ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1903.07676
  4. Cited By
Software-defined Design Space Exploration for an Efficient DNN
  Accelerator Architecture

Software-defined Design Space Exploration for an Efficient DNN Accelerator Architecture

18 March 2019
Y. Yu
Yingmin Li
Shuai Che
N. Jha
Weifeng Zhang
ArXivPDFHTML

Papers citing "Software-defined Design Space Exploration for an Efficient DNN Accelerator Architecture"

3 / 3 papers shown
Title
HitGNN: High-throughput GNN Training Framework on CPU+Multi-FPGA
  Heterogeneous Platform
HitGNN: High-throughput GNN Training Framework on CPU+Multi-FPGA Heterogeneous Platform
Yi-Chien Lin
Bingyi Zhang
Viktor Prasanna
GNN
32
5
0
02 Mar 2023
CODEBench: A Neural Architecture and Hardware Accelerator Co-Design
  Framework
CODEBench: A Neural Architecture and Hardware Accelerator Co-Design Framework
Shikhar Tuli
Chia-Hao Li
Ritvik Sharma
N. Jha
36
13
0
07 Dec 2022
Bifrost: End-to-End Evaluation and Optimization of Reconfigurable DNN
  Accelerators
Bifrost: End-to-End Evaluation and Optimization of Reconfigurable DNN Accelerators
Axel Stjerngren
Perry Gibson
José Cano
34
4
0
26 Apr 2022
1