Application of CPU in AI and Machine Learning
Renchao Yu · 2024
In recent years, the burgeoning fields of Artificial Intelligence (AI) and Machine Learning (ML) have increasingly permeated daily life, catalyzing significant advancements in technology. This rapid evolution has, in turn, necessitated the continual adaptation and enhancement of Central Processing Units (CPUs), which remain at the forefront of computational hardware. Despite these advancements, there has been a noticeable dearth in scholarly literature focusing on training neural network models exclusively on CPUs. This gap presents a substantial impediment to the exploration and advancement of CPU applications within AI and ML domains. Upon extensive literature review and analysis, it becomes evident that the CPU's role in AI and ML has not only been pivotal but has also retained distinct advantages despite the relative deceleration in its development trajectory. Current trends suggest that modern CPUs are increasingly moving towards an integrated architecture, incorporating specialized modules and fostering synergies with heterogeneous computing units. This paradigm shift underscores a critical question: How can we stimulate CPU development further and leverage its inherent strengths effectively? Addressing this query is essential for pushing the boundaries of CPU technology in the ever-evolving landscape of AI and ML.