Orchestrated Co-scheduling, Resource Partitioning, and Power Capping on CPU-GPU Heterogeneous Systems via Machine Learning.
Issa SabaEishi ArimaDai LiuMartin SchulzPublished in: CoRR (2024)
Keyphrases
- heterogeneous systems
- grid environment
- machine learning
- data transfer
- parallel computing
- resource allocation
- graphics processing units
- multithreading
- scheduling algorithm
- parallel architectures
- resource constraints
- data access
- computing systems
- distributed architecture
- data mining
- data flow
- processing units
- data transmission
- real time
- power consumption
- application developers
- parallel machines
- scheduling problem
- grid computing
- legacy systems
- general purpose
- parallel programming
- web services
- parallel computers
- file system
- resource management
- distributed systems
- multiple types
- data management