"PEARL: Enabling Portable, Productive, and High-Performance Deep ..."

Yuan Meng et al. (2024)

> Home

Details and statistics

DOI: 10.1145/3649153.3649193

access: closed

type: Conference or Workshop Paper

metadata version: 2024-08-28

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/cf/MengKSIP24
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/cf/MengKSIP24
Yuan Meng, Michael Kinsner, Deshanand P. Singh, Mahesh A. Iyer, Viktor K. Prasanna:
PEARL: Enabling Portable, Productive, and High-Performance Deep Reinforcement Learning using Heterogeneous Platforms. CF 2024

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.