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Found 4 papers, 3 papers with code
Benchmarking the Linear Algebra Awareness of TensorFlow and PyTorch
Linear algebra operations, which are ubiquitous in machine learning, form major performance bottlenecks.
Concurrent Alternating Least Squares for multiple simultaneous Canonical Polyadic Decompositions
We observe that, in practice, experts often have to compute multiple decompositions of the same tensor, each with a small number of components (typically fewer than 20), to ultimately find the best ones to use for the application at hand.
Linnea: Automatic Generation of Efficient Linear Algebra Programs
In order to combine the productivity offered by high-level languages, and the performance of low-level kernels, we are developing Linnea, a code generator for linear algebra problems.
Mathematical Software
Automatic Generation of Efficient Linear Algebra Programs
In order to both achieve the productivity that comes with high-level languages, and make use of the efficiency of low level kernels, we are developing Linnea, a code generator for linear algebra problems.
Mathematical Software
