PyGim: an Efficient Graph Neural Network Library for Real Processing-In-Memory Architectures
PROCEEDINGS OF THE ACM ON MEASUREMENT AND ANALYSIS OF COMPUTING SYSTEMS（2024）
Key words
machine learning,graph neural networks,sparse matrix-matrix multi- plication,library,multicore,processing-in-memory,near-data processing,memory systems,data movement bottleneck,DRAM,benchmarking,real-system characterization,workload characterization
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined