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Tile: A New Language for Machine Learning
11–20 of 39 posts
Re: Tile: A New Language for Machine Learning
#12Not enough parentheses... ;-)
Re: Tile: A New Language for Machine Learning
#13Does it apply the same tricks as [0], the Tensor Algebra Compiler from MIT? [0] https://news.ycombinator.com/item?id=15599914
taco's runtime appears to be designed for large sparse data while we designed Tile specifically for the dense linear algebra operations in neural nets. Quite a bit of work has gone into making the Tile runtime do the necessary optimizations to make neural nets run efficiently on GPUs and other accelerator designs, none at all for sparse workloads. Given that I'd expect the internals to be fairly different.
Re: Tile: A New Language for Machine Learning
#14Not enough parentheses... ;-)
Come on, they still have a keyword AND two sets of parentheses AND a sigil AND a set of braces to define a function.
It's like they couldn't agree on which syntax to use, so they decided to use them all.
Re: Tile: A New Language for Machine Learning
#15Earlier quoted context omitted.
What's wrong with domain specific languages? SQL is a language for database manipulation, jq is a language for querying JSON, CSS is a language for styling documents, etc.
it would be more like an SQL for people wanting to do SQL in ML, but its not really what the article is talking about. i need another language to program machine learning in like i need another hole in my head.
But... that's not what this is. It's a tool to make writing device-agnostic ML frameworks easier. Consumers of said frameworks wouldn't even be aware of it.
Re: Tile: A New Language for Machine Learning
#16"making it many times easier to add support for GPUs"
Re: Tile: A New Language for Machine Learning
#177 Powerful Programming Languages For Doing Machine Learning
http://blog.hackerearth.com/powerful-programming-languages-f...
Python if a popular scientific language and a rising star for machine learning. I'd be surprised if it can take the data analysis mantle from R, but matrix handling in NumPy may challenge MATLAB and communication tools like IPython are very attractive and a step into the future of reproducibility.
Re: Tile: A New Language for Machine Learning
#18when i read "a language for X" I think "ok...no"
Domain Specific Languages are good thing for specialized applications. Here we want automatic differentiation, parallelization and vectorization.
It gets bad when general purpose language's features are added to allow things that the language wasn't designed for. A good interface to a GP language would be more relevant.
Re: Tile: A New Language for Machine Learning
#19Does it apply the same tricks as [0], the Tensor Algebra Compiler from MIT? [0] https://news.ycombinator.com/item?id=15599914
taco's runtime appears to be designed for large sparse data while we designed Tile specifically for the dense linear algebra operations in neural nets. Quite a bit of work has gone into making the Tile runtime do the necessary optimizations to make neural nets run efficiently on GPUs and other accelerator designs, none at all for sparse workloads. Given that I'd expect the internals to be fairly different.
Have you benchmarked Tile against Stalin∇?
https://github.com/Functional-AutoDiff/STALINGRAD
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Re: Tile: A New Language for Machine Learning
#20Earlier quoted context omitted.
taco's runtime appears to be designed for large sparse data while we designed Tile specifically for the dense linear algebra operations in neural nets. Quite a bit of work has gone into making the Tile runtime do the necessary optimizations to make neural nets run efficiently on GPUs and other accelerator designs, none at all for sparse workloads. Given that I'd expect the internals to be fairly different.
Have you benchmarked Tile against Stalin∇? https://github.com/Functional-AutoDiff/STALINGRAD Page 3: http://barak.pearlmutter.net/papers/ad2016b.pdf
That looks both clever and interesting, do you know if they have published any benchmarks on GPU or other accelerator targets?