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arXiv · 2512.16512

XTC, A Research Platform for Optimizing AI Workload Operators

Pompougnac Hugo·Guillon Christophe·Noiry Sylvain·Dutilleul Alban·Iooss Guillaume·Rastello Fabrice
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Abstract

Achieving high efficiency on AI operators demands precise control over computation and data movement. However, existing scheduling languages are locked into specific compiler ecosystems, preventing fair comparison, reuse, and evaluation across frameworks. No unified interface currently decouples scheduling specification from code generation and measurement. We introduce XTC, a platform that unifies scheduling and performance evaluation across compilers. With its common API and reproducible measurement framework, XTC enables portable experimentation and accelerates research on optimization strategies.

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Pompougnac Hugo, Guillon Christophe, Noiry Sylvain, Dutilleul Alban, Iooss Guillaume, Rastello Fabrice. 2025-12-18. XTC, A Research Platform for Optimizing AI Workload Operators. https://arxiv.org/abs/2512.16512

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