SaaSHub helps you find the best software and product alternatives Learn more →
JuliaInterpreter.jl Alternatives
Similar projects and alternatives to JuliaInterpreter.jl
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
ModelingToolkit.jl
An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
-
SciMLBenchmarks.jl
Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
-
DifferentialEquations.jl
Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
-
DiffEqOperators.jl
Discontinued Linear operators for discretizations of differential equations and scientific machine learning (SciML)
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
JuliaInterpreter.jl reviews and mentions
-
Do you use Julia for general purpose tasks?
The projects page is a list of suggestions of projects that someone has already said they want to run. If you can find a mentor, you can submit a project for anything. For potential performance improvements, I'd look at https://github.com/JuliaDebug/JuliaInterpreter.jl/issues/206, https://github.com/JuliaDebug/JuliaInterpreter.jl/issues/312, and https://github.com/JuliaDebug/JuliaInterpreter.jl/issues/314. I'm not sure if Tim Holy or Kristoffer have time to mentor a project, but if you're interested in doing a gsoc, ask around in the Julia slack/zulip, and you might be able to find a mentor.
-
Julia 1.7 has been released
I would not go as far as calling it very naive, there has certainly been some work put into optimizing performance within the current design.
There are probably some gains to be had by using a different storage format for the IR though as proposed in [1], but it is difficult to say how much of a difference that will make in practice.
[1] https://github.com/JuliaDebug/JuliaInterpreter.jl/pull/309
-
What's Bad about Julia?
You're right, done some more research and there seems to be an interpreter in the compiler: https://github.com/JuliaDebug/JuliaInterpreter.jl. It's only enabled by putting an annotation, and is mainly used for the debugger, but it's still there.
Still, it still seems to try executing the internal SSA IR in its raw form (which is more geared towards compiling rather than dynamic execution in a VM). I was talking more towards a conventional bytecode interpreter (which you can optimize the hell out of it like LuaJIT did). A bytecode format that is carefully designed for fast execution (in either a stack-based or register-based VM) would be much better for interpreters, but I'm not sure if Julia's language semantics / object model can allow it. Maybe some intelligent people out there can make the whole thing work, is what I was trying to say.
-
Julia: faster than Fortran, cleaner than Numpy
It could, but that is a lot more work than it sounds. It might be easier to make it possible to swap out the compiler for one that is much faster (LLVM is slow but does good optimisations, other compilers like cranelift are faster but produce slower code). There is a Julia interpreter but it was written in Julia itself (it was written to support debuggers), so it doesn't really solve the latency issues.
-
Julia: Faster than Fortran, cleaner than Numpy
If you need to run small scripts and can't switch to a persistent-REPL-based workflow, you might consider starting Julia with the `--compile=min` option. You can also reduce startup times dramatically by building a sysimg with PackageCompiler.jl
There is also technically an interpreter if you want to go that way [1], so in principle it might be possible to do the same trick javascript does, but someone would have to implement that.
[1] https://github.com/JuliaDebug/JuliaInterpreter.jl
-
A note from our sponsor - SaaSHub
www.saashub.com | 10 May 2024
Stats
JuliaDebug/JuliaInterpreter.jl is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of JuliaInterpreter.jl is Julia.
Popular Comparisons
- JuliaInterpreter.jl VS Diffractor.jl
- JuliaInterpreter.jl VS DaemonMode.jl
- JuliaInterpreter.jl VS Tullio.jl
- JuliaInterpreter.jl VS julia-numpy-fortran-test
- JuliaInterpreter.jl VS Infiltrator.jl
- JuliaInterpreter.jl VS rust
- JuliaInterpreter.jl VS rust
- JuliaInterpreter.jl VS DiffEqOperators.jl
- JuliaInterpreter.jl VS Catwalk.jl
- JuliaInterpreter.jl VS OMEinsum.jl
Sponsored