Emerging Platforms Meet Emerging LLMs: A Year-Long Journey of Top-Down Development

arXiv:2404.09151v1 Announce Type: cross
Abstract: Deploying machine learning (ML) on diverse computing platforms is crucial to accelerate and broaden their applications. However, it presents significant software engineering challenges due to the fast evolution of models, especially the recent \llmfull{s} (\llm{s}), and the emergence of new computing platforms. Current ML frameworks are primarily engineered for CPU and CUDA platforms, leaving a big gap in enabling emerging ones like Metal, Vulkan, and WebGPU.
While a traditional bottom-up development pipeline fails to close …

abstract applications arxiv challenges computing cs.lg cs.se current development diverse emergence engineering evolution however journey llm llms machine machine learning platforms software software engineering type