Accelerating Floating-Point Computations with Intel AMX

Summary

High-performance computing, especially for machine learning, often relies on GPUs, but there is a need for cost-effective CPU-based alternatives. This document explores the Intel AMX accelerator, available in newer Intel CPUs, to accelerate floating-point computations using mixed precision. The research demonstrates how to implement and achieve performance gains using AMX with bfloat16 data types in C++, Python, and libraries like PyTorch and TensorFlow, providing a comprehensive understanding of its potential on the Kestrel HPC machine.

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