Real-Time Machine Learning (RTML) Compiling Hardware Neural-Net Accelerators (CHANNA)

Abstract

The CHANNA project developed an open-source machine-learning accelerator generator (named Gemmini) that supports integration into a full system-on-a-chip design. Additionally, the team completed evaluations of generated accelerators running various machine learning (ML) workloads; demonstrated that the generator can produce competitive accelerators for a wide range of ML tasks; and developed a novel accelerator virtualization mechanism, AuRORA, to enable virtualized and disaggregated accelerator integration for many-accelerator-many-application systems.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2024
Accession Number
AD1229977

Entities

People

  • Borivoje Nikolic
  • Jonathan Ragan-Kelley
  • Krste Asanovic
  • Sophia Shao

Organizations

  • University of California, Berkeley

Tags

Fields of Study

  • Computer science

Readers

  • Aerospace Engineering.
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Parallel and Distributed Computing.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks