Recurrence equations lie at the heart of many computational paradigms
in...
Spatial dataflow architectures such as reconfigurable dataflow accelerat...
We introduce the Bayesian Compiler Optimization framework (BaCO), a gene...
We introduce Stardust, a compiler that compiles sparse tensor algebra to...
Real world arrays often contain underlying structure, such as sparsity, ...
We propose the Sparse Abstract Machine (SAM), an intermediate representa...
We introduce SpDISTAL, a compiler for sparse tensor algebra that targets...
We introduce a formal operational semantics that describes the fused
exe...
We introduce DISTAL, a compiler for dense tensor algebra that targets mo...
Sparse tensors arise in problems in science, engineering, machine learni...
While loop reordering and fusion can make big impacts on the constant-fa...
This document describes an attempt to develop a compiler-based approach ...
Image processing and machine learning applications benefit tremendously ...
Runtime compilation of runtime-constructed code is becoming standard pra...
We present a new algorithm for transposing sparse tensors called Quesadi...
This paper shows how to generate code that efficiently converts sparse
t...
We address the problem of optimizing mixed sparse and dense tensor algeb...
This paper shows how to build a sparse tensor algebra compiler that is
a...
This paper shows how to build a sparse tensor algebra compiler that is
a...
This paper shows how to optimize sparse tensor algebraic expressions by
...
Recent advances in compiler theory describe how to compile sparse tensor...