NPCI - GPU-Accelerated Processing for UPI-Scale Data
AI / PRIVACY / CYBER RELEVANCE
Relevant to scalable AI/data-processing infrastructure and the corresponding need for strong access, data-governance and security controls.
AI: HighPrivacy: ModerateCybersecurity: High
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- GPU-native processing
- dataframe analytics
- graph processing
- scalability/performance
PURVIEW
Describes GPU-accelerated processing techniques designed for data workloads at UPI scale, including high-performance dataframe, numerical and graph analytics. While primarily technical, it is relevant to AI governance because large-scale computation increases the ability to analyse transactional and network data, including for machine-learning and graph-based fraud detection. The technical architecture makes corresponding governance requirements more important: efficient processing must still operate within controlled access, data-minimisation, retention, audit and security boundaries. It therefore helps explain the infrastructure side of large-scale financial AI and why privacy and cybersecurity controls must scale together with compute and analytics capabilities.
Classification and legal status. Technical paper; non-binding.