AI-Driven Approach for Portable GPU Kernels in High-Performance Computing
By
Jiajia Li
Baker's choice. Dense with flavour, light on filler.
Summary
This academic paper from North Carolina State University researchers presents an approach to leveraging AI ecosystems for creating portable and sustainable GPU kernels in High-Performance Computing (HPC). It addresses the challenge of developing optimized GPU kernels across evolving architectures, which remains a major productivity bottleneck in HPC. The work proposes using AI-based methods to improve code portability and sustainability across different GPU platforms, aiming to reduce the development burden on HPC programmers.
Key quotes
· 3 pulledHigh-Performance Computing (HPC) applications increasingly depend on GPUs, yet developing optimized kernels across evolving GPU architectures remains a major productivity bottleneck.
With a tile-based approach to GPU kernel development, the AI ecosystem can help automate and optimize code generation for diverse hardware backends.
This work demonstrates how leveraging large language models and AI tooling can reduce the manual effort required for GPU kernel portability in HPC environments.
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