Gotcha!
Thanks. I'm not familiar with dynamic linking. What will that do?
Any specific plans for python support?
Or julia. Which is 1000th better than js
It will eventually, iirc
Question please: Even though there is stated desire to support python etc vm, this will be hampered by the need for the client to download the large VM vs native code that can be distributed itself, correct?
Have you tried dask?
What about dynd? Iirc doesn't use iteration st all.
Woah!!! Cool
Make sure you use the devect macro or parallel accelerator if you're going to use vector iced code :)
It's not a would and gpod. Numba works like that right now, has better interoperability with python and less context switching. Numba is I easily installed on all systems through conda package manager and is easily used…
Actually, Numba array allocation in nopython mode is allowed now. What other numerical features are missing?
Numba obviate these issues
What would one need to use c or c++ to write a julia package? It's as fast as native code so no need to use multiple languages.
Numba would still be faster. It would fuse away any intermediates in the code and remove any Overhead to the compiled code. also have the option of devecting to loops. both of which are generally faster than vectorized…
Numbs compiles entire functions on and allows array expressions with allocation and loop fusion. I don't see the problem
Use numba to compile python loops or array expressions to fast llvm, and problem solved. I'm sticking with python.
That's just the data structure. Fitting models would be much tougher.
Will julia ever be popular for general computing and Web stuff? It's s till fast for non scientific use cases, has multi threading (in master) and is getting go like channels.
Julia!!!!! The answer to all these problems, both for general and science programming.
Dask has that, and scikit learn is moving that way also. It even beats spark for out of core work on a single machine
There's a dev branch that has been actively developed
Numba has list, Named tuples, and is working on define your own jit classes.
Numba has loop fusion, runtime, and soon multithreading parallel vectorized functions. How is that c like?
Gotcha!
Thanks. I'm not familiar with dynamic linking. What will that do?
Any specific plans for python support?
Or julia. Which is 1000th better than js
It will eventually, iirc
Question please: Even though there is stated desire to support python etc vm, this will be hampered by the need for the client to download the large VM vs native code that can be distributed itself, correct?
Have you tried dask?
What about dynd? Iirc doesn't use iteration st all.
Woah!!! Cool
Make sure you use the devect macro or parallel accelerator if you're going to use vector iced code :)
It's not a would and gpod. Numba works like that right now, has better interoperability with python and less context switching. Numba is I easily installed on all systems through conda package manager and is easily used…
Actually, Numba array allocation in nopython mode is allowed now. What other numerical features are missing?
Numba obviate these issues
What would one need to use c or c++ to write a julia package? It's as fast as native code so no need to use multiple languages.
Numba would still be faster. It would fuse away any intermediates in the code and remove any Overhead to the compiled code. also have the option of devecting to loops. both of which are generally faster than vectorized…
Numbs compiles entire functions on and allows array expressions with allocation and loop fusion. I don't see the problem
Use numba to compile python loops or array expressions to fast llvm, and problem solved. I'm sticking with python.
That's just the data structure. Fitting models would be much tougher.
Will julia ever be popular for general computing and Web stuff? It's s till fast for non scientific use cases, has multi threading (in master) and is getting go like channels.
Julia!!!!! The answer to all these problems, both for general and science programming.
Dask has that, and scikit learn is moving that way also. It even beats spark for out of core work on a single machine
There's a dev branch that has been actively developed
Numba has list, Named tuples, and is working on define your own jit classes.
Numba has list, Named tuples, and is working on define your own jit classes.
Numba has loop fusion, runtime, and soon multithreading parallel vectorized functions. How is that c like?