ChrisRackauckas

11 ms·

91.
by ChrisRackauckas 3y ago
There is a culture of well-defined interfaces which are checked at compile time. This is something that was emphasized in recent posts and changes such as: * New trait systems define the allowed inputs into given solvers in order to enforce
92.
by ChrisRackauckas 3y ago
This is precisely what we did with the SciML ecosystem. You can see a blog post from a year back: https://sciml.ai/news/2022/10/08/error_messages/ . There's a lot of high level interface checkin
93.
by ChrisRackauckas 3y ago
> Numbat can be compiled to Web Assembly and you can run it in your browser. I'm not sure if that is possible with Julia? It's fine these days. https://tshort.github.io/WebAssemblyCompiler.jl/stable/ex
94.
by ChrisRackauckas 3y ago
The Julia WASM tools can make apps which support (/require) this feature. For example, you can compile the ODE solver to WASM as is demonstrated on https://tshort.github.io/WebAssemblyCompiler.jl/stable/examp.
95.
by ChrisRackauckas 3y ago
I agree JIT overhead is not meaningless, but it's pretty odd that only some programming languages in the benchmark measure compilation time while others do not. If we really think it's not meaningless, then other languages (C, For
96.
by ChrisRackauckas 3y ago
I just tried it from the Windows command line and this benchmark with the plots ran in what seemed like instant, and some simple timing showed it was under 2 seconds with a fresh Julia v1.10 beta installation. That seems to line up with wha
97.
by ChrisRackauckas 3y ago
The clinical analysis for the COVID-19 vaccines was pretty practical and that was Pumas used by Moderna. There's a JuliaCon talk about that from the Director Head of Pharmacometrics at Moderna. There's Formula 1 usage, there&#x27
98.
by ChrisRackauckas 3y ago
If I'm not mistaken, Arrow is an in-memory format and not necessarily a storage format. Though it is common to use Arrow with the Parquet serialization format, and the benchmarks here show a much faster read performance than Parquet wh
99.
by ChrisRackauckas 3y ago
The repo is pretty clear on its intentions to not be a language-specific format: > Development Plans > I fully intend to develop JDF.jl into a language neutral format by version v0.4. However, I have other OSS commitments including R&
100.
by ChrisRackauckas 3y ago
You're missing big box stores like Walmart which each have tens of thousands of square feet of parking around them for every car which could potentially show up. Many times, these giant parking lots are mandated by law, so each grocery
101.
by ChrisRackauckas 3y ago
> either one of which is unusual behavior for a cat. Not really. Depends on the cat.
102.
by ChrisRackauckas 3y ago
Julia has language-level support for missing values ( https://docs.julialang.org/en/v1/manual/missing/ ) which acts like the solution here, but generally for any value that can be put in an array by doing
103.
by ChrisRackauckas 3y ago
For circuits a lot of them are represented by differential-algebraic equations (DAEs) and require modeling tools in order to handle the high differential index of the systems. This is the reason why they are typically handled via acausal mo
104.
by ChrisRackauckas 3y ago
I'd argue that acausal modeling is much easier for circuit design. And there's quite a bit of research, including surveys of experts, that backs it up as well. I recently put out a video exactly on this topic that summarizes some
105.
by ChrisRackauckas 3y ago
The creators of Modelica, Hilding Elmqvist and Martin Otter, work in Julia these days so there's been a boom to the development of acausal modeling tooling in Julia. They built https://github.com/ModiaSim/Modia.jl
106.
by ChrisRackauckas 3y ago
There is an example of using this with gradient-based optimization here: https://docs.sciml.ai/SciMLSensitivity/dev/tutorials/data_pa... . As an ODE solver, you wouldn't do nanoGPT with it though, you&#x2
107.
by ChrisRackauckas 3y ago
We recently showed DiffEqGPU.jl generating customized ODE solver kernels for NVIDIA CUDA, AMD GPUs, Intel OneAPI, and Apple Metal, where for CUDA it matches state of the art (MPGOS) which is about 10x-100x something like Jax/PyTorch (w
108.
by ChrisRackauckas 3y ago
Did you try v1.9 or v1.10 yet? From others I'm hearing that the code caching changed Makie from about 70 seconds down to 10 in v1.9, and then the loading time improvements brought it to like 5 (unreleased of course, though v1.10 should
109.
by ChrisRackauckas 3y ago
Interesting response. I develop the Julia SciML organization https://sciml.ai/ and we'd be more than happy to work with you to get wrappers for PRIMA into Optimization.jl's general interface ( https://do
110.
by ChrisRackauckas 3y ago
I'm not sure I'd have the same take. Yes, R as a language is kind of wonky and people who use R tend to not be good programmers. However, the APIs of some packages are designed well enough that even with all of those barriers it c
111.
by ChrisRackauckas 3y ago
I both agree and disagree. It does look weird as library vs language. However at the same time, in Pandas everything tends to be in the Pandas library, whereas when using DataFrames.jl you tend to mix it with a lot of features that are exte
112.
by ChrisRackauckas 3y ago
Julia has a pipe syntax (|>). But I think the bigger part here is more generally APIs built around it, which people are doing some things to port tidy syntax ( https://github.com/TidierOrg/Tidier.jl ).
113.
by ChrisRackauckas 3y ago
Indeed DataFrames.jl isn't and won't be the fastest way to do many things. It makes a lot of trade offs in performance for flexibility. The columns of the dataframe can be any indexable array, so while most examples use 64-bit flo
114.
by ChrisRackauckas 3y ago
Most of my time isn't academic or writing code. Most of it is focused on enhancing algorithms to achieve what's required for new methods to work deployed in production environments such as the Pumas clinical pharmacology work, and
115.
by ChrisRackauckas 3y ago
You can use CondaPkg.jl ( https://github.com/cjdoris/CondaPkg.jl ) to setup Python dependencies with version control. I haven't played with it too much but it seemed to work out for what I tried. Indeed the reason w
116.
by ChrisRackauckas 3y ago
A lot of things are shared on a daily basis. There's a lot of open discussion on the various community channels like Discourse and Slack: the #ttfx channel on slack for example is a great one to follow to keep up with the latency chang
117.
by ChrisRackauckas 3y ago
fastmath is bad in general. In Julia it's not as bad as many other languages because it's attempted to be kept local. The @fastmath macro is essentially a find-replace macro, where it finds things like ^ and replaces it with the f
118.
by ChrisRackauckas 3y ago
There's already some pretty nice improvements in TTL in v1.10. I plan to move onto the v1.10 betas once those are cut, since it's not an insignificant difference. A lot of the testing is being done on the test package https:&#x2F
119.
by ChrisRackauckas 3y ago
IIRC there was a bug triggering precompilation each time you re-instantiated manifests, and Pluto notebooks keep a manifest of all packages that they used (in order to have full reproducibility, so it doesn't necessarily match your glo
120.
by ChrisRackauckas 3y ago
The release was just cut 9 hours ago, as shown on the releases part of the Github page ( https://github.com/JuliaLang/julia/releases/tag/v1.9.0 ). That then starts the jobs for the creation and deployment

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