| Julia | |
|---|---|
 | |
| Paradigm | Multi-paradigm:multiple dispatch (primary paradigm),functional,array,procedural (imperative),structured,reflective,meta,multistaged[1] |
| Designed by | Jeff Bezanson,Alan Edelman,Stefan Karpinski,Viral B. Shah |
| Developer | Jeff Bezanson, Stefan Karpinski, Viral B. Shah, and other contributors[2][3] |
| First appeared | 2012; 13 years ago (2012)[4] |
| Stable release | |
| Preview release | |
| Typing discipline | Dynamic,[10]inferred,optional,nominative,parametric,strong[10] |
| Implementation language | Julia,C,C++,LLVM,[11]Scheme (was used the parser; almost exclusively) |
| Platform | Tier 1: 64- and 32-bitLinux,Windows 10+, and64-bitmacOS;IA-32,x86-64,Apple silicon(ARM64) Macs; Nvidia GPUs/CUDA 11.0+ (on Linux;tier 2 for Windows)[12][13][14] Tier 2: 64-bitFreeBSD 13.4+ (for x86-64),64-bit Arm for Windows 11 (Prism[15]) and Linux; Apple GPUs/Metal on macOS 13+, Intel GPUs/OneAPI 6.2+ and Nvidia GPUs (on Windows) Tier 3: 64-bitRISC-V,[16] 64-bitmusl (e.g.Alpine Linux); and AMD GPUs/ROCm 5.3+. |
| OS | Linux,macOS,Windows 10+ andFreeBSD |
| License | MIT |
| Filename extensions | .jl |
| Website | JuliaLang.org |
| Influenced by | |
Julia is adynamicgeneral-purposeprogramming language. As ahigh-level language, distinctive aspects of Julia's design include a type system withparametric polymorphism, the use ofmultiple dispatch as a coreprogramming paradigm,just-in-time compilation and a parallelgarbage collection implementation. Notably, Julia does not supportclasses withencapsulated methods but instead relies on the types of all of a function's arguments to determine which method will be called.
By default, Julia is run similarly to scripting languages, using its runtime, and allows forinteractions,[22] but Julia programs can also be complied to small binary standalone executables (or to small libraries for e.g. Python), with e.g. theJuliaC.jl compiler.[23][24][25][26]
Julia programs can reuse libraries from other languages, and vice versa. Julia has interoperability withC,C++,Fortran,Rust,Python, andR. Some Julia packages have bindings for Python and Rlibraries.
Julia is supported by programmer tools like IDEs (see below) and by notebooks like Pluto.jl,Jupyter, and since 2025,Google Colab officially supports Julia natively.
Julia is sometimes used inembedded systems (e.g. has been used in a satellite in space on aRaspberry Pi Compute Module 4; 64-bit Pis work best with Julia, and Julia is supported inRaspbian).[27]
Work on Julia began in 2009, whenJeff Bezanson,Stefan Karpinski,Viral B. Shah, andAlan Edelman set out to create a free language that was both high-level and fast. On 14 February 2012, the team launched a website with a blog post explaining the language's mission.[4] In an interview withInfoWorld in April 2012, Karpinski said of the name "Julia": "There's no good reason, really. It just seemed like a pretty name."[28] Bezanson said he chose the name on the recommendation of a friend,[29] then years later wrote:
Maybe julia stands for "Jeff'suncommon lisp is automated"?[30]
Julia'ssyntax is stable, since version 1.0 in 2018, and Julia has abackward compatibility guarantee for 1.x and also a stability promise for the documented (stable)API, while in the years before in the early development prior to 0.7 the syntax (and semantics) was changed in new versions. All of the (registered package)ecosystem uses the new and improved syntax, and in most cases relies on new APIs that have been added regularly, and in some cases minor additional syntax added in a forward compatible way e.g. in Julia 1.7.
In the 10 years since the 2012 launch of pre-1.0 Julia, the community has grown. The Julia package ecosystem has over 11.8 million lines of code (including docs and tests).[31] The JuliaConacademic conference for Julia users and developers has been held annually since 2014 with JuliaCon2020[32] welcoming over 28,900 unique viewers,[33] and then JuliaCon2021 breaking all previous records (with more than 300 JuliaCon2021 presentations available for free on YouTube, up from 162 the year before), and 43,000 unique viewers during the conference.[34]
Three of the Julia co-creators are the recipients of the 2019James H. Wilkinson Prize for Numerical Software (awarded every four years) "for the creation of Julia, an innovative environment for the creation of high-performance tools that enable the analysis and solution of computational science problems."[35] Also, Alan Edelman, professor ofapplied mathematics atMIT, has been selected to receive the 2019IEEE Computer SocietySidney Fernbach Award "for outstanding breakthroughs in high-performance computing, linear algebra, and computational science and for contributions to the Julia programming language."[36]
Both Julia 0.7[37] and version 1.0 were released on 8 August 2018. Work on Julia 0.7 was a "huge undertaking" (e.g., because of an "entirely new optimizer"), and some changes were made to semantics, e.g. theiteration interface was simplified.[38]Julia 1.6 was the largest release since 1.0, and it was thelong-term support (LTS) version for the longest time, faster on many fronts, e.g. introduced parallel precompilation and faster loading of packages, in some cases "50x speedup in load times for large trees of binary artifacts".[39] Since 1.7 Julia development is back totime-based releases.[40] Julia 1.7 was released in November 2021 with many changes, e.g. a new fasterrandom-number generator and Julia 1.7.3 fixed e.g. at least one security issue.[41] Julia 1.8 was released in 2022,[42] with 1.8.x improvements for distributing Julia programs without source code, and compiler speedup, in some cases by 25%,[43] and more controllableinlining (i.e. now also allowing applying@inline at the call site, not just on the function itself). Julia 1.9 was released on 7 May 2023. It has many improvements, such as the ability to precompile packages to native machine code (older Julia versions also have precompilation for packages, but only partial, never fully to native code, so those earlier versions had a "first use" penalty, slowing down while waiting to fully compile). Precompiled packages, since version 1.9, can be up to hundreds of times faster on first use (e.g. forCSV.jl andDataFrames.jl), and to improve precompilation of packages a new packagePrecompileTools.jl has been introduced. Julia 1.10 was released on 25 December 2023 with many new features, e.g. parallel garbage collection, and improved package load times and a new parser, i.e. it rewritten in Julia, with better error messages and improved stacktrace rendering.[44] Julia 1.11 was released on 7 October 2024, and with it 1.10.5 became the nextlong-term support (LTS) version (i.e. those are the only two supported versions), since replaced by 1.10.10 released on 27 June, and 1.6 is no longer an LTS version. Julia 1.11 adds e.g. parallel garbage collection and the newpublic keyword to signal safe public API (Julia users are advised to use such API, not internals, of Julia or packages, and package authors advised to use the keyword, generally indirectly, e.g. prefixed with the@compat macro, fromCompat.jl, to also support older Julia versions, at least the LTS version). Julia 1.11.1 has much improved startup, and this can be important for some benchmarks.
Julia 1.12 was released on 7 October 2025 (and 1.12.2 on 20 November), and with it aJuliaC.jl package including thejuliac compiler that works with it, for making rather small binary executables (much smaller than was possible before; through the use of new so-called trimming feature). Julia 1.10LTS is by now the only other still-supported branch, though 1.11.8 is also expected (is already downloadable as source code; though maybe not in its final form).[45]
Since 2014,[46] the Julia Community has hosted an annual Julia Conference focused on developers and users. The first JuliaCon took place in Chicago and kickstarted the annual occurrence of the conference. Since 2014, the conference has taken place across a number of locations including MIT[47] and the University of Maryland, Baltimore.[48] The event audience has grown from a few dozen people to over 28,900 unique attendees[49] during JuliaCon 2020, which took place virtually. JuliaCon 2021 also took place virtually[50] with keynote addresses from professorsWilliam Kahan, the primary architect of theIEEE 754 floating-point standard (which virtually all CPUs and languages, including Julia, use),[51] Jan Vitek,[52] XiaoyeSherry Li, and Soumith Chintala, a co-creator ofPyTorch.[53] JuliaCon grew to 43,000 unique attendees and more than 300 presentations (still freely accessible, plus for older years). JuliaCon 2022 will also be virtual held between July 27 and July 29, 2022, for the first time in several languages, not just in English.
The Julia language became a NumFOCUS fiscally sponsored project in 2014 in an effort to ensure the project's long-term sustainability.[54] Jeremy Kepner atMIT Lincoln Laboratory was the founding sponsor of the Julia project in its early days. In addition, funds from theGordon and Betty Moore Foundation, theAlfred P. Sloan Foundation,Intel, and agencies such asNSF,DARPA,NIH,NASA, andFAA have been essential to the development of Julia.[55]Mozilla, the maker of Firefox web browser, with its research grants for H1 2019, sponsored "a member of the official Julia team" for the project "Bringing Julia to the Browser",[56] meaning to Firefox and other web browsers.[57][58][59][60] The Julia language is also supported by individual donors on GitHub.[61]
JuliaHub, Inc. was founded in 2015 as Julia Computing, Inc. byViral B. Shah, Deepak Vinchhi,Alan Edelman,Jeff Bezanson,Stefan Karpinski andKeno Fischer.[62][63]
In June 2017, Julia Computing raised US$4.6 million in seed funding fromGeneral Catalyst and Founder Collective,[64] the same month was "granted $910,000 by theAlfred P. Sloan Foundation to supportopen-source Julia development, including $160,000 to promote diversity in the Julia community",[65] and in December 2019 the company got $1.1 million funding from the US government to "develop a neural componentmachine learning tool to reduce the total energy consumption of heating, ventilation, and air conditioning (HVAC) systems in buildings".[66] In July 2021, Julia Computing announced they raised a $24 millionSeries A round led by Dorilton Ventures,[67] which also ownsFormula One teamWilliams Racing, that partnered with Julia Computing. Williams' Commercial Director said: "Investing in companies building best-in-class cloud technology is a strategic focus for Dorilton and Julia's versatile platform, with revolutionary capabilities in simulation and modelling, is hugely relevant to our business. We look forward to embedding Julia Computing in the world's most technologically advanced sport".[68] In June 2023, JuliaHub received (again, now under its new name) a $13 million strategic new investment led by AE Industrial Partners HorizonX ("AEI HorizonX"). AEI HorizonX is a venture capital investment platform formed in partnership withThe Boeing Company, which uses Julia.[69] Tim Holy's work (atWashington University in St. Louis's Holy Lab) on Julia 1.9 (improving responsiveness) was funded by theChan Zuckerberg Initiative.
Julia is ageneral-purpose programming language,[70] while also originally designed for numerical/technical computing. It is also useful for low-levelsystems programming,[71] as aspecification language,[72] high-level synthesis (HLS) tool (for hardware, e.g.FPGAs),[73] and for web programming[74] at both server[75][76] and client[77][78] side.
The main features of the language are:
Multiple dispatch (also termedmultimethods in Lisp; though there slower, most languages do not have an optimized implementation) is ageneralization ofsingle dispatch – thepolymorphic mechanism used in commonobject-oriented programming (OOP) languages, such asPython,C++,Java,JavaScript, andSmalltalk – that useinheritance.
In Julia, all concrete types aresubtypes of abstract types, directly or indirectly subtypes of theAny type, which is the top of the type hierarchy. Concrete types cannot themselves be subtyped the way they can in other languages; composition is used instead (see alsoinheritance vs subtyping).
By default, the Julia runtime must be pre-installed as user-provided source code is run. Alternatively, Julia (GUI) apps can be quickly bundled up into a single file withAppBundler.jl[26] for "building Julia GUI applications in modern desktop application installer formats. It uses Snap for Linux,MSIX for Windows, and DMG for MacOS as targets. It bundles full Julia within the app".[79]PackageCompiler.jl can build standaloneexecutables that need no Julia source code to run.[22]
In Julia, everything is an object, much like object-oriented languages; however, unlike most object-oriented languages, all functions usemultiple dispatch to select methods, rather than single dispatch.
Most programming paradigms can be implemented using Julia'shomoiconic macros and packages. Julia'ssyntactic macros (used formetaprogramming), like Lisp macros, are more powerful thantext-substitution macros used in thepreprocessor of some other languages such as C, because they work at the level ofabstract syntax trees (ASTs). Julia's macro system ishygienic, but also supports deliberate capture when desired (like foranaphoric macros) using theesc construct.
Julia draws inspiration from various dialects of Lisp, includingScheme andCommon Lisp, and it shares many features withDylan, also a multiple-dispatch-oriented dynamic language (which features aninfix syntax rather than a Lisp-like prefix syntax, while in Julia "everything"[80] is anexpression), and withFortress, another numerical programming language (which features multiple dispatch and a sophisticated parametric type system). WhileCommon Lisp Object System (CLOS) adds multiple dispatch to Common Lisp, not all functions are generic functions.
In Julia, Dylan, and Fortress, extensibility is the default, and the system's built-in functions are all generic and extensible. In Dylan, multiple dispatch is as fundamental as it is in Julia: all user-defined functions and even basic built-in operations like+ are generic. Dylan's type system, however, does not fully support parametric types, which are more typical of theML lineage of languages. By default, CLOS does not allow for dispatch on Common Lisp's parametric types; such extended dispatch semantics can only be added as an extension through theCLOS Metaobject Protocol. By convergent design, Fortress also features multiple dispatch on parametric types; unlike Julia, however, Fortress is statically rather than dynamically typed, with separate compiling and executing phases. The language features are summarized in the following table:
| Language | Type system | Generic functions | Parametric types |
|---|---|---|---|
| Julia | Dynamic | Default | Yes |
| Common Lisp | Dynamic | Opt-in | Yes (but no dispatch) |
| Dylan | Dynamic | Default | Partial (no dispatch) |
| Fortress | Static | Default | Yes |
An example of the extensibility of Julia, theUnitful.jl package adds support for physicalunits of measurement to the language.
Julia has built-in support for callingC orFortran language libraries using the@ccall macro. Additional libraries allow users to call to or from other languages such asPython,[81]C++,[82][83]Rust,R,[84]Java[85] and to use withSQL.[86][87][88][89]
Julia can be compiled to binaryexecutables withPackageCompiler.jl.[22] (or withjuliac). Smaller executables can also be written using a static subset of the language provided byStaticCompiler.jl that does not supportruntime dispatch (nor garbage collection, since excludes the runtime that provides it).[90]
The Julia official distribution includes an interactive (optionallycolor-coded[91])read–eval–print loop (REPL; "command-line"),[92] with a searchable history,tab completion, and dedicated help andshell modes,[93] which can be used to experiment and test code quickly.[94] The following fragment represents a sample session example where strings are concatenated automatically byprintln:[95]
julia>p(x)=2x^2+1;f(x,y)=1+2p(x)y;julia>println("Hello world!"," I'm on cloud ",f(0,4)," as Julia supports recognizable syntax!")Hello world! I'm on cloud 9 as Julia supports recognizable syntax!
SinceUnicode is supported, including for variables and functions you can for example define theRiemann xi function as follows:
usingSpecialFunctions:gammaasΓ,zetaasζξ(s)=1/2*s*(s-1)*π^(-s/2)*Γ(s/2)*ζ(s)
Due to its potential lack of readability and support from some editors, its use is controversial to force users to use Unicode/Greek letters, especially in packages made for others. Thus as can be seengamma is defined by the package used there withASCII (and in the example code either it could have been used or as shown the alias defined can be used;keyword arguments can be defined with ASCII only, but can actuallyalso be defined using Greek/Unicode with a trick, and it's only controversial to only define the latter, defining both in registered packages is possible and most consider ok, since it allows users to use either ASCII or the alternative defined).
The REPL gives user access to the system shell and to help mode, by pressing; or? after the prompt (preceding each command), respectively. It also keeps the history of commands, including between sessions.[96] Code can be tested inside Julia's interactive session or saved into a file (with the idiomatic.jlextension considered best) and run from the command line by typing:[80]
$julia<filename>Julia usesUTF-8 andLaTeX codes, allowing it to support common math symbols for many operators, such as ∈ for thein operator, typable with\in then pressingTab ↹ (i.e. usesLaTeX codes, or also possible by simply copy-pasting, e.g. √ and ∛ possible forsqrt andcbrt functions). Julia 12.x has supportsUnicode 16[97] (Julia 1.13-DEV supports latest 17.0 release[98] and will supportsubscriptq letter,[99] probably first programming language to do so) for the languages of the world, even for source code, e.g. variable names (while it's recommended to use English for public code, and e.g. package names).
Julia is supported byJupyter, an online interactive "notebooks" environment,[100] andPluto.jl, a "reactive notebook" (where notebooks are saved as pure Julia files), a possible replacement for the former kind.[101] In addition Posit's (formerlyRStudio Inc's) Quarto publishing system supports Julia, Python, R and ObservableJavaScript (those languages have official support by the company, and can even be weaved together in the same notebook document, more languages are unofficially supported).[102][103]
The REPL can be extended with additional modes, and has been with packages, e.g. with anSQL mode,[104] for database access, andRCall.jl adds anR mode, to work with theR language.[105]
Julia'sVisual Studio Code extension provides a fully featuredintegrated development environment with "built-in dynamic autocompletion, inline results, plot pane, integrated REPL, variable view, code navigation, and many other advanced language features"[106] e.g. debugging is possible,linting, andprofiling.[107][108][109][110]
Julia is in practiceinteroperable with other languages, in fact the majority of the top 20 languages in popular use. Julia can be used to call shared library functions individually, such as those written in C or Fortran, and packages are available to allow calling other languages (which do not provide C-exported functions directly), e.g. Python (withPythonCall.jl), R,[111] MATLAB, C# (and other .NET languages withDotNET.jl, from them withJdotNET), JavaScript, Java (and other JVM languages, such asScala withJavaCall.jl). And packages for other languages allow to call to Julia, e.g. from Python, R (to Julia 1.10.x currently possible[112]),Rust, Ruby, or C#. Such as with juliacall (part ofPythonCall.jl) to call from Python and a differentJuliaCall package for calling, Julia up to 1.10.x, from R. Julia has also been used for hardware, i.e. to compile toVHDL, as ahigh-level synthesis tool, for exampleFPGAs.[73]
Julia has packages supporting markup languages such asHTML (and also forHTTP),XML,JSON andBSON, and fordatabases (such as PostgreSQL,[113] Mongo,[114] Oracle, including forTimesTen,[115] MySQL, SQLite, Microsoft SQL Server,[114] Amazon Redshift, Vertica, ODBC) and web use in general.[116][117]
Julia has a built-inpackage manager and includes a default registry system.[118] Packages are most often distributed as source code hosted onGitHub, though alternatives can also be used just as well. Packages can also be installed as binaries, using artifacts.[119] Julia's package manager is used to query and compile packages, as well as managing environments. Federated package registries are supported, allowing registries other than the official to be added locally.[120]
Julia's core is implemented in Julia andC, together withC++ for theLLVM dependency. The code parsing, code-lowering, and bootstrapping were implemented in FemtoLisp, aScheme dialect, up to version 1.10.[121] Since that version the new pure-Julia stdlibJuliaSyntax.jl is used for the parsing (while the old one can still be chosen)[122] which improves speed and "greatly improves parser error messages in various cases".[123] The LLVM compiler infrastructure project is used as theback end for generating optimizedmachine code for all commonly used platforms. With some exceptions, thestandard library is implemented in Julia.
Julia has four support tiers.[124]
Julia has tier 1macOS support, for 64-bitApple Silicon Macs, natively (previously suchApple M1-based Macs were only supported byrunning inRosetta 2 emulation[125][126]), and also fully supports Intel-based Macs (or fully supported, no longer listed with any official tier, since Apple no longer sells Intel Macs). 64-bit ARM is supported with tier 2 support on other platforms, Windows 11 and Linux (and tier 3 for FreeBBSD 14.1+). "WSL 2 (Ubuntu LTS)" has tier 2 support on Windows 10+ (WSL 1 seemingly works too), and should also work when used with otherdistros. OpenBSD has received "initial support" and is under active development.
AllIA-32 processors completely implementing thei686 sub-architecture are supported and all 64-bitx86-64 (akaamd64), i.e. all less than about a decade old are supported. 64-bitArmv8 (and later; i.e.AArch64) processors are supported on first tier (for macOS); otherwise second tier on Linux, and ARMv7 (AArch32) is not listed on tier 4, "built at some point in the past, but is known not to build currently" (down from their 3 before with older Julia version).[127] Hundreds of packages areGPU-accelerated:[128] Nvidia GPUs have support withCUDA.jl (tier 1 on 64-bit Linux and tier 2 on 64-bit Windows, the package implementingPTX, for compute capability 3.5 (Kepler) or higher; both require CUDA 11+, older package versions work down to CUDA 9). There are also additionally packages supporting other accelerators, such as Google'sTPUs,[129] and some Intel (integrated) GPUs, throughoneAPI.jl,[130] and AMD's GPUs have support with e.g.OpenCL; and experimental support for the AMDROCm stack.[131]
for several ARM platforms, from small Raspberry Pis to the world's fastest (at one point, until recently) supercomputerFugaku's ARM-basedA64FX.[132]PowerPCLE (64-bit) has tier 3 support, meaning it "may or may not build", and its tier will lower to 4 for 1.12, i.e. then no longer builds/works.[133]
Julia has official (tier 2) support for 64-bit ARMv8 meaning e.g. newer 64-bit (ARMv8-A)Raspberry Pi computers work with Julia (e.g. the Pi Compute Module 4 has been used in space running Julia code).[134] For many Pis, especially older 32-bit ones, it helps to cross-compile the user's Julia code for them. The older 32-bit ARMv7 Pis worked in older Julia versions (still do, but for latest Julia version(s), note downgraded from tier 3 to its current tier 4: "Julia built at some point in the past, but is known not to build currently."). The originalRaspberry Pi 1 has no official support (since it usesARMv6 which has newer had a support tier; though some cut-down Julia has been known to run on that Pi).[135][136]Pico versions of the Pi are known to no work (since using the M-profile Arm, not running under Linux; not yet supported). Julia is now supported inRaspbian[137] while support is better for newer Pis, e.g., those with Armv7 or newer; the Julia support is promoted by theRaspberry Pi Foundation.[138]
On some platforms, Julia may need to be compiled from source code (e.g., the originalRaspberry Pi), with specific build options, which has been done and unofficial pre-built binaries (and build instructions) are available.[139][140]
Julia has also been built for 64-bitRISC-V (has tier 3 support),[141] i.e. has some supporting code in core Julia.
While Julia requires anoperating system by default, and has no official support to run without, or onembedded system platforms such asArduino, Julia code has still been run on it, with some limitations, i.e. on a baremetal 16 MHz8-bit (ATmega328P)AVR-microcontroller Arduino with 2 KB RAM (plus 32 KB of flash memory).[142][143]
Julia has been adopted at many universities includingMIT,Stanford,UC Berkeley,Ferdowsi University of Mashhad and theUniversity of Cape Town. Large private firms across many sectors have adopted the language includingAmazon,IBM,JP Morgan AI Research,[144] andASML. Julia has also been used by government agencies includingNASA and theFAA, as well as every US national energy laboratory.[145][146]
Julia is widely used for drug development in the pharmaceutical industry, having been adopted byModerna,Pfizer,AstraZeneca,Procter & Gamble, andUnited Therapeutics.[167][168]
Julia's generated functions are closely related to the multistaged programming (MSP) paradigm popularized by Taha and Sheard, which generalizes the compile time/run time stages of program execution by allowing for multiple stages of delayed code execution.
we have shown the performance to approach and even sometimes exceed that of CUDA C on a selection of applications from the Rodinia benchmark suite
He has co-designed the programming language Scheme, which has greatly influenced the design of Julia
Julia works on all the Pi variants, we recommend using the Pi 3.
Given that 1.7 is not too far away (timed releases going forward)
the bootstrapping took about 80 seconds previously, but on this PR the time is reduced to about 60 seconds.
This year's JuliaCon was the biggest and best ever, with more than 300 presentations available for free on YouTube, more than 20,000 registrations, and more than 43,000 unique YouTube viewers during the conference, up from 162 presentations, 10,000 registrations, and 28,900 unique YouTube viewers during last year's conference.
running language interpreters in WebAssembly. To further increase access to leading data science tools, we're looking for someone to port R or Julia to WebAssembly and to attempt to provide a level 3 language plugin for Iodide: automatic conversion of data basic types between R/Julia and Javascript, and the ability to share class instances between R/Julia and Javascript.
We envision a future workflow that allows you to do your data munging in Python, fit a quick model in R or JAGS, solve some differential equations in Julia, and then display your results with a live interactive d3+JavaScript visualization ... and all that within a single, portable, sharable, and hackable file.
General Purpose [..] Julia lets you write UIs, statically compile your code, or even deploy it on a webserver.
Airborne collision avoidance system
We present a prototype Julia HLS tool, written in Julia, that transforms Julia code to VHDL.
In summary, even though Julia lacks a multi-threaded server solution currently out of box, we can easily take advantage of its process distribution features and a highly popular load balancing tech to get full CPU utilization for HTTP handling.
you can install the Julia package OhMyREPL.jl [..] which lets you customize the REPL's appearance and behaviour
string(greet, ", ", whom, ".\n") example for preferred ways to concatenate strings. Julia has the println and print functions, but also a @printf macro (i.e., not in function form) to eliminate run-time overhead of formatting (unlike the same function in C).For me RCall loads without issue on Julia 1.11 on MacOS
A list of known issues for ARM is available.
Almost 300 packages rely directly or indirectly on Julia's GPU capabilities.
We flew our GPS receiver payload, Harry v3 on Waratah Seed-1 6U cubesat [..] Julia can also run on Raspberry Pi CM4, the processor I used on our GPS payload computer.
I believe #10917 should fix this. The CPU used therearm1176jzf-s. Please reopen if it does not.I can confirm (FINALLY) that it works on the Raspberry Pi 2 [..] I guess we can announce alpha support for arm in 0.4 as well.
Julia works on all the Pi variants, we recommend using the Pi 3.
Almost all of the Python SDK's features are reimplemented in Julia — for those few that aren't, we are also providing a subsidiary package, PyBraket.jl, which allows you to translate Julia objects into their Python equivalents and call the Python SDK.
Julia and the first observation of Ω−_b → Ξ+_c K− π−
Summary: Julia is ready to be used in physics HEP analysis.
bump julia version to 1.7.3
The flight test team was able to demonstrate … a vertical takeoff and landing vehicle with both electric and conventional fuel propulsion systems onboard. The[uncrewed aerial system] was able to plan and execute these missions autonomously using onboard hardware. It was the first time the Julia programming language was flown on the embedded hardware - algorithms were precompiled ahead of time.
New subspecs of Model1002 for estimating the DSGE with COVID-19 shocks
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