Macroeconomic Modelling
The Federal Reserve Bank of New York publishes its trademark Dynamic Stochastic General Equilibrium models in Julia
JULIA PROGRAMMING
A fresh approach to scientific computing
We are greedy: we want more.
Fast
Julia was designed from the beginning for high performance. Julia programs compile to efficient native code for multiple platforms via LLVM.
Dynamic
Julia is dynamically typed, feels like a scripting language, and has good support for interactive use.
Reproducible
Reproducible environments make it possible to recreate the same Julia environment every time, across platforms, with pre-built binaries
Composable
Julia uses multiple dispatch as a paradigm, making it easy to express many object-oriented and functional programming patterns. The talk on the Unreasonable Effectiveness of Multiple Dispatch explains why it works so well.
General
Julia provides asynchronous I/O, metaprogramming, debugging, logging, profiling, a package manager, and more. One can build entire Applications and Microservices in Julia.
Open source
Julia is an open source project with over 1,400 contributors. It is made available under the MIT license. The source code is available on GitHub.
TRUSTED BY GIANTS
On a mission to make scientific computing more accessible and fun .
NY Federal Reserve
MIT
Robotics Locomotion
MIT roboticists program robots in Julia to climb stairs and walk on hazardous, difficult and uneven terrain
CISCO
Network Security
Cisco researchers use Julia for machine learning to improve network security
Boston Public Schools
Optimising Bus Routes and Times
Optimization in Julia helps Boston schools eliminate up to 200 school buses, save up to $18 million and lets students get more sleep
Astrazeneca
Predicting Toxicity
AstraZeneca and Prioris.ai researchers use Julia, Flux.jl and Turing.jl to predict toxicity with a Bayesian neural network
Nasa
Circuitscape
Circuitscape.jl uses electrical circuit theory to model animal, plant and human migration patterns and their response to climate change
