29 citations · 39 across the 5 of their papers we have counts for
8 papers
Stardust: Compiling Sparse Tensor Algebra to a Reconfigurable Dataflow Architecture
Olivia Hsu, Alexander Rucker, Tian Zhao +2
We introduce Stardust, a compiler that compiles sparse tensor algebra to reconfigurable dataflow architectures (RDAs). Stardust introduces new user-provided data representation and…
DISTAL: The Distributed Tensor Algebra Compiler
Rohan Yadav, Alex Aiken, Fredrik Kjolstad
We introduce DISTAL, a compiler for dense tensor algebra that targets modern distributed and heterogeneous systems. DISTAL lets users independently describe how tensors and computa…
An Attempt to Generate Code for Symmetric Tensor Computations
Jessica Shi, Stephen Chou, Fredrik Kjolstad +1
This document describes an attempt to develop a compiler-based approach for computations with symmetric tensors. Given a computation and the symmetries of its input tensors, we der…
Compiling Halide Programs to Push-Memory Accelerators
Qiaoyi Liu, Dillon Huff, Jeff Setter +8
Image processing and machine learning applications benefit tremendously from hardware acceleration, but existing compilers target either FPGAs, which sacrifice power and performanc…
Copy-and-Patch Compilation: A fast compilation algorithm for high-level languages and bytecode
Haoran Xu, Fredrik Kjolstad
Fast compilation is important when compilation occurs at runtime, such as query compilers in modern database systems and WebAssembly virtual machines in modern browsers. We present…
Automatic Generation of Efficient Sparse Tensor Format Conversion Routines
Stephen Chou, Fredrik Kjolstad, Saman Amarasinghe
This paper shows how to generate code that efficiently converts sparse tensors between disparate storage formats (data layouts) such as CSR, DIA, ELL, and many others. We decompose…