buffer with many attributes at different offsets is equivalent to many buffers with one attribute and no offset. This gives an alternate perspective on the same data layout. Is this an improvement? It avoids an addition in the shader, at the cost of passing more data – addresses are 64-bit while attribute offsets are 16-bit. More importantly, it lets us translate the vertex buffer size in bytes into a size in “vertices” for each vertex attribute. Instead of clamping the offset, we clamp the vertex index. We still make full use of the hardware addressing modes, now with robustness: umin idx, vertex, last valid load.v4i32 result, base, idx << 2 We need to calculate the last valid vertex index ahead-of-time for each attribute. Each attribute has a format with a particular size. Manipulating the addressing equation, we can calculate the last byte accessed in the buffer (plus 1) relative to the base: The load is valid when that value is bounded by the buffer size in bytes. We solve the integer inequality as: The driver calculates the right-hand side and passes it into the shader. One last problem: what if a buffer is too small to load anything? Clamping won’t save us – the code would clamp to a negative index. In that case, the attribute is entirely invalid, so we swap the application’s buffer for a small buffer of zeroes. Since we gave each attribute its own base address, this determination is per-attribute. Then clamping the index to zero correctly loads zeroes. Putting it together, a little driver math gives us robust buffers at the cost of one umin instruction. In addition to buffer robustness, we need image robustness. Like its buffer counterpart, image robustness requires that out-of-bounds image loads return zero. That formalizes a guarantee that reasonable hardware already makes. …But it would be no fun if our hardware was reasonable. Running the conformance tests for image robustness, there is a single test failure affecting “mipmapping”. For background, mipmapped images contain multiple “levels of detail”. The base level is the original image; each successive level is the previous level downscaled. When rendering, the hardware selects the level closest to matching the on-screen size, improving efficiency and visual quality. With robustness, the specifications all agree that image loads return… Zero if the X- or Y-coordinate is out-of-bounds Zero if the level is out-of-bounds Meanwhile, image loads on the M1 GPU return… Zero if the X- or Y-coordinate is out-of-bounds Values from the last level if the level is out-of-bounds Uh-oh. Rather than returning zero for out-of-bounds levels, the hardware clamps the level and returns nonzero values. It’s a mystery why. The vendor does not document their hardware publicly, forcing us to rely on reverse engineering to build drivers. Without documentation, we don’t know if this behaviour is intentional or a hardware bug. Either way, we need a workaround to pass conformance. The obvious workaround is to never load from an invalid level: if (level <= levels) { return imageLoad(x, y, level); } else { return 0; } That involves branching, which is inefficient. Loading an out-of-bounds level doesn’t crash, so we can speculatively load and then use a compare-and-select operation instead of branching: vec4 data = imageLoad(x, y, level); return (level <= levels) ? data : 0; This workaround is okay, but it could be improved. While the M1 GPU has combined compare-and-select instructions, the instruction set is scalar. Each thread processes one value at a time, not a vector of multiple values. However, image loads return a vector of four components (red, green, blue, alpha). While the pseudo-code looks efficient, the resulting assembly is not: image_load R, x, y, level ulesel R[0], level, levels, R[0], 0 ulesel R[1], level, levels, R[1], 0 ulesel R[2], level, levels, R[2], 0 ulesel R[3], level, levels, R[3], 0 Fortunately, the vendor driver has a trick. We know the hardware returns zero if either X or Y is out-of-bounds, so we can force a zero output by setting X or Y out-of-bounds. As the maximum image size is 16384 pixels wide, any X greater than 16384 is out-of-bounds. That justifies an alternate workaround: bool valid = (level <= levels); int x_ = valid ? x : 20000; return imageLoad(x_, y, level); Why is this better? We only change a single scalar, not a whole vector, compiling to compact scalar assembly: ulesel x_, level, levels, x, #20000 image_load R, x_, y, level If we preload the constant to a uniform register, the workaround is a single instruction. That’s optimal – and it passes conformance. Blender “Wanderer” demo by Daniel Bystedt, licensed CC BY-SA.

14th Feb 2024 • 98 votes

More in programming

TokyoDev Welcomes Its Head of Operations

TokyoDev has grown substantially over the past few years. We’ve expanded our community, dramatically increased the scope and frequency of our events, and have curated a library of articles for international developers. Despite all that, the way we run the business hasn’t changed much. I’ve continued to coordinate most of these activities myself, making the final decisions and keeping everything connected. In short, TokyoDev cannot run without my daily input. That approach worked well when TokyoDev was smaller, but it’s increasingly limiting how much we can accomplish. To help the business grow further, I wanted to find someone to take over some of my responsibilities and bring a fresh perspective. This is a significant step for me personally, as while I have worked with many contractors over the years, I have never actually hired a regular employee. Most importantly, I wanted to ensure that this person was someone I could trust to understand what TokyoDev stands for, and to make decisions in line with our philosophy. So I’m happy to announce that Scott Rothrock is joining TokyoDev full time as our Head of Operations. About Scott Scott has lived in Japan for nearly 20 years and has worked as a software engineer in multiple industries and environments, including small Japanese-owned businesses, overseas employers, and international companies based in Japan. Until the end of October 2026, he was the head of the Japan Markets team at Kraken Technologies, where he led an international team of software engineers in delivering complicated, regulated products on strict timelines for Japanese electricity and gas retailers, while also ensuring compliance with evolving organizational and global standards. He’s made a name for himself both inside and outside Japan as a kind, effective mentor who can cultivate great engineers and leaders. Scott’s previous role in TokyoDev Some of you may already know Scott in another capacity, as he has been involved with TokyoDev since 2022. He began as a community volunteer and later became our community manager, which also included responsibilities such as managing our article pipeline from submission to publishing. When I created TokyoDev’s Discord, I had no previous experience running an online community. Scott joined soon after I started and began helping other members, stepping in when people behaved inappropriately, and configuring our roles and permissions and safety features. I was impressed by his initiative and asked him to become an official moderator in January 2023. Outside of his role as a moderator, Scott has always pushed TokyoDev to grow; for example, he arranged internet events such as livestreamed AMAs and interviews. He organized TokyoDev’s first meetup as a volunteer in February 2023, which taught me that there was interest in TokyoDev events outside of the internet. By the end of 2023, I had brought him on as our part-time community manager. What I saw throughout his tenure was that Scott continued to take initiative in expanding TokyoDev. Scott was one of our first external contributors, writing about his experience living with a disability in Japan. He encouraged me to expand and refine both our editing and submission processes so that we could reach out to even more contributors and platform their perspectives. The editorial team now consists of him and Rebecca Callahan, and they’ve had a hand in every article that TokyoDev has published. In other words, since 2022, Scott has shown that he cares about TokyoDev as much as I do. He is invested in what we do and why we do it, and shares my vision for what TokyoDev can become. What changes now Scott’s experiences as an engineer, a mentor, and a leader make me confident that, as our Head of Operations, he will continue to help TokyoDev mature. A big part of what has made TokyoDev successful is that I see the software developers who use our site as my peers and genuinely want to help them. Scott shares that perspective, and will join me in ensuring that TokyoDev remains true to its principles while we grow. So what changes in the short term? Nothing dramatic. I will teach Scott about managing TokyoDev as a business, and he will document our processes and products as a part of that learning. He will also look for areas of improvement while ensuring that we remain compliant with regulations and labor law. Over time, I will hand over some other responsibilities. I will continue to run TokyoDev, but TokyoDev will become less dependent on me for its day-to-day operations. Long term, I’m excited about what this will enable us to do. TokyoDev has always been about helping international software developers build successful careers in Japan, and bringing Scott on full time puts us in a much better position to continue doing that. We look forward to writing the next chapter of TokyoDev together.

11 hours ago • 1 votes
Speeding up Kidz Fun Art &#038; making Google love it

Kidz Fun Art is a drawing, colouring and animation app for kids that I’ve been building since 2021. It runs in the browser also as a simple wrapper app on iOS, iPadOS and Windows. It wasn’t getting a great click through rate on Google, even for people who directly searched for it. So, for two days I took a hard look at how fast it loads and how search engines see it. It wasn’t flattering. This post covers what I found, what I changed and what the graphs say now. Short version: on a simulated slow phone, the homepage’s Largest Contentful Paint got about 2.6× faster (15.9 s to 6.1 s) and its first load is about 82% smaller (4.2 MB to 0.75 MB). I also fixed a set of SEO mistakes that are, frankly, embarrassing to write down. I’ll write them down anyway. Part 1: Google had no idea what the site was for I started by reading 16 months of Google Search Console data. 9,380 clicks in total. About 9,200 came from people who had typed “kidz fun art” or a close spelling. People searching for what the app actually does (“coloring app for kids”, “ai art for kids”, “make a comic book”) sent the site 164 clicks. In 16 months. Total. When there was a relevant page, Google ranked it well. The site was #1 for things like “drawing app for kids ipad” and a German query that means “paint by numbers app without ads”. There just weren’t many relevant pages. Then I looked at the code, and the cause was obvious. The homepage <title> was “Kidz Fun Art” in all 12 languages. That’s a fine name, and a terrible title. It tells a search engine nothing. The homepage’s first <h1> was the pricing table’s “Choose your experience”. I was, in effect, telling Google that the most important thing on my homepage was the checkout. Every blog post had the same meta description: a generic line about “news, updates, tips”. Each post’s front matter already had a perfectly good excerpt field that nobody read. Blog posts had two <h1>s: the site header and the post title. There was no structured data at all. The sitemap that redirected every single URL This one stings. The sitemap is the one file whose whole job is to say “here are my URLs, please index them”. Mine listed 17 URLs, and every one of them redirected. The sitemap build used an environment variable that resolved to kidzfun.art. The site lives on www.kidzfun.art, so every URL got a 308. Only the English blog posts were listed. The other 11 languages appeared only as hreflang alternates, which pointed at redirecting URLs too. There were no <link rel="canonical"> tags on any page and no hreflang in the page <head>. Google was left to guess which URL was the real one, and it guessed wrong a lot. What I changed: The sitemap is now built on https://www.kidzfun.art, with 204 URLs: every home page, blog index, blog post, About page and gallery page, in all 12 languages. Each one lists all of its language alternates plus an x-default. A shared SeoLinks component adds an absolute canonical (www, no query string) and the full hreflang set to every public page. The ?v= cache-busting URLs that had been showing up as duplicates now canonicalise to the clean URL. /xx/blog/yy/... URLs, which returned a 500 in production (oops), now 308 to /blog/yy/.... Login, account, debug, export and embed pages send X-Robots-Tag: noindex, follow from next.config.js, so they stop using up crawl budget. robots.txt now mentions the sitemap. Novel idea. Why Google skipped half the site Search Console’s Pages report had 93 of 174 known pages not indexed. Every reason on that list traces back to the mistakes above: “Page with redirect” (22): that sitemap, plus internal links to the non-www host. “Duplicate without user-selected canonical” (18): I hadn’t selected any canonicals. Fair cop. “Crawled, currently not indexed” (39): mostly translated posts that Google reached through redirecting URLs, plus thin pages like /login. “Discovered, currently not indexed” (12): Google found these and decided they weren’t worth a visit. With no sitemap entry and no hreflang, I hadn’t given it a reason to. On-page fixes Titles and descriptions: Each blog post got its own seoTitle and description, in all 12 languages. The meta description now comes from the post’s excerpt, which is what that field was for all along. The About pages take their title and description from their own localized Markdown. They had been sharing an English title and a generic description. One <h1> per page: A # heading inside a post’s Markdown now renders as an <h2>, so the post title is the only <h1>. The About page opts back in with a keepH1 prop. Its Markdown heading is the page title. This fix arrived in two parts. The first part left the About page with zero <h1>s. I noticed, eventually. Structured data and social tags: JSON-LD for the home page (the app), blog posts (articles) and the embedded videos. Open Graph and X/Twitter tags on every public page, so shared links get a proper card. A real 404 for deleted gallery images: The AI gallery shows a friendly “AI Artwork Not Found” page when an image has been deleted. It used to return 200 OK, which Google calls a “soft 404” and dislikes. It now returns a 404 with noindex, and a 503 if the Firestore lookup itself fails, so a database hiccup tells crawlers “come back later” rather than “this is gone”. Part 2: Making the homepage fast The homepage is the app. It works offline, so every dialog (save, stickers, colouring pages, “get an adult”, “no wifi”) is server-rendered into the HTML up front. That’s a deliberate trade-off, and I kept it because I want new users to be able to immediately be able to start drawing as soon as they launch the app. What I hadn’t thought about was what it meant for the network. What the homepage downloaded before the app could start I measured the live site with a Lighthouse-style mobile profile: slow 4G (1.6 Mbps, 150 ms latency), 4× CPU slowdown, empty cache. First load: 4.5 MB over 198 requests. The homepage HTML alone was 358 KB, with about 77 <img> tags in hidden dialogs. The browser dutifully fetched every one of those images. The script that starts the app (main.min.js, 191 KB) sat at the very end of the document, so the browser found it last and gave it whatever bandwidth was left. The app script finished arriving at about 14 seconds. The CPU was not the problem. Every long task was under 300 ms. This was purely about bandwidth and request order. I had built a very polite queue and put my own app at the back of it. Watch the queue The waterfall is a simplified illustration. The milestone times (first paint, LCP, load) are measured: slow 4G + 4× CPU, local production build, median of 3 runs. My Largest Contentful Paint was the “Contact support” link The canvas doesn’t count toward LCP, and the toolbar buttons are small. So on a slow load the largest thing painted was… the loading dialog. The loading dialog fades in its “Taking a while? Contact support” text after 5 to 7.5 seconds. On a slow connection, that text became the page’s LCP element, at 15.9 s. I was measuring my page speed by how long it took to suggest the user complain about my page speed. There’s a lesson in there somewhere. The fix wasn’t to change the dialog. It was to make the app start sooner, so it paints before that text ever appears. What I changed Preload the app script. I added <link rel="preload" as="script"> in <head> for main.min.js and errorHandler.min.js. The <script> tags stay where they were, so execution order doesn’t change. The browser just starts fetching them before any image. This one line did more than anything else on this list. It’s a little humbling. Turn the three dialog GIFs into MP4s. Three animated GIFs: an arrow pushing pictures into a tablet (927 KB), a dancing rainbow pencil (650 KB) and a paper plane (305 KB). That’s 1.9 MB of decoration in dialogs most visitors never open on their first visit. I re-encoded them with ffmpeg: H.264 High profile, -preset veryslow -crf 20, yuv420p, +faststart, constant frame rate taken from each GIF’s frame delay. The commands are committed as scripts/gif-to-mp4.sh. The result is 130 KB in total, with SSIM between 0.988 and 0.993 against the originals. The pencil needed tpad=stop_mode=clone:stop_duration=0.2, because ffmpeg’s GIF reader drops the final 250 ms hold and the dance lost its big finish. The new <video autoplay loop muted playsinline> tags render at exactly the same size and class as the old <img> tags. Alt text moved to aria-label. Locked colouring thumbnails were full-size PNGs. In the colouring page picker, locked pages used the full-size colouring PNG as their background image, inlined into the HTML. That came to about 1.3 MB on every first visit, to draw thumbnails in a dialog that was closed. They now use the small image, set when the picker opens, like the unlocked ones always did. Sticker thumbnails wait their turn. I tried loading="lazy" first. It didn’t help: Chrome fetched the images before the stylesheet that hides the dialogs had arrived, so as far as it knew they were visible. Sticker thumbnails and the media library’s YouTube thumbnail now use data-deferred-src. They load 3 seconds after the load event, or as soon as their dialog opens, whichever comes first. The service worker preload starts after load. The offline preload queue (about 2 MB of colouring pages and stickers) used to start while the page was still loading and compete with it. Now it starts after the load event. Same files, same offline result, no fighting for bandwidth. Analytics is async. Nothing waited for it, so nothing needed to block on it. Cache headers. /images/*: max-age=86400, stale-while-revalidate=604800. It had been max-age=0, so every image was re-checked on every visit. Versioned /js, /css and /addToHomescreen files are immutable for a year in production. Offline still has to work Offline support is a core feature, so “just don’t download it” was never an option. Some of the changes above put it at risk, and a couple of things turned up along the way: Safari plays video from byte ranges. Safari requests video with Range: bytes=.... Answer that with a full cached response and the video won’t play. The service worker now answers Range requests from its cache with a proper 206 Partial Content slice (lib/util/rangeResponse.ts, with unit tests). First-visit gap: on a first visit the service worker isn’t controlling the page yet, so dialog images only reached the offline cache on the second online visit. The page’s own dialog images and videos now go to the front of the offline preload queue on the first visit. I nearly downloaded my whole site, 12 times over. The service worker cached every <link href> it found in the page. The new SEO work had just added canonical and hreflang <link>s pointing at all 12 localized homepages. So every new visitor would have downloaded about 12 extra homepages, in languages they don’t speak, “for offline use”. I caught it before production. The service worker now skips rel=canonical and rel=alternate. Safari stopped the service worker mid-download. The old preload queue ran on timers after the request had been answered. Safari considers an idle service worker fair game, so it stopped it after the first few images. The page now sends images in batches of 10, and the service worker caches each batch before it replies. A page lock-up I’d never noticed. resizeDialog added a new “image loaded” listener every time the window resized. With lots of images loading at once, the listeners multiplied until the page locked up. It now attaches one listener per image, which, in hindsight, is how many it needed. Part 3: The blog Blog index cards used the full 1920 px screenshots as covers, up to 500 KB each, in a box about 200 px wide. Each card was a little billboard, shrunk down by the browser on every visit. Covers now go through next/image with sizes that match the actual card widths, so the browser gets a resized WebP. The first few cards get priority. The rest load lazily. The first sizes hint was too small at some widths and made covers blurry. It now matches the real card widths, up to about 630 px between 769 px and 1028 px wide. Post pages: The cover image gets fetchpriority="high", and images further down the post load lazily. Five images were recompressed in place, keeping the same filenames and dimensions. The PNGs came out about 4× smaller and the JPEGs about 40% smaller. I deleted a 1.1 MB cover.png that nothing referenced. All 12 translations of that post used cover.jpg. The PNG had just been sitting in public/ taking up space. Results on the slow 4G profile: /blog LCP went from 13.3 s to 1.8 s. A typical post went from 3.9 s to 1.7 s. The gallery didn’t get faster, on purpose. It got a 5-minute edge cache and a cached Firestore image count, which fixed its slow server responses. I decided not to change its 20 full-size PNG thumbnails, so its lab LCP barely moved (8.4 s to 8.6 s). That’s a choice, and the chart owns it. Part 4: Lighthouse homework After the speed work went live I ran Lighthouse on the production homepage (mobile) and cleaned up what it flagged. Performance stayed in the low 70s, so I have some more work to do, but it’s moved nicely in the right direction. Part 5: Telling the search engines Fixing the site is half the job. The other half is getting crawlers to come back and notice. Google Search Console: Resubmitted the www sitemap. Clicked “Validate fix” on “Duplicate without user-selected canonical” and on the redirect errors. Requested indexing for the main language homepages and the top blog posts. The quota is about 10 a day, so it’ll take a few days. Wrote down a baseline from the Performance report, so in 4 to 8 weeks I can tell whether any of this worked. Bing Webmaster Tools: Submitted all 204 sitemap URLs through URL Submission. The daily quota is 10,000, so no trickle-feeding needed. Bing’s index also feeds DuckDuckGo and several AI search tools, so it’s cheap extra reach. Most of Bing’s “SEO recommendations” pointed at old ?v= URLs and old titles. They’ll clear as Bing recrawls. What I’m not watching: the Lighthouse score. Google ranks on real-user Chrome data (the Chrome UX Report): a rolling 28-day window, judged at the 75th percentile. So the honest answer to “did it work?” is “ask me in a month”. How I kept from breaking things The app has hundreds of unit and integration tests, all of which still pass (even though they do take over 30 minutes to run). I also manually regression tested all the riskiest changes. Hopefully I don’t make things worse before they get better… Lessons, mostly at my own expense Read your own sitemap. Actually open it and click a URL. Mine had been quietly redirecting for who knows how long. <link rel="preload"> for the script that boots your app is the cheapest big win there is. Browsers fetch resources in the order they find them. If your app script is at the bottom of a 358 KB document full of images, it really is last in line. Check what your LCP element actually is before you try to make it faster. Mine was a “Contact support” link. GIF is an image format from 1987 that I was using as a video format. A real video codec beats it by an order of magnitude at the same quality. try/catch doesn’t catch promise rejections. I knew that. My code didn’t. Every <link> you add to <head> is something your service worker might decide to download. Speed scores are for diagnosis. Rankings come from real users. Fix what the lab finds, then wait for the field data. Epilogue You’re still here? Wow. Cool. After all this, I’m hoping that users notice nothing other than quicker app start times. I’m looking forward to keeping an eye on traffic and retention in the coming weeks. Wish me luck!

12 hours ago • 1 votes
My new digital home

It's time for a dev blogger's favorite topic: blogging about my new blogging setup. After migrating my blog from Hexo to Eleventy, building a photography website and creating a personal one-pager, it was time to find a new digital home for all my projects. If you notice any issue after the migration, please let me know. I redirect the RSS feed to the new domain, but you might want to update the feed URL in your reader. Motivation I've been maintaining three different websites under two different names: a mostly developer-oriented blog, a photography portfolio and a one-pager gluing everything together. When I started blogging about my sabbatical journey, I was thinking about making yet another page to create a clear separation. I've decided to do the opposite and merge all my websites into one instead. As I further reduce my dependency on social media and third-party services, it has become even more important to have my own space and practice POSSE. Every decision I've made was driven by two main goals: simplicity and personality. Setup I've stopped chasing the latest and greatest. I want to keep the setup as clean as possible, which means pulling fewer dependencies. Every package adds complexity and maintainability costs, so I've only added what was necessary — no more Gulp, Sass or Tailwind. Instead of taking one of my existing websites as a starting point, I created this project from scratch. I reused some of my previous code, but I didn't want to take over any technical debt (especially with the advancements in CSS). The foundation of this website hasn't changed: Eleventy (Build Awesome). It covers the fundamentals of a static site and offers a great level of customization. I've made my project more and less dependent on Eleventy at the same time: I replaced Gulp as my build pipeline with pure Eleventy processing. I replaced most shortcodes with Markdown alternatives (and markdown-it plugins), which are better supported by editors like Obsidian. I've also replaced the Nunjucks template engine with Liquid, which comes with a few trade-offs. The main reason was to avoid creating a new collection for every set of posts I render. With Liquid, you can apply array functions like filtering or sorting in the template itself: {% assign drafts = collections.all | where: "data.isDraft" | reverse %} {% for draft in drafts %} … {% endfor %} Another advantage is having date formatting included, so I don't need another library or custom code. You can even set a default date format, so you don't have to provide it each time. What I don't like is the verbosity of the template language, although I've gotten used to it by now. Nunjucks: {{ "/tags/" + tag + "/" }} {{ modified or created or date }} {% set perspectives = ["dev", "photography", "life"] %} Liquid: {{ "/tags/" | append: tag | append: "/" }} {{ modified | default: created | default: date }} {% assign perspectives = "dev, photography, life" | split: ", " %} After migrating my existing content, I've noticed the build taking way too long, both in the dev server and the production build. I've found out that the Eleventy template cache is turned off for Liquid by default. This was useful during development, but when updating actual content, it caused every template and partial to be constantly recalculated. After turning the cache on, this issue was resolved: eleventyConfig.setLiquidOptions({ cache: true }); Check the colophon for the full tech stack overview. Perspectives The main challenge was finding a way to separate and present my main personas. The Venn diagram intersection of people interested in software development, photography and my personal life is probably small. I could use tags, but they don't offer the level of personalization I was looking for. Most personal blogs separate the content by post type (blog post, note, photo), but this doesn't fit my use case. Instead, I've decided to structure my website around three perspectives, a term I have borrowed from the Eclipse IDE. Each perspective comes with its own avatar, tagline and bio. If someone is interested in everything I share (hi Mom!), they can still view all my posts. Design Since building my photography website, I've made many changes, but I never got around to share an update. The biggest change was the design, which I have used as a blueprint for the new website. I've decided to mimic a social timeline/feed, which most people are familiar with. At the same time, it should be clear that it's a personal website and not yet another walled garden. Typography is an important part of every design. The first step is to choose between a system font stack and a custom font, which comes with the usual performance vs. personality trade-offs. I've decided to go with a uniform look across all devices. I've settled on Source Sans 3 for copy text and Hack for code. Another big change was introducing a sidebar. I always felt like the empty horizontal space was "wasted" on a desktop device, but getting the sidebar UX right is challenging. I'm happy with the result, especially with the last two panels adding a personal touch to the design. Images I've made several changes to the handling of image files. To make them compatible with Markdown editors, I had to replace my custom picture shortcode. The official Eleventy image plugin is a popular choice, but it violates my simplicity goal and doesn't support everything I needed. I've decided to go with a plain Markdown image markup and a single image file (no format fallback or 2x version for retina displays). Additionally, I wrote a markdown-it plugin to turn the optional title parameter into a caption. As for the file format, both WebP and AVIF have excellent browser support. For each image, I select the format based on the quality and file size. For my photos, I'm using WebP for the timeline thumbnails and JPG for the full-size version. Theme picker There have been some recent discussions about dark mode toggles, and I considered going for a light/dark solution based on the user's OS preference. Driven by the personality goal, I knew I had to add at least one more theme, so a proper theme picker was necessary. Similar to navigation, people like to hide the theme selection on mobile devices behind a burger menu or a dropdown. I prefer the solution by Sarah L. Fossheim, where all available themes are displayed above the page footer. A friend was scrolling through my new website, and their first question was "Why is the theme picker in the footer?". This tells me the solution was a good idea — I don't think he would have noticed a typical theme button in the header. The implementation follows standard practices: Use the light or dark theme as default based on the user's OS or browser preference. Store a selected theme in the local storage and use it as the single source of truth. Prevent a flash of inaccurate color theme. Make the theme play nicely with bfcache. I might have slightly gone overboard with my third theme, but the nostalgia kept me adding more and more features. Enjoy going back to the 90s: Feeds As browser vendors decided to remove XSLT support, I didn't bother to style my feed. Instead, I've created a new web feeds page, listing all available feeds and a short explanation. I provide one feed for every perspective and one with all my posts combined. I once offered tag-based RSS feeds. This was useful for my sabbatical, but even there I had only a single subscriber. Now, all tag feeds redirect to their main perspective feed. I've also dropped the JSON feed, despite having at least 16 subscribers. Given that every web feed reader supports Atom feeds, I don't see the value of providing a JSON alternative. A JSON feed doesn't add much complexity, but handling different media types (post, photo) and properly escaping the content is one more thing to implement and maintain. Quality assurance I've put a lot of effort into my new digital home, and I want to make sure it stays in good shape. I've included several tools, most running automatically as part of the CI pipeline: eleventyDataSchema — lint Eleventy data values like titles or dates markdownlint — format/lint Markdown files Vale — lint content (grammar, writing style, formatting) Lychee — find broken links (internal and external) Evaluatory — check accessibility and validate HTML Oxlint — lint JavaScript files Eleventy linters are another option to analyze a template's output, but I haven't found a use case for it yet. Not everything can be automated, so I also did the following manually: Test with Chrome, Firefox and Safari Test with Polypane Test with Google Lighthouse Test with a screen reader Test with JavaScript disabled Test with CSS disabled Test at 200% zoom Test with a bigger browser font size Test with custom fonts disabled Test with delayed assets Performance It's difficult to compare the performance of two separate websites with that of a combined one. Some parts got worse, e.g. bigger font files and more CSS. At the same time, I've noticed that gzip compression was turned off for anything but HTML for a few years now (I must have missed it when upgrading nginx) 🙈. One improvement was to implement on-demand assets. For example, the lite-youtube-embed CSS and JavaScript is only loaded if a <lite-youtube> element is present on the page. As before, JavaScript is fully optional (except for interactive demos in individual posts). I've been using a mix of <noscript> and CSS to hide elements that require JS (like the theme picker). I don't like the user experience of pagination, so I avoided it for years. But now that I have almost 300 posts, I've decided to finally add it. I display 30 posts per page, with images further down still being lazy-loaded for better performance. I haven't applied pagination to tag pages, as that's more complex with Eleventy. Bits and pieces Here are some other noteworthy changes: I've removed post-specific social share images and use a single WebP Open Graph image instead. I've dropped JSON-LD. Open Graph and microformats are sufficient. "Naming is hard" is a common expression in software development, but it also applies to photograph titles. I've decided to use a counter as the title, e.g. #0100. Sometimes I do come up with a title that I love, like the Castle in the Sky, so I might mention it in the description. On a photo page, you can now open the previous/next photo using the left/right arrow keys (in addition to the existing navigation buttons). It's now possible to filter photos by date, gear, or location. Check the explore page for an overview. I've learned about and used some experimental CSS features (with progressive enhancement), like scroll-triggered animations or squircle corners. I've added an AI statement on my LLM usage. I finally have a proper about page. Cool URIs don't change, but it's inevitable when moving to a new domain. All my previous URLs are redirected, except for some assets that are no longer used. I will keep the old domain, so the redirects will continue to work for a foreseeable future. I've kept my previous Easter egg and added a few more. Have a happy hunt! 🕵️‍♂️ Inspiration I visited hundreds of personal websites looking for inspiration. Here are a few that I kept coming back to: Emma Goto. I love Emma's approach to presenting the variety of her interests, even though I went a different route. Brennan Kenneth Brown. This website has so much to offer. It's a great example of what the open web looks like. Rex Barrett. The sentence "Collecting hobbies is my hobby." hit home — so much that I had to steal borrow it for my short life bio. Conclusion This project was mostly about merging the content of two websites into one. I knew this would take a considerable amount of time, but I still greatly underestimated the effort. In the end, it was all about the journey, not the destination. I loved fine-tuning the design and tweaking little details that probably no one will ever notice. I still have many more ideas left in my backlog. How do you like my new digital home? If you have an opinion, let me know! Reply via email

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