6 papers
WingSpan: Concurrency and Dependence for Sparse and Structured Tensor Compilers
Adrian Gushin, Sang Yoon Kim, Willow Ahrens
Sparse tensors represent data that is mostly zero or some other compressible fill pattern. Such datasets can be massive, so optimized tensor algebra libraries and compilers have be…
The Continuous Tensor Abstraction: Where Indices are Real
Jaeyeon Won, Willow Ahrens, Teodoro Fields Collin +2
This paper introduces the continuous tensor abstraction, allowing indices to take real-number values (for example, A[3.14]). It also presents continuous tensor algebra expressions,…
Insum: Sparse GPU Kernels Simplified and Optimized with Indirect Einsums
Jaeyeon Won, Willow Ahrens, Joel S. Emer +1
Programming high-performance sparse GPU kernels is notoriously difficult, requiring both substantial effort and deep expertise. Sparse compilers aim to simplify this process, but e…
Galley: Modern Query Optimization for Sparse Tensor Programs
Kyle Deeds, Willow Ahrens, Magda Balazinska +1
The tensor programming abstraction is a foundational paradigm which allows users to write high performance programs via a high-level imperative interface. Recent work on sparse ten…
Finch: Sparse and Structured Tensor Programming with Control Flow
Willow Ahrens, Teodoro Fields Collin, Radha Patel +3
From FORTRAN to NumPy, tensors have revolutionized how we express computation. However, tensors in these, and almost all prominent systems, can only handle dense rectilinear intege…
SySTeC: A Symmetric Sparse Tensor Compiler
Radha Patel, Willow Ahrens, Saman Amarasinghe
Symmetric and sparse tensors arise naturally in many domains including linear algebra, statistics, physics, chemistry, and graph theory. Symmetric tensors are equal to their transp…