Simplifying dependent reductions in the polyhedral model
Abstract
A Reduction – an accumulation over a set of values, using an associative and commutative operator – is a common computation in many numerical computations, including scientific computations, machine learning, computer vision, and financial analytics. Contemporary polyhedral-based compilation techniques make it possible to optimize reductions, such as prefix sums, in which each component of the reduction’s output potentially shares computation with another component in the reduction. Therefore an optimizing compiler can identify the computation shared between multiple components and generate code that computes the shared computation only once.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 04, 2021
- Source ID
- 10.1145/3434301
Entities
People
- Cambridge Yang
- Eric W. Atkinson
- Michael Carbin
Organizations
- Massachusetts Institute of Technology
- Office of Naval Research