Joshua Patterson, principal data scientist of Accenture Labs shares how his team is using NVIDIA GPUs and GPU-accelerated libraries to quickly detect security threats by analyzing anomalies in large-scale network graphs.
“When we can move 4 billion node graphs onto a GPU and have the shared memory of all the other GPUs and have that connected processing power… it’s really going to cut-out months of development cycles,” said Joshua referring to NVLink in the recently announced NVIDIA DGX-1 deep learning supercomputer and the new nvGRAPH library in CUDA 8.
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Share Your Science: Visualizing 200M Cybersecurity Alerts Daily with GPUs
May 20, 2016
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AI-Generated Summary
- Accenture Labs applies NVIDIA GPUs and GPU-accelerated libraries to analyze anomalies in large-scale network graphs for rapid security threat detection.
- Principal data scientist Joshua Patterson notes that NVLink on the NVIDIA DGX-1 deep learning supercomputer can move 4 billion node graphs onto a GPU with shared memory across GPUs, cutting months from development cycles.
- The new nvGRAPH library in CUDA 8 enables this large-scale graph analytics capability.
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