In this video from the 2016 Blue Waters Symposium, George Slota from Pennsylvania State University presents: Extreme-scale Graph Analysis on Blue Waters. “In recent years, many graph processing ...
BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...
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New framework reduces memory usage and boosts energy efficiency for large-scale AI graph analysis
BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at the ...
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