Please see platform specific instructions for further installation instructions and if you have trouble installing Julia. Juno is an extension to the popular Atom editor with all the capabilities provided by Atom. See what our products can do for pharmaceutical analytics, Fugro Roames engineers use machine learning in Julia to identify network failures and potential failures 100x faster, MIT roboticists program robots in Julia to climb stairs and walk on hazardous, difficult and uneven terrain, Now-Casting Economics uses Julia to reduce macroeconomic modeling time from weeks to days, Researchers use Julia on a NERSC supercomputer to catalog millions of astronomical objects and achieve peak performance of 1.54 petaflops per second, One of Europeâs largest insurers is using Julia for Solvency II Compliance, Next-generation macroeconomic models require high-performance computing: enter Julia, The Federal Aviation Administration is using Julia to develop the Next-Generation Airborne Collision Avoidance System, The world's largest asset manager is using Julia to upgrade its trademark Aladdin analytics platform, JULIA USERS AND JULIA COMPUTING CUSTOMERS, Need help with Julia? Julia programs compile to efficient native code for multiple platforms via LLVM. We operate out of Boston, London and Bangalore, and we serve customers worldwide. Whether you're looking for the convenient and familiar DataFrames, or a new approach with JuliaDB, Julia provides you a rich variety of tools. We thank Fastly for their generous infrastructure support. Click, Training: Parallel Computing in Julia, Oct 29 - 30. Miletus allows for complex financial contracts to be constructed with a combination of simple primitive components and operations. Julia developers can build better software quicker and easier while benefiting from Julia's unparalleled high performance. See below for details on curated packages. It also has powerful shell-like capabilities for managing other processes. We operate out of Boston, London and Bangalore, and we serve customers worldwide. VegaLite.jl provides the Vega-Lite grammar of interactive graphics interface as a Julia package. Pumas is massively scalable with an inherent ability to run on GPUs and on any hosted or private cloud computing setups in conjunction with others products of Julia Computing like JuliaTeam and JuliaRun. Julia features optional typing, multiple dispatch, and good performance, achieved using type inference and just-in-time (JIT) compilation, implemented using LLVM. It empowers users to access the Julia language and its rich package ecosystem from within the world's most popular spreadsheet. Miletus provides both basic the primitives for the construction of financial contract payoffs as well as a decoupled set of valuation model routines that can be applied to various combinations of contract primitives. Julia's rich machine learning and statistics ecosystem includes capabilities for generalized linear models, decision trees, and clustering. We also provide training and consulting services and build open source or proprietary packages for our customers on a consulting basis. Julia is designed from the ground up to be very good at numerical and scientific computing. Julia has been downloaded over 17 million times and the Julia community has registered over 4,000 Julia packages for community use. Use General registry to use any package from 2900+ open source packages. You can also perform online computations on streaming data with OnlineStats.jl. Pumas is the first platform to provide true integration of pharmacometric models with convolution neural networks and other machine learning approaches. Â© 2016 - 2020 Julia Computing, Inc. All Rights Reserved. While it is a general purpose language and can be used to write any application, many of its features are well-suited for numerical analysis and computational science. The Celeste.jl project achieved 1.5 PetaFLOP/s on the Cori supercomputer at NERSC using 650,000 cores. For first-class support for your critical applications. Use Julia as a computational backend for data in Excel. Use Julia as a computational backend for data in Excel JuliaInXL is a package that's designed to enhance Microsoft Excel® spreadsheets with Julia. Julia can work with almost all databases using JDBC.jl and ODBC.jl drivers. Need help with Julia? The Bloomberg APIs provide easy access to real-time market data as well as historic data. It provides Lisp-like macros and other metaprogramming facilities. Julia has been downloaded over 17 million times and the Julia community has registered over 4,000 Julia packages for community use. These include various mathematical libraries, data manipulation tools, and packages for general purpose computing. Use JuliaPro registry to use any of the 250+ curated JuliaPro packages. Plots.jl is a visualization interface and toolset. This can be seen in the abundance of scientific tooling written in Julia, such as the state-of-the-art differential equations ecosystem (DifferentialEquations.jl), optimization tools (JuMP.jl and Optim.jl), iterative linear solvers (IterativeSolvers.jl), a robust framework for Fourier transforms (AbstractFFTs.jl), a general purpose quantum simulation framework (Yao.jl), and many more, that can drive all your simulations. More details about Pumas.jl can be found at Pumas.ai. The Queryverse provides query, file IO and visualization functionality. In addition, it also integrates with the Hadoop ecosystem using Spark.jl, HDFS.jl, and Hive.jl. In addition to these, you can easily use libraries from Python, R, C/Fortran, C++, and Java. The content on this website is made available under the MIT license. Users who prefer a more grammar of graphics style API might like the pure Julia Gadfly.jl plotting package. Juno provides the flexibility of a traditional IDE with the convenience of a notebook in a hybrid canvas programming style. This will allow traders to quickly price options under a variety of models and automatically identify potential arbitrage opportunities, quants to develop and backtest new strategies, and risk analysts to efficiently manage portfolio risk and counterparty exposure. JuliaFin provides a variety of modelling and pricing engines, a high performance time series data store, as well as interoperability with various databases and data feeds. Julia Computing’s mission is to create and deliver products that make the Julia programming language easy to use, easy to deploy and easy to scale. The talk on the Unreasonable Effectiveness of Multiple Dispatch explains why it works so well. Email us: [email protected]. Get the latest news about Julia delivered to your inbox. Packages such as DistributedArrays.jl and Dagger.jl provide higher levels of abstraction for parallelism. Curated packages are well tested, documented and supported by us. It also allows switching a single Excel session between multiple separate Julia environments and lets users effortlessly develop and deploy Julia functionality to Excel by using Juno and JuliaInXL together. Julia is a high-level, high-performance, dynamic programming language. JuliaPro is free to download and is the fastest on-ramp to Julia for individual researchers, engineers, scientists, quants, traders, economists, students and others. Release with long-term support (v1.0.5-2). Julia can also be embedded in other programs through its embedding API. The Julia data ecosystem lets you load multidimensional datasets quickly, perform aggregations, joins and preprocessing operations in parallel, and save them to disk in efficient formats. Plotting software makes trade-offs between features and simplicity, speed and beauty, and a static and dynamic interface. Julia lets you write UIs, statically compile your code, or even deploy it on a webserver. It includes a number of powerful editing features such as auto-completion, real-time feedback, unicode symbols and operators, to name a few. Julia has foreign function interfaces for C/Fortran, C++, Python, R, Java, and many other languages. Distributed Linear Algebra is provided by packages like Elemental.jl and TSVD.jl. This includes pharmacokinetic and pharmacodynamic (PK/PD), physiologically based pharmacokinetic (PBPK), and quantitative systems pharmacology (QsP) models. Click, Training: Introduction to Julia, Oct 15 - 16. Click, Training: Introduction to Machine Learning and Artificial Intelligence, Oct 22 - 23. Within private companies, it can be difficult to smoothly transition internal code into high quality open-source contributions. Reproducible environments make it possible to recreate the same Julia environment every time, across platforms, with pre-built binaries. JuliaPro is lightweight and easy to install. Model, compose and compute financial contracts. These include various mathematical libraries, data manipulation tools, and packages for general purpose computing. Built with Franklin.jl and the Julia Programming Language. Being designed from the ground up for mathematical and numerical computing, Julia is unusually well-suited for expressing ML algorithms. It empowers users to access the Julia language and its rich package ecosystem from within the world's most popular spreadsheet. Julia is an open source project with over 1,000 contributors. Julia Computingâs mission is to create and deliver products that make the Julia programming language easy to use, easy to deploy and easy to scale. With a set of highly enthusiastic developers and maintainers from various parts of the scientific community, this ecosystem will only continue to get bigger and bigger. Unreasonable Effectiveness of Multiple Dispatch, Using time travel to remotely debug faulty DRAM, Transitioning Code From Closed To Open: A JuliaCon 2020 Discussion Between Julia Users In Industry. You can also find packages for Bayesian Networks and Markov Chain Monte Carlo. Julia also offers a number of domain-specific ecosystems, such as in biology (BioJulia), operations research (JuliaOpt), image processing (JuliaImages), quantum physics (QuantumBFS, QuantumOptics), nonlinear dynamics (JuliaDynamics), quantitative economics (QuantEcon), astronomy (JuliaAstro) and ecology (EcoJulia). It provides a common API across various backends, like GR.jl, PyPlot.jl, and PlotlyJS.jl. Some packages make a display and never change it, while others make updates in real-time. When viewed through the lens of functional programming, this basic set of primitive objects and operations form a set of "combinators" that can be used in the construction of more complex financial constructs. Data visualization has a complicated history. In addition to these, you can easily use libraries from Python, R, C/Fortran, C++, and Java. R programs can do the same with R's JuliaCall, which is demonstrated by calling MixedModels.jl from R. Julia is designed for parallelism, and provides built-in primitives for parallel computing at every level: instruction level parallelism, multi-threading and distributed computing. JuliaInXL is a package that's designed to enhance Microsoft ExcelÂ® spreadsheets with Julia. Julia uses multiple dispatch as a paradigm, making it easy to express many object-oriented and functional programming patterns. Going on a Bull Run - Accelerating Finance with Julia, Julia: A Programming Language to Heal the Planet Together. Curated packages are tested, documented and supported by Julia Computing. For those who do not wish to leave the comfort of the terminal, there is also UnicodePlots.jl. Miletus is a powerful financial contract definition and modeling language, along with a valuation framework written in Julia. The package lets users call Julia functions from Excel and enables loading files and functions into new or existing Julia processes from the Excel ribbon. In Miletus, these "combinators" are implemented through the use of Julia's user-defined types, generic programming, and multiple dispatch capabilities.