A review of self-scheduled strategies for numerical linear algebra on GPU

Key Points

• The review emphasizes the advantages of self-scheduled strategies in numerical linear algebra using GPU technology, improving processing efficiency.
• Key methodologies and frameworks are identified for optimizing matrix operations on GPUs, targeting faster computation.
• Observational analysis of various self-scheduling techniques across different systems showcases their effectiveness in parallel computation.
• These strategies may enable significant performance enhancements in numerical linear algebra, calling for further exploration and evaluation.