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
- Joshua Patterson, principal data scientist at Accenture Labs, is utilizing NVIDIA GPUs and GPU-accelerated libraries to analyze large-scale network graphs for security threats.
- The use of NVIDIA's DGX-1 deep learning supercomputer and nvGRAPH library in CUDA 8 enables the analysis of 4 billion node graphs, significantly accelerating processing power.
- This technology is expected to reduce development cycles by months, according to Joshua Patterson.
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