The sparse tensor algebra compiler (keynote)

Tensor algebra is a powerful tool with applications in machine learning, data analytics, engineering, and science. Increasingly often the tensors are sparse, which means most components are zeros. To get the best performance, currently programmers are left to write kernels for every operation, with different mixes of sparse and dense tensors in different formats. There are countless combinations, which makes it impossible to manually implement and optimize them all. The Tensor Algebra Compiler (TACO) is the first system to automatically generate kernels for any tensor algebra operation on tensors in any of the commonly used formats. Its performance is competitive with best-in-class hand-optimized kernels in popular libraries, while supporting far more tensor operations. For more information, see http://tensor-compiler.org.