That is correct (and we appreciate the citation). The tensor compiler (taco) has focused on compiling expressions that contain one or more sparse tensors so far and, even though it can generate code for dense…
The story for sparse matrices is more complicated. Because of the dependencies imposes by sparse data structures (you don’t have random access and often have to traverse them) you cannot do loop ruling without adding if…
We’ve tried to engineer it to emit clean code, but seems we left in some unused variables. The C compilers dead code elimination should remove those though.
We currently compile to C code and use the system Compiler to compile it further. For dense loop nests it does a good job of auto-vectorizing, but we believe there’s good opportunities for doing something custom,…
That is a good idea, but we are only so many. One student in the Julia group is developing Julia bindings though, and we hope to make C/python bindings. The inner workings are published in the paper “The Tensor Algebra…
Thanks, that is really nice of you :)
For sure, as you point out, many such kernels have been written, going at least as far back as 1967. We believe our contribution is being able to generate kernels for all the expressions. Thanks for the reference…
I don't know of an explicit list like this, but some areas that we are particularly interested in are: data analytics (tensor factorization), machine learning (anything sparse including perhaps sparse neural networks),…
Thanks! I really like that conference!
Hi, that sounds very interesting and I hope someone works on it. We're only so many people though, and we have several things we want to do that will at least occupy us until next summer.
Larry chose to focus on the big data part, because it is intuitive. But I think you're absolutely correct, that it has applications in physics/chemistry (and machine learning too). We're actually talking to people in…
Hi Hacker News! I’m one of the developers. This project was also featured in MIT News yesterday: http://news.mit.edu/2017/faster-big-data-analysis-tensor-alg... The code is available at:…
Thanks! Yes, we have an `apps` directory in the source tree that we will add programs to. These programs are tested by our test suites, and will later be our performance regressions. I'm actually working with some…
Very valid concerns. If you use C++ it's easy to interoperate with Simit, since Simit is a C++ library with an online compiler that compile the time steppers. You build the graph using a C++ api and then you run a Simit…
We needed new language constructs (the matrix assembly) and a new type system for matrices that ties back to the graph to make it simple and fast. It is also not limited to FEM codes. It can be used to write any…
It actually shares two authors (Jon and Saman). Their work on Halide was amazing!
That is correct (and we appreciate the citation). The tensor compiler (taco) has focused on compiling expressions that contain one or more sparse tensors so far and, even though it can generate code for dense…
The story for sparse matrices is more complicated. Because of the dependencies imposes by sparse data structures (you don’t have random access and often have to traverse them) you cannot do loop ruling without adding if…
We’ve tried to engineer it to emit clean code, but seems we left in some unused variables. The C compilers dead code elimination should remove those though.
We currently compile to C code and use the system Compiler to compile it further. For dense loop nests it does a good job of auto-vectorizing, but we believe there’s good opportunities for doing something custom,…
That is a good idea, but we are only so many. One student in the Julia group is developing Julia bindings though, and we hope to make C/python bindings. The inner workings are published in the paper “The Tensor Algebra…
Thanks, that is really nice of you :)
For sure, as you point out, many such kernels have been written, going at least as far back as 1967. We believe our contribution is being able to generate kernels for all the expressions. Thanks for the reference…
I don't know of an explicit list like this, but some areas that we are particularly interested in are: data analytics (tensor factorization), machine learning (anything sparse including perhaps sparse neural networks),…
Thanks! I really like that conference!
Hi, that sounds very interesting and I hope someone works on it. We're only so many people though, and we have several things we want to do that will at least occupy us until next summer.
Larry chose to focus on the big data part, because it is intuitive. But I think you're absolutely correct, that it has applications in physics/chemistry (and machine learning too). We're actually talking to people in…
Hi Hacker News! I’m one of the developers. This project was also featured in MIT News yesterday: http://news.mit.edu/2017/faster-big-data-analysis-tensor-alg... The code is available at:…
Thanks! Yes, we have an `apps` directory in the source tree that we will add programs to. These programs are tested by our test suites, and will later be our performance regressions. I'm actually working with some…
Very valid concerns. If you use C++ it's easy to interoperate with Simit, since Simit is a C++ library with an online compiler that compile the time steppers. You build the graph using a C++ api and then you run a Simit…
We needed new language constructs (the matrix assembly) and a new type system for matrices that ties back to the graph to make it simple and fast. It is also not limited to FEM codes. It can be used to write any…
It actually shares two authors (Jon and Saman). Their work on Halide was amazing!