Skip to main navigation
Skip to search
Skip to main content
Princeton University Home
Help & FAQ
Home
Profiles
Research units
Facilities
Projects
Research output
Press/Media
Search by expertise, name or affiliation
MemFlow: Memory-Driven Data Scheduling with Datapath Co-Design in Accelerators for Large-Scale Inference Applications
Qi Nie,
Sharad Malik
Electrical and Computer Engineering
Princeton Institute for Computational Science and Engineering
Research output
:
Contribution to journal
›
Article
›
peer-review
2
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'MemFlow: Memory-Driven Data Scheduling with Datapath Co-Design in Accelerators for Large-Scale Inference Applications'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Large-scale Inference
100%
Data Scheduling
100%
Accelerator Design
100%
DRAM Access
66%
Neural Network
33%
Hardware Accelerator
33%
Design Tools
33%
Singular Value Decomposition
33%
Performance Improvement
33%
Design Methodology
33%
Principal Coordinate Analysis (PCoA)
33%
Limited Resources
33%
Memory Hierarchy
33%
Data Access
33%
Energy-performance Tradeoff
33%
Inference Algorithms
33%
Scratchpad
33%
Scratchpad Memory
33%
Computer Science
Datapath
100%
Participatory Design
100%
Neural Network
25%
Hardware Accelerator
25%
Singular Value
25%
Memory Hierarchy
25%
Data Access
25%
Large Data Set
25%
Scratchpad Memory
25%
Principle Component Analysis
25%