Microarchitectural mechanisms to exploit value structure in SIMT architectures

Abstract

SIMT architectures improve performance and efficiency by exploiting control and memory-access structure across data-parallel threads. Value structure occurs when multiple threads operate on values that can be compactly encoded, e.g., by using a simple function of the thread index. We characterize the availability of control, memory-access, and value structure in typical kernels and observe ample amounts of value structure that is largely ignored by current SIMT architectures. We propose three microarchitectural mechanisms to exploit value structure based on compact affine execution of arithmetic, branch, and memory instructions. We explore these mechanisms within the context of traditional SIMT microarchitectures (GP-SIMT), found in general-purpose graphics processing units, as well as fine-grain SIMT microarchitectures (FG-SIMT), a SIMT variant appropriate for compute-focused data-parallel accelerators. Cycle-level modeling of a modern GP-SIMT system and a VLSI implementation of an eight-lane FG-SIMT execution engine are used to evaluate a range of application kernels. When compared to a baseline without compact affine execution, our approach can improve GP-SIMT cycle-level performance by 4-17% and can improve FG-SIMT absolute performance by 20-65% and energy efficiency up to 30% for a majority of the kernels.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jun 23, 2013
Source ID
10.1145/2508148.2485934

Entities

People

  • Christopher Batten
  • Christopher Torng
  • Derek Lockhart
  • Ji Kim
  • Shreesha Srinath

Organizations

  • Cornell University
  • Defense Advanced Research Projects Agency
  • Intel Corporation
  • National Science Foundation
  • Nvidia
  • Synopsys

Tags

Fields of Study

  • Computer science

Readers

  • Allergy and Immunology.
  • Distributed Systems and Data Platform Development
  • Neural Network Machine Learning.

Technology Areas

  • Space