DirectNVM: Hardware-accelerated NVMe SSDs for High-performance Embedded Computing

Abstract

With data-intensive artificial intelligence (AI) and machine learning (ML) applications rapidly surging, modern high-performance embedded systems, with heterogeneous computing resources, critically demand low-latency and high-bandwidth data communication. As such, the newly emerging NVMe (Non-Volatile Memory Express) protocol, with parallel queuing, access prioritization, and optimized I/O arbitration, starts to be widely adopted as a de facto fast I/O communication interface. However, effectively leveraging the potential of modern NVMe storage proves to be nontrivial and demands fine-grained control, high processing concurrency, and application-specific optimization. Fortunately, modern FPGA devices, capable of efficient parallel processing and application-specific programmability, readily meet the underlying physical layer requirements of the NVMe protocol, therefore providing unprecedented opportunities to implementing a rich-featured NVMe middleware to benefit modern high-performance embedded computing.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jan 31, 2022
Source ID
10.1145/3463911

Entities

People

  • Amro Awad
  • Mingjie Lin
  • Yu Zou

Organizations

  • Defense Advanced Research Projects Agency
  • North Carolina State University
  • University of Central Florida

Tags

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Parallel and Distributed Computing.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy